Interaction with Endogenous Microorganisms, Comamonas testosteroni Enhanced the Degradation of Polycyclic Aromatic Hydrocarbon in Soil

Interaction with Endogenous Microorganisms, Comamonas testosteroni Enhanced the Degradation of Polycyclic Aromatic Hydrocarbon in Soil | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Interaction with Endogenous Microorganisms, Comamonas testosteroni Enhanced the Degradation of Polycyclic Aromatic Hydrocarbon in Soil Xueting Sun, Xin Li, Yue Cui, Ziwei Jiang, Qiao Wang, Qian Lu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-307586/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study was to explore the functional role of Comamonas testosteroni ( Ct ) on soil indigenous microorganisms, and analyze the effect of Ct on PAHs degradation in PAH-contaminated soil. Results showed that inoculation of Ct could degrade naphthalene (Nap), phenanthrene (Phe), and benzo [α] pyrene (BaP) significantly. The degradation rate of Nap, Phe and BaP was 81.18%, 63.38% and 37.98% on day 25, respectively, suggesting that the low molecular weight of Nap and Phe were easier to be degraded by microorganisms than BaP. Network analysis showed that inoculation of Ct significantly increased the bacteria closely related to PAHs. Structural equation models confirmed Steroidobacter as functional bacteria could affect the degradation of Nap and BaP. Inoculated Ct could effectively enhance the synergy among indigenous bacteria to degrade PAHs. This would be helpful to understand the function of inoculated strains in PAH-contaminated soil and identify functional microorganisms of PAHs remediation. Environmental Engineering Soil remediation Polycyclic aromatic hydrocarbons Comamonas testosteroni Functional microbial interactions Network analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Polycyclic aromatic hydrocarbons (PAHs) are a class of fused-polycyclic aromatic ring compounds that are mainly discharged from the incomplete combustion of fossil fuels or other organic materials (Humel et al., 2020 ). PAHs are of great concern because of their lipophilic, mutagenic, and carcinogenic properties. The low aqueous solubility and the high solid-water distribution ratios promote PAH accumulation in the solid phases of the terrestrial environment (Lu et al., 2019a ). With the development of industry, the concentration of PAH in the soil is typically detected at a relatively high-level in recent years (Sun et al., 2018). Long-term PAH pollution disturbs the soil ecological environment, causing severe potential risks to soil organisms and humans (Li et al., 2019a ). Previous studies have found that naphthalene (Nap), phenanthrene (Phe) and pyrene (Pyr), etc. were predominant PAHs in 16 precedence-controlled PAHs on the United States Environmental Protection Agency (USEPA) priority pollutant list (Patel et al., 2018 ; Zhang and Chen, 2017 ). Nap is the lowest molar mass of the PAHs and it can be adsorbed onto the soil due to its adsorption capacity and high-water solubility (Mendes et al., 2020 ). Benzo [α] pyrene (BaP) is considered a priority control pollutant because of its carcinogenic, teratogenic and mutagenic effects (Bhattacharya et al., 2014 ). Therefore, it is necessary to find suitable remedial technology to alleviate the possible environmental risk posed by PAHs in soils. In recent years, several physical, chemical, and biological technologies have been established and applied to remediation of PAH-contaminated soil (Varjani et al., 2017). Compared to the high cost and potential secondary contamination incurred by physical and chemical methods, bioremediation, especially microbial remediation, is considered a cost-effective remediation technology (Vila et al., 2015 ). Many microorganisms including bacteria and fungi have been isolated from PAH-contaminated sites with the ability to degrade PAHs efficiently. PAH-degrading bacteria can metabolize PAHs as a source of carbon and energy in soils (Aranda et al., 2016), and they play an important role in the degradation of PAHs. Some bacteria such as Pseudomonas , Sphingomonas , Bacillus , Sphingobacterium and Mycobacterium have been widely recognized and used to degrade PAHs (Venkateswar et al., 2015 ; Mallick, et al., 2011 ). A previous study showed that a mixed inoculation of Bacillus subtilis and P. aeruginosa removed 82.2% of Phe within 30 days under laboratory conditions (Zhao et al., 2011 ). The isolated strain Comamonas sp. ZF-3 had efficient biodegradability of phenolic compounds and heterocyclic compounds in coking wastewater (Yuan et al., 2020 ). It can be seen that bacteria have the ability to degrade PAHs with complex structures very efficiently. However, the biodegradation of PAHs solely utilizing native bacteria under natural conditions is a very slow process. The efficiency of bacteria to degrade PAHs are related to many factors, mainly including the concentration of effective bacteria, environmental factors, and the degree of soil PAHs pollution. Therefore, finding the optimistic degradation conditions is the key to improve the degradation efficiency. Comamonas testosteroni ( C. testosteroni ) is a gram-negative bacterium belonging to the class of β-proteobacteria, which is widely found in soil, activated sludge and seabed sediments. C. testosteroni can degrade many sterols and PAHs, and even use these complex organic compounds as the sole carbon source (Zalesak et al., 2017 ). Moreover, C. testosteroni can degrade heavy metal pollutants in the environment (Zheng et al., 2014 ). It has a strong adaption to change environments and xenobiotics. With these attractive features, researchers have begun to explore C. testosteroni strains as environmental bioremediation hosts (Tang et al., 2018 ). However, due to the complexity of the natural ecosystem, finding the optimal inoculation conditions for inoculants is crucial to maximizing the degradation of pollutants. In this study, we inoculated C. testosteroni into PAHs (Nap, Phe, BaP) contaminated soil under an optimal system. The principal goals of this study were: (1) to determine the optimal degradation system through the orthogonal analysis to maximize the degradation of PAHs inoculated with C. testosteroni , (2) to analyze the effect of inoculation of C. testosteroni on the degradation of PAHs in the soil under the system, (3) to assess the relationship among inoculants, indigenous microbes and the degradation of PAHs. This research will provide useful perspectives and methods for solving PAHs soil pollution by inoculating C. testosteroni . 2. Material And Methods 2.1 Preparation of inoculant C.testosterone strain (NR029161.2) were selected as inoculum. The inoculum was prepared by growing in lysogeny broth (LB) agar plates at 28°C for 14 h. The independent colony was inoculated into LB liquid medium and incubated at 28°C for 14 h on a rotary shaker (180 rpm). Exponential growth-phase cells were then harvested by centrifugation at 4°C for 15 min (4500 rpm), discarded the supernatant and resuspended individually in sterile water. 2.2 Experimental design and sample collection Soils were collected from topsoil at a depth of 0–20 cm from Harbin Normal University, China. They were air-dried at room temperature (around 25℃) and then passed to a 2 mm sieve. Contaminated soil was prepared by adding Nap, Phe and BaP (> 98% purity; Sigma-Aldrich, Shanghai, China) stock solution (in acetone) to sieved soil with different concentrations (Table 1 ). Table 1 The combination of parameters based on orthogonal table with 3 factors and 3 levels. Factors Level A Concentration of total PAHs (µg/kg) (Nap/Phe/BaP) B Concentration of bacteria (DW, %) C Temperature (℃) 1 4800 (2400/800/1600) 0 30 2 2400 (1200/400/800) 0.01 20 3 1200 (600/200/400) 0.05 10 The orthogonal design was used to find the optimal PAHs degradation system. They were designed with 3 factors and 3 levels of the orthogonal table as shown in Table 1 . PAHs concentration (Factor A), bacteria concentration (Factor B) and temperature (Factor C) were chosen as three factors. The levels of total PAHs concentrations were 4800 µg/kg, 2400 µg/kg and 1200 µg/kg, respectively. The levels of C.testosterone concentrations were 0, 0.01% and 0.05%. The levels of temperature were 30 ℃, 20 ℃ and 10 ℃. Samples of the soils, each weighing 200 g (dry weight, DW) was placed in a glass container with 500 g capacity and covered with aluminum foil. According to the results of the orthogonal experiment, the optimal conditions were selected to study the changes in the degradation process of soil PAHs. Two groups of the experiment were carried out, including soil with Nap, Phe and BaP (CK), and inoculated of C.testosteroni in soil with Nap, Phe, BaP (CT). The experiment continued for 25 days and each experimental treatment was repeated three times. The samples were collected on days 0, 2, 4, 6, 10, 15, 20 and 25. Each sample was divided into two parts, one part was sealed with tinfoil bags, and quick-frozen with liquid nitrogen, then stored at -80℃ for microbial community and molecular biological analysis, the other part was stored at 4℃ for PAHs analysis. 2.3 Soil PAH analysis Sample extraction and purification were performed following the USEPA Method 3550B (USEPA 1996 ) with some modifications. Briefly, an amount of 10 g of each soil sample with diatomite mixtures was extracted with the ASE 150 (Dionex Corp, USA) through n-hexane/dichloromethane (1:1, v/v) solvent mixtures. The extraction was evaporated by a rotary vacuum evaporator, concentrated to about 1 mL, and then loaded on a silica gel column for purification, and the residual solvent was removed by nitrogen. The residue was dissolved in 1 mL of n-hexane. PAHs were analyzed by Agilent 7890A gas chromatography system combined with 5975C mass selective detector (GC/MS), and PAHs were separated by HP-5MS (30m×0.32mmi.d.×0.25µm film thickness), details could be found in Li et al. ( 2019a ). 2.4 qPCR and high throughput sequencing Soil microbial DNA was extracted by using the Ezup column soil genomic DNA extraction kit (Sangon Biotech, Shanghai, China). The genes ( 16SrRNA , 3α-HSD/CR and NahAc ) abundance were determined by real-time fluorescent quantitative PCR (qPCR). It was performed on each DNA template by using the SYBR Green Master Mix on the ABI 7500 Real-Time PCR system. The primers and amplification conditions were listed in Table S1. The qPCR reaction conditions as follows: pre-denaturation for 30s at 95℃, denaturation for 10s at 95℃, annealing for 30s at 60℃, 40 cycles. The qPCR reaction mixture consisted of 2µL of DNA template, 10µL of 2×ChamQ Universal SYBR qPCR Master mix, 0.4µL of 50×Rox Reference Dye 2, 0.4µL each forward and reverse primer, to a final volume of 20µL with ddH 2 O. The 16SrRNA gene comprising V3 and V4 hypervariable regions was amplified by PCR using the forward primer 341F (5'- CCTACGGRRBGCASCAGKVRVGAAT-3') and reverse primer 806R (5'-GGACTACNVGGGTWTCTAATCC-3'). High-throughput sequencing of PCR product was performed on an Illumina MiSeq platform (Illumina, San Diego, CA, USA) at GENEWIZ, Inc. (China). 2.5 Data analysis SPSS 25.0 and Origin 2018 were used for statistical analysis of the orthogonal experiment and PAHs content. The changes in the microorganism community and the relationships between microbes and functional gene were analyzed by using the nonmetric multidimensional scaling ordination (NMDS) and redundancy analyses (RDA), both of them were conducted by Canoco5.0 software. The relationship between PAHs and microorganisms was analyzed by network analysis (Cytoscape 3.6.1). The structural equation model (SEM) was performed by the SPSS package of Amos 20.0. Functional capacity of the bacteria was predicted based on the bacteria composition using the phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt), functional genes were predicted based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database ( https://www.kegg.jp/ ). 3. Results And Discussion 3.1 Orthogonal analysis Inoculation was a favorable way to biodegrade PAHs. However, many factors affect the degradation of PAHs by microorganisms, temperature, indigenous microbial community structure, and inoculum concentration. The orthogonal experiment is a versatile optimization and economical experimental design method for arranging experiments with multiple factors and multiple levels (Mu et al., 2020 ). To evaluate the effectiveness of environmental factors on PAHs degradation by C. testosteroni , the orthogonal test was adopted to three factors and three levels (Table 1 ), and the results were presented in Table 2 . A1B2C2 was the optimal condition of PAHs degradation in this study. The degradation rate of total PAHs reached up to 58.09% on day 25 when the concentration of PAHs (Nap/Phe/BaP) was 4800 (2400/800/1600) µg/kg, the concentration of bacteria was 0.01% and the temperature was 20℃. In contrast, under the conditions of 10℃ with lower PAHs concentration, PAHs was only decreased 9.39% (A3B1C3). The above results indicate that suitable temperature or suitable inoculation concentration of C. testosteroni was beneficial to the degradation of PAHs. Table 2 The contribution of orthogonal experimental factors to the degradation rate of PAHs Experimental numbers Factor Result A B C Total PAHs degradation rate(%) A1B1C1 1 1 1 31.01 A1B2C2 1 2 2 58.09 A1B3C3 1 3 3 24.98 A2B1C2 2 1 2 21.01 A2B2C3 2 2 3 49.52 A2B3C1 2 3 1 18.62 A3B1C3 3 1 3 9.39 A3B2C1 3 2 1 39.03 A3B3C2 3 3 2 26.81 \({K}_{1}\) 114.08 61.41 88.65 \({K}_{2}\) 89.15 146.64 105.91 \({K}_{3}\) 75.23 70.41 83.89 \(\stackrel{-}{{K}_{1}}\) 38.03 20.47 29.55 \(\stackrel{-}{{K}_{2}}\) 29.72 48.88 35.30 \(\stackrel{-}{{K}_{3}}\) 25.08 23.47 27.96 Optimal Level A1 B2 C2 \({R}_{j}\) 12.95 28.41 7.34 \({\text{K}}_{i}\) represents the value of the i-th level, \(\stackrel{-}{{K}_{i}}\) represents the mean of the i-th level, and \({\text{R}}_{j}\) represents the range of the factor j . In order to analyze the influence of various factors on the degradation efficiency of PAHs, the range analysis was performed on the orthogonal experiment results. Base on the results of range analysis, the order among the factors was arranged according to the magnitude of the range (Table 2 ). The greater the range, the greater the influence of factor j on the test index. For the PAHs degradation efficiency, the order of significant influence of various factors was as follows: bacteria concentration > PAHs concentration > temperature. These results revealed that the inoculation level of C. testosteroni had significant influences on the degradation of PAHs. 3.2 Concentrations and degradation of PAHs Based on the optimal system in the orthogonal experiment (A1B2C2), the dynamic characteristics of Nap, Phe and BaP degradation in the soil were further analyzed. Figure 1 showed the concentration changes of Nap, Phe and Bap at different times after inoculation during 25 days in CT. The concentration of these PAHs was showed a downward trend and the degradation trends of Phe and BaP were similar (Fig. 1 a). Initially, Nap, Phe and BaP were 2315µg/kg, 770µg/kg and 1529µg/kg, respectively. At day 25, these PAHs decreased to a minimum value, and there were significantly lower than the initial ones ( p Nap (63.4%) > BaP (38.0%) at day 25. The degradation rate of Nap was rapidly increased to 54.01% on the 10th day and then increased slowly by only 9.4% on the 25th day compared with that on the 10th day. At the end of the experiment, the accumulation of Nap degradation was 1467µg/kg. Phe and BaP were effectively degraded and the degradation rate was 43.8% and 21.0% during 10 days, respectively. Phe had a high degradation rate in the following 15 days (37.8%), however, the degradation rate of BaP was lower than that of Phe. BaP was composed of 5-ring polyarenes, which belongs to high molecular weight PAHs (HMW-PAHs, ≥ 5 rings). The solubility of PAHs was one of the limiting factors for PAHs degradation. The increases in the molecular weight of PAHs lead to a decrease in their biodegradability (Ghosal et al., 2016 ). In the first 10 days, the degradation rate was Nap > Phe > Bap, and Nap was significantly higher than other PAHs in CT ( p < 0.05). However, in the following 15 days, Nap had the lowest degradation rate (9.4%) compared with other PAHs. Previous research has shown that HMW-PAHs were converted into low molecular weight PAHs (LMW-PAHs, < 4 rings) and then degraded (Minkina et al., 2019 ). We speculated that BaP and Phe might be converted into Nap for further degradation, which should be the main reason for the low Nap degradation rate detected from 10-25days. The degradation rate of Phe was the highest (81.2%) within 25 days, indicating that inoculation of C. testosteroni effectively promoted the Phe degradation. In other words, under the condition of A1B2C2, inoculation of C. testosteroni could rapidly reduce Nap in a short time, and effectively decline the concentration of Phe and BaP. The degradation of PAHs might be due to the inoculation of C. testosteroni or it was promoting the synergism of indigenous microorganisms. 3.3 Microbial performance under PAHs expose in soil The microbial richness could be reflected by the Ace index (Sengupta et al., 2015). The microbial richness of CK and CT under PAHs expose was decreased, however, it was generally higher in CT than that in CK except on the 6th day (Fig. 2 a). The main reason might be related to the relative abundance of C. testosteroni , which was significantly increased on day 6 (> 60%) and then species richness was reduced. The diversity of microorganisms was investigated according to the Shannon index (Lu et al., 2018 ). In this study, the diversity of the CT was different compared with CK (Fig. 2 a). Inoculation of C. testosteroni could decrease the bacterial diversity during 0–6 days and then increased in the later period (10–25 days). Inoculation of C. testosteroni could change the bacterial diversity and richness. NMDS was used to identify differences in the bacterial community for each group (Fig. 2 b), which further showed that the bacterial community was different between the inoculated group (CT) and non-inoculated group (CK). Under PAHs exposure, bacterial community composition changed rapidly during 25 days. Moreover, the microbial community structure of the CK from 0–6 d was relatively similar, however, it was opposite in CT, which might be caused by the inoculation of C. testosteroni . The bacterial community structure was changed continuously in CK, suggesting that the PAHs might be harmful to bacterial metabolism and survival and then bacterial community succession. Notably, samples from CK and CT were grouped in diverse polygonal regions and no intersection of the bacterial communities between the two groups, suggesting that C. testosteroni inoculant affected bacterial communities due to its synergistic effect on indigenous bacteria in the soil. High-throughput sequencing results showed that the soil bacterial community mainly originated from 25 phyla. The bacterial community composition of the two groups was similar at the phylum level. The dominant phylum consisted of Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Gemmatimonadetes, and the relative abundances accounted for 21.8–53.5%, 13.94–37.25%, 8.27–35.05%, 5.36–19.51%, 3.71–6.89%, 2.73–6.38%, respectively (Fig. S1). Proteobacteria and Acidobacteria have the highest abundance, accounting for about 60% on average and this phenomenon was similar to the result of Delgado et al. ( 2018 ). The abundance of Proteobacteria was higher in CT than that in CK, which might be caused by the inoculants of C. testosteroni which belongs to Proteobacteria. The classified dominant genera in the top 30 abundance of the bacterial community composition in soils were plotted as a relative abundance map of the genera level (Fig. 2 c). The dominant bacterial genus mainly includes Comamonas , Sphinomonas , RB41 , Pseudarthrobacter , Flavobacterium , Lysobacter , with relative abundances ranging from 0 to 37.73%, 1.88 to 15.2%, 3.25 to 7.53%, 0.47 to 18.53%, 0.03 to 11.71%, 0.18 to 4.94%, respectively. In the CT, Comamonas was the main genus, showing a fluctuating change, peaking at day 6 and disappearing at day 25. The abundance of Sphingomonas and RB41 showed a gradual upward trend and became the main genus at day 25 (Fig. 2 c). Comamonas and Sphingomonas could effectively degrade PAHs (Smułek et al., 2020). Moreover, the concentration of Nap, Phe and BaP were decreased and reached the minimum at day 25 in this study. It was proved that the inoculants could better adapt to the soil conditions and perform their functions or cooperate with the indigenous microorganism to degrade PAHs. The abundance of Flavobacterium was higher at 0-4d and then suddenly decreased from day 6 to day 25 in CT, while it was extremely low in CK (0.03–0.18%). Previous research showed Flavobacterium had the potential to degrade PAHs (Ahmad et al., 2019 ). The microbial community structure of the CK was a small change in the early stage, but the inoculation had a significant effect on the microbial community. We speculated that the degradation of the PAHs in the CT was closely related to the dynamic changes of microorganisms, and C. testosteroni might further degrade PAHs by affecting indigenous bacteria. It is worth noting that the abundance of Pseudarthrobacter was high at 25d in the CK. The study of Li et al. ( 2019b ) reported that Pseudarthrobacter was affected by PAHs exposure, which could be used as an important indicator of soil PAH pollution, indicating that PAHs pollution at day 25 was worse in CK compared with CT. 3.4 Quantitative analysis of gene abundance 16SrRNA gene was present in all bacterial genomes, and it was generally used as a marker gene for bacterial classification. In this study, the 16SrRNA gene copy number was measured to determine the changes in bacterial quantity in the soil. As shown in Fig. 2 d, the average abundance of 16SrRNA gene in CT was generally higher than that in CK during 0-25d except for the 15d and ranged from 242.3 to 620.5 log copies/gDNA, indicating that C. testosteroni could increase the abundance of bacteria. Moreover, the abundance of the 16SrRNA gene were obvious fluctuations in CT might due to the impact of PAHs or the competition among microorganisms. 3α-hydroxysteroid dehydrogenase/carbonyl reductase (3α-HSD/CR) from C. testosteroni was a member of the short-chain dehydrogenase/reductases (SDRs) superfamily, which was a class of enzymes that metabolize a range of substrates including steroid, monosaccharides and PAHs, etc (Ji et al., 2014 ). The gene abundance of 3α-HSD/CR has a certain effect on the degradation of PAHs. In this study, the gene abundance in the CT was significantly higher than that in the CK within 25 days ( p < 0.05) (Fig. 2 e), indicating that inoculation of C. testosteroni increased the degradation efficiency of PAHs. On the day of 25, the abundance of Comamonas was very low in CT (Fig. 2 c), but the gene abundance of 3α-HSD/CR was still higher in CT than that in CK. This result showed that the presence of indigenous microorganisms who contributed greatly to the 3α-HSD/CR gene abundance, and their potential to degrade PAHs was activated by C. testosteroni . NahAc was the common initial dioxygenase gene encoding the large (α) subunit of dioxygenase, which was the critical enzyme in the upper pathway of PAHs degradation (Xu et al., 2019 ). The first step for aerobic bacteria to degrade PAHs was to hydroxylate the aromatic ring through dioxygenase to form cis-dihydrodiol and to reform the diol intermediate by the dehydrogenase. Subsequently, the hydroxylated aromatic ring was cleaved by the ortho- or inter-cleavage pathway through the diol or outer diol ring cleavage dioxygenase. Finally, it was converted into intermediates of the TCA cycle by intermediates such as catechol (Mallick et al., 2011 ). Quantification of NahAc gene abundance could evaluate the ability of PAHs degradation by indigenous microorganisms. The NahAc gene abundance was significantly higher in CT than that in CK ( p < 0.01), indicating that inoculation of C. testosteroni might enhance the synergy of indigenous microorganisms to degrade PAHs (Fig. 2 e). The changing trend of NahAc abundance was consistent with 16SrRNA gene from day 0 to day15. At this period, NahAc abundance might mostly be affected by the number of bacteria. After 15d, its abundance increased, indicating that the inoculation of C. testosteroni gradually changed the microbial community and caused more endogenous microorganisms to participate in the degradation of PAHs. The results of RDA showed that the correlation between bacteria and functional genes in the CK was relatively scattered while concentrated in CT, which might further explain C. testosteroni could increase the potential of indigenous bacteria to degrade PAHs (Fig. S2). 3.5 Predicted potential function of bacterial community PICRUSt was developed to predict the functional characteristics of the microbial community based on 16SrRNA homology and conserved feature of functional contribution (Li et al., 2019b ). All predicted functional genes were mainly associated with six components in KEGG pathways, approximately 51% associated with metabolism, 15% associated with genetic information processing and 12% associated with environmental information processing. Since the highest proportion of predicted functional genes were associated with metabolism, further exploration of the responses of the soil microbial metabolism to PAH exposure is necessary. Functional genes included the metabolism of amino acid, carbohydrate, lipid, nucleotide, energy, and xenobiotics, which were predicted in large quantities. In CT, more complex substances such as lipid and xenobiotics metabolism were improved after inoculation (Fig. 3 a). In other words, C. testosteroni improved the ability of soil microorganisms to degrade complex compounds. The subsystem of xenobiotics biodegradation and metabolism involved 12 components associated with PAHs were predicted. These results were analyzed for further exploration of the responses of soil microbial metabolism to PAHs (Fig. 3 b). We found that the majority of metabolism was stronger in the CT, such as PAH degradation, especially benzoate degradation and aminobenzoate degradation. Moreover, it was interesting that the change was similar to the abundance of C. testosteroni , with the peak at day 6 (Fig. 2 d), indicating that C. testosteroni had an important impact on the metabolism of degrading PAH for bacterial communities. These metabolisms weakened at the day of 25 in CT, while there were opposite in the CK, indicating that the corresponding substances had been effectively degraded. 3.6 Identifying functional microorganisms for PAHs degradation The interaction between different genus bacteria in CK and CT were described in Fig. 4 a and b, respectively. The 23 nodes and 29 nodes were found in CK and CT respectively. In addition, inoculation with C. testosteroni could significantly enhance the correlation between each bacteria genus in CT, and the positive correlation was significantly increased in CT compared with CK ( p < 0.05). C. testosteroni was only negative correlation with RB41 (Fig. 4 b). In order to better understand the effect of microorganisms on PAHs, the network analysis was constructed based on the relationship between PAHs and bacteria at the genus level in CT. The results showed that a total of 13,12, and 16 bacteria genera were significantly negatively correlated with Nap, Phe and BaP, respectively ( p < 0.05) (Fig. 4 c). The negative correlation represented the action of microorganisms on PAHs or the toxicity of PAHs to microorganisms, namely, more related bacteria fewer PAHs, or less related bacteria more PAHs. Microbes multiplication in a contaminated environment were able to use the contaminant as the source of energy because of their genetic adaptability which leads to bioremediation (Gupta et al., 2015 ). The negative correlations showed that the biodegradation of PAHs by bacteria was strong, moreover, the degradation effect of PAHs in the CT was better than that of uninoculated C. testosteroni (Table 2 ). These results showed that in the complex microbial community structure, C. testosteroni was not only degraded PAHs by themselves, but it was mainly strengthening the interaction of endogenous microorganisms to promote the degradation of PAHs. SEM was a priori approach to infer causality between factors in ecosystems (Lu et al., 2018 ; Wu et al., 2020 ; Chen et al., 2020 ). In order to further identify functional microorganisms for PAHs degradation, SEM was employed to analyze the relationship between bacteria and PAHs, these results were shown in Fig. 5 . Flavisolibacter (r = -0.195, p < 0.001) and Steroidobacter (r = -0.818, p < 0.001) affected Nap directly (Fig. 5 a), moreover, Flavisolibacter (r = -0.391, p < 0.05) and Steroidobacter (r = -0.67, p < 0.001) impacted Phe and BaP directly, respectively (Fig. 5 b, c). Previous studies reported that Steroidobacter and Sphingomonas could degrade aromatic hydrocarbons such as PAHs (Yun et al., 2018 ; Lu et al., 2019b ). In this study, Sphingomonas did not have a significant correlation with Nap and Phe, but it was significantly positively correlated with Steroidobacter (r = 0.823, p < 0.01), and Steroidobacter were significantly positively correlated with Flavisolibacter (r = 0.845, p < 0.01). These results illustrated that Sphingomonas might indirectly affect the degradation of Nap and Phe by affecting the correlationship of bacteria. It was worth noting that RB41 and BaP were negatively correlated with each other (Fig. 5 c). RB41 was shown to be important in maintaining the metabolic and biogeochemical functions of soils under low-nutrient or stress conditions (Wang et al., 2019 ). This result indicated that RB41 was affected by the exposure of BaP, however, it could degrade BaP. Comamonas was significantly negative correlation with RB41 (r = -0.718, p < 0.001). With the decrease of PAHs concentration, Comamonas abundance decreased, while RB41 abundance increased, resulting in a negative correlation between them. In this study, the key microbes closely related to Nap, Phe and BaP were Steroidobacter , Flavisolibacter , Sphingomonas , Comamonas and RB41 . With the inoculation of C. testosteroni , the interaction between Steroidobacter and other indigenous bacteria was strengthened in CT. Steroidobacter had relatively low abundance (< 1%), indicating the role of C. testosteroni might be to trigger other bacteria genus to resistance PAHs. Inoculation was an effective method to degrade PAHs (Yuan et al., 2020 ). Because of the influence of complex environmental factors, it was difficult to confirm inoculants degrade pollutants or strengthen other microorganisms to degrade pollutants. In this study, we selected C. testosteroni as an inoculant which was originally existed in the soil and inoculated in PAHs contaminated soil. Previous studies were reported that C. testosteroni could effectively degrade PAHs (Zalesak et al., 2017 ). We found the relative abundance of C. testosteroni was high in CT. Moreover, the concentration of Nap, Phe and BaP were decreased continuously, which was proved that the inoculants could adapt to the soil conditions and better perform their functions to degrade PAHs. However, according to the results of network analysis and SEM, C. testosteroni could degrade PAHs, moreover, it also enhanced the synergistic effect of indigenous microorganisms or changed the soil microhabitat to degrade PAHs. Based on the above results, screening of functional microorganisms not only pays attention to their functions but also needs to focus on the groups of microorganisms with interactive effects. 4. Conclusion In this study, the optimum inoculated conditions of C. testosteroni in soil were revealed by orthogonal test. Inoculation of C. testosteroni increased the degradation of PAHs because of inoculant increased degrading gene abundance and stimulated metabolic activities of PAHs degrading microorganisms. C. testosteroni inoculated in soil could change the bacteria community structure and enhance bacteria interaction to increase the PAHs degradation. This study would be helpful to understand the function of inoculated strains in PAHs contaminated soil and identify functional microorganisms of PAHs remediation. Declarations Acknowledgments This study wishes to thank College of Geographical Science for providing the equipment of ASE. Authors’ contribution All authors participated in conceiving the study. Xin Li conducted experiments with assistance from Ziwei Jiang. Xueting Sun conducted all statistical analyses, with comments and suggestions from Xin Li and Qiao Wang. Yue Cui and Qiao Wang conducted partial experimental indexes determination. Xueting Sun wrote the manuscript with signifcant assistance and comments from Qian Lu and Jizhe Cui. Funding This research was financially supported by Special Fund Project for Harbin Science and Technology Innovation Talents (2016RAXXJ083), Innovative Talent Training Plan of Heilongjiang Provincial Education Department (UNPYSCT-2020128), Doctoral Initiation Fund of Harbin Normal University (XKB201913), and Innovative Research Project for Postgraduate of Harbin Normal University (HSDSSCX2019-25). Declaration Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare no competing interests References Ahmad, M., Yang, Q., Zhang, Y., Ling, J., Dong, J., 2019. 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Treatability studies of naphthalene in soil, water and air with persulfate activated by iron(II). J. Environ. Sci. 90, 67-77. Minkina, T., Sushkova, S., Yadav, B. K., Rajput, V., Mandzhieva, S., Nazarenko, O., 2019. Accumulation and transformation of benzo [α] pyrene in Haplic Chernozem under artificial contamination. Environ. Geochem. Health. 42(8), 2485-2494. Mu, L., Zhang L., Ma J., Zhu K. Y., Chen, C. S., Li, A. M., 2020. Enhancement of anaerobic digestion of phoenix tree leaf by mild alkali pretreatment: Optimization by Taguchi orthogonal design and semi-continuous operation. Bioresour Technol. 313, 123634. Patel, A. B., Mahala, K., Jain, K., Madamwar, D., 2018. Development of mixed bacterial cultures DAK11 capable for degrading mixture of polycyclic aromatic hydrocarbons (PAHs). Bioresour Technol, 253, 288-296. Sengupta, A., Dick, W. A., 2015. Bacterial community diversity in soil under two tillage practices as determined by pyrosequencing. Microb. Ecol. 70(3), 853-859. Smułeka, W., Sydowb, M., Zabielska-Matejukb, J., Kaczorek, E., 2020. Bacteria involved in biodegradation of creosote PAH-A case study of longterm contaminated industrial area. Ecotox. Environ. Safe. 187,109843-109852. Sun, J., Pan, L., Tsang, D. C. W., Zhan, Y., Li, X., 2017. Organic contamination and remediation in the agricultural soils of China: a critical review. Sci. Total Environ. 615, 724. Tang, Q., Lu, T., Liu, S. J., 2018. Developing a synthetic biology toolkit for Comamonas testosteroni , an emerging cellular chassis for bioremediation. ACS Synth Biol. 7, 1753-1762. USEPA, 1996. United States Environmental Protect Agencye- USEPA 3550B: Ultrasonic extraction. EPA, Revision 2. Varjani, S. J., 2017. Microbial degradation of petroleum hydrocarbons. Bioresour. Technol. 223, 277-286. Venkateswar, R. M., Mawatari, Y., Yajima, Y. K., Seki, C., Hoshino, T., Chang, Y. C., 2015. Poly-3-hydroxybutyrate (PHB) production from alkylphenols, mono and poly-aromatic hydrocarbons using Bacillus sp. CYR1: A new strategy for wealth from waste. Bioresour Technol. 192, 711-7. Vila, J., Tauler, M., Grifoll, M., 2015. Bacterial PAH degradation in marine and terrestrial habitats. Curr. Opin. Biotechnol. 33, 95-102. Wang, M., Chen, S., Chen, L., Wang, D., 2019. Responses of soil microbial communities and their network interactions to saline-alkaline stress in cd-contaminated soils. Environ. Pollut. 252, 1609-1621. Wu, J. Q., Wei, Z. M., Zhu, Z. C., Zhao, Y., Jia, L. M., Lv, P., 2020. Humus formation driven by ammonia-oxidizing bacteria during mixed materials composting. Bioresour Technol. 311, 123500. Xu, Y. C., Liu, T. T., Zhu, X. F., Ji, G. D., 2019. Quantitative analysis of genetic associations in the biodegradative pathway of PAHs in wetland sediments of the Bohai coast region. Chemosphere. 218, 282-291. Yuan, K, Li, S. Q., Zhong, F., 2020. Characterization of a newly isolated strain Comamonas sp. ZF-3 involved in typical organics degradation in coking wastewater. Bioresour. Technol. 304, 123035. Yun, J., Jung, H., Ryu, H. W., Oh, K. C., Jeon, J. M., Cho, K. S., 2018. Odor mitigation and bacterial community dynamics in on-site biocovers at a sanitary landfill in South Korea. Environ. Res. 166, 516-528. Zalesak, M., Ruzicka, J., Vicha, R., 2017.Cometabolic Degradation degradation of Dichloroethenes dichloroethenes by Comamonas testosteroni RF2. Chemosphere.186: 919-927. Zhang, P., Chen, Y.G., 2017. Polycyclic aromatic hydrocarbons contamination in surface soil of China: a review. Sci Total Environ. 605-606:1011-1020. Zhao Z. Y., Selvam, A., Wong, J. W. C., 2011. Effects of rhamnolipids on cell surface hydrophobicity of PAH degrading bacteria and the biodegradation of phenanthrene. Bioresour. Technol. 102, 3999-4007. Zheng, S.X, Su, J., Wang, L., Yao, R., Wang, D., Deng, Y. J., Wang, R., Wang, G. J., Rensing, C., 2014. Selenite reduction by the obligate aerobic bacterium Comamonas testosteroni S44 isolated from a metalc ontaminated soil. BMC Microbiology. 14(1),204-208. Supplementary Files supplementaryinformations.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-307586","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":18809523,"identity":"db0f01ac-618f-4e2e-955d-277b76ae21bb","order_by":0,"name":"Xueting Sun","email":"","orcid":"","institution":"Harbin Normal University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xueting","middleName":"","lastName":"Sun","suffix":""},{"id":18809524,"identity":"c8b71881-b13a-46c1-8663-6f1941fc5168","order_by":1,"name":"Xin Li","email":"","orcid":"","institution":"Harbin Normal University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Li","suffix":""},{"id":18809525,"identity":"2ec58fee-3e71-4afb-9923-985ffcaabc77","order_by":2,"name":"Yue Cui","email":"","orcid":"","institution":"Harbin Normal University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Cui","suffix":""},{"id":18809526,"identity":"898e2a77-899f-49b8-a032-0d52538ea197","order_by":3,"name":"Ziwei Jiang","email":"","orcid":"","institution":"Harbin Normal University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ziwei","middleName":"","lastName":"Jiang","suffix":""},{"id":18809527,"identity":"cc334614-01a4-4a9e-9e20-89ef65643b58","order_by":4,"name":"Qiao Wang","email":"","orcid":"","institution":"Harbin Normal University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qiao","middleName":"","lastName":"Wang","suffix":""},{"id":18809528,"identity":"0e183915-3212-4ea2-afd3-ae088e235d4a","order_by":5,"name":"Qian Lu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYBACPgbm4z8+GNjIsbG3HyBOCxsDW4LkjII0Yz6eMwnEauExkOb4cDhxnoSDAZFa2NMSjBkM0tLbJBgSGH5UbCNCC8/jA8kFBja5bdKNBxh7ztwmQotEWsLhGQZpuW0yBxKYGduI0pJj2MxjcDidTSLBgGgtxsxALQkkaOF5lsYIdJhhGzCQDxLlF3725GMMH/7YyMu3tx988KOCCC0MwKCFgwPEqEfVMgpGwSgYBaMAKwAAmFs5KZjnWnUAAAAASUVORK5CYII=","orcid":"","institution":"Harbin Normal University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Lu","suffix":""},{"id":18809529,"identity":"b54efe4a-65ee-426b-8019-04d3f9ade37b","order_by":6,"name":"Jizhe Cui","email":"","orcid":"","institution":"Harbin Normal University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jizhe","middleName":"","lastName":"Cui","suffix":""}],"badges":[],"createdAt":"2021-03-07 16:41:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-307586/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-307586/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":7457317,"identity":"cad280d9-d681-4c57-ae03-6f505f89c89b","added_by":"auto","created_at":"2021-03-29 19:02:23","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":37254,"visible":true,"origin":"","legend":"Changes of PAHs concentration (a) and PAHs degradation rate (b) in soil from 0 to 25d. All values represent means ± SD (n = 3).","description":"","filename":"f1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-307586/v1/c1ab423ac7ab20c92aea052f.jpg"},{"id":7457318,"identity":"20462063-615f-486f-bd39-21b2099ae221","added_by":"auto","created_at":"2021-03-29 19:02:23","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":76902,"visible":true,"origin":"","legend":"Shannon-Wiener index and Ace index of bacteria for soil samples (a); NMDS ordination of bacterial community from CK and CT (b); Relative abundance of bacteria genera during incubation experiment (c); Relative quantity of functional genes: 16S rRNA (d), 3α- HSD/CR (e) and NahAc (f).","description":"","filename":"f2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-307586/v1/adf01c9ecff54ff4676069d4.jpg"},{"id":7457319,"identity":"9b4bbf14-23d1-4ffa-82a5-fdafb6f9ac45","added_by":"auto","created_at":"2021-03-29 19:02:23","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":63361,"visible":true,"origin":"","legend":"PICRUSt analysis based on KEGG database in CK and CT. Level 2 function categories (a); Level 2 function categories (b).","description":"","filename":"f3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-307586/v1/1b96bd54fa31bbaf413b6646.jpg"},{"id":7457123,"identity":"41d8af65-4cc7-4853-a49b-2799adadf989","added_by":"auto","created_at":"2021-03-29 18:59:23","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":79929,"visible":true,"origin":"","legend":"The network analysis of the relationship between bacteria genera in CK (a), CT (b). The network analysis of PAHs and related bacteria in CT (c). Orange nodes represent the related bacteria, and the size represents the abundance. Red triangles represent different types of PAHs. Lines represent the significant correlation (p \u003c 0.05). Red lines represent positive correlation. Green lines represent negative correlation. Gray line represents the significant correlation between bacteria genera.","description":"","filename":"f4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-307586/v1/10b63c858a49865a4a057b52.jpg"},{"id":7457120,"identity":"a41acda3-6672-4c10-8319-e5201c6e3852","added_by":"auto","created_at":"2021-03-29 18:59:23","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":38115,"visible":true,"origin":"","legend":"SEMs showed the causeal of relationship between related bacteria genera and Nap (a), Phe (b) and BaP (c) in CT. Arrows depict casual relationships: red lines indicate positive effects, green lines indicate negative effects and gray lines indicate paths with coefficients non-significant different. Arrow widths were proportional to R values. Numbers adjacent to arrows are standardized path coefficients. *p \u003c 0.05, **p \u003c 0.01, ***p \u003c 0.001.","description":"","filename":"f5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-307586/v1/0d7f776a32b78410c21f7a29.jpg"},{"id":13682622,"identity":"2918ccc0-1915-4908-b317-025c86a25b3d","added_by":"auto","created_at":"2021-09-17 11:58:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":668850,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-307586/v1/444da8ee-6484-4628-8b5e-f0b7005208b1.pdf"},{"id":7457320,"identity":"73f96b42-945f-4cc1-b43b-0b6462aec118","added_by":"auto","created_at":"2021-03-29 19:02:23","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":308426,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryinformations.docx","url":"https://assets-eu.researchsquare.com/files/rs-307586/v1/9b6288c1bfbacc7a273425b1.docx"}],"financialInterests":"","formattedTitle":"Interaction with Endogenous Microorganisms, Comamonas testosteroni Enhanced the Degradation of Polycyclic Aromatic Hydrocarbon in Soil","fulltext":[{"header":"1. Introduction","content":" \u003cp\u003ePolycyclic aromatic hydrocarbons (PAHs) are a class of fused-polycyclic aromatic ring compounds that are mainly discharged from the incomplete combustion of fossil fuels or other organic materials (Humel et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). PAHs are of great concern because of their lipophilic, mutagenic, and carcinogenic properties. The low aqueous solubility and the high solid-water distribution ratios promote PAH accumulation in the solid phases of the terrestrial environment (Lu et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e). With the development of industry, the concentration of PAH in the soil is typically detected at a relatively high-level in recent years (Sun et al., 2018). Long-term PAH pollution disturbs the soil ecological environment, causing severe potential risks to soil organisms and humans (Li et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e). Previous studies have found that naphthalene (Nap), phenanthrene (Phe) and pyrene (Pyr), etc. were predominant PAHs in 16 precedence-controlled PAHs on the United States Environmental Protection Agency (USEPA) priority pollutant list (Patel et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Zhang and Chen, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Nap is the lowest molar mass of the PAHs and it can be adsorbed onto the soil due to its adsorption capacity and high-water solubility (Mendes et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Benzo [α] pyrene (BaP) is considered a priority control pollutant because of its carcinogenic, teratogenic and mutagenic effects (Bhattacharya et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Therefore, it is necessary to find suitable remedial technology to alleviate the possible environmental risk posed by PAHs in soils.\u003c/p\u003e \u003cp\u003eIn recent years, several physical, chemical, and biological technologies have been established and applied to remediation of PAH-contaminated soil (Varjani et al., 2017). Compared to the high cost and potential secondary contamination incurred by physical and chemical methods, bioremediation, especially microbial remediation, is considered a cost-effective remediation technology (Vila et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Many microorganisms including bacteria and fungi have been isolated from PAH-contaminated sites with the ability to degrade PAHs efficiently. PAH-degrading bacteria can metabolize PAHs as a source of carbon and energy in soils (Aranda et al., 2016), and they play an important role in the degradation of PAHs. Some bacteria such as \u003cem\u003ePseudomonas\u003c/em\u003e, \u003cem\u003eSphingomonas\u003c/em\u003e, \u003cem\u003eBacillus\u003c/em\u003e, \u003cem\u003eSphingobacterium\u003c/em\u003e and \u003cem\u003eMycobacterium\u003c/em\u003e have been widely recognized and used to degrade PAHs (Venkateswar et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Mallick, et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). A previous study showed that a mixed inoculation of \u003cem\u003eBacillus subtilis\u003c/em\u003e and \u003cem\u003eP. aeruginosa\u003c/em\u003e removed 82.2% of Phe within 30 days under laboratory conditions (Zhao et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The isolated strain \u003cem\u003eComamonas sp. ZF-3\u003c/em\u003e had efficient biodegradability of phenolic compounds and heterocyclic compounds in coking wastewater (Yuan et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). It can be seen that bacteria have the ability to degrade PAHs with complex structures very efficiently. However, the biodegradation of PAHs solely utilizing native bacteria under natural conditions is a very slow process. The efficiency of bacteria to degrade PAHs are related to many factors, mainly including the concentration of effective bacteria, environmental factors, and the degree of soil PAHs pollution. Therefore, finding the optimistic degradation conditions is the key to improve the degradation efficiency.\u003c/p\u003e \u003cp\u003e \u003cem\u003eComamonas testosteroni\u003c/em\u003e (\u003cem\u003eC. testosteroni\u003c/em\u003e) is a gram-negative bacterium belonging to the class of β-proteobacteria, which is widely found in soil, activated sludge and seabed sediments. \u003cem\u003eC. testosteroni\u003c/em\u003e can degrade many sterols and PAHs, and even use these complex organic compounds as the sole carbon source (Zalesak et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Moreover, \u003cem\u003eC. testosteroni\u003c/em\u003e can degrade heavy metal pollutants in the environment (Zheng et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). It has a strong adaption to change environments and xenobiotics. With these attractive features, researchers have begun to explore \u003cem\u003eC. testosteroni\u003c/em\u003e strains as environmental bioremediation hosts (Tang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, due to the complexity of the natural ecosystem, finding the optimal inoculation conditions for inoculants is crucial to maximizing the degradation of pollutants. In this study, we inoculated \u003cem\u003eC. testosteroni\u003c/em\u003e into PAHs (Nap, Phe, BaP) contaminated soil under an optimal system. The principal goals of this study were: (1) to determine the optimal degradation system through the orthogonal analysis to maximize the degradation of PAHs inoculated with \u003cem\u003eC. testosteroni\u003c/em\u003e, (2) to analyze the effect of inoculation of \u003cem\u003eC. testosteroni\u003c/em\u003e on the degradation of PAHs in the soil under the system, (3) to assess the relationship among inoculants, indigenous microbes and the degradation of PAHs. This research will provide useful perspectives and methods for solving PAHs soil pollution by inoculating \u003cem\u003eC. testosteroni\u003c/em\u003e.\u003c/p\u003e "},{"header":"2. Material And Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e2.1 Preparation of inoculant\u003c/b\u003e\u003c/h2\u003e \u003cp\u003e \u003cem\u003eC.testosterone\u003c/em\u003e strain (NR029161.2) were selected as inoculum. The inoculum was prepared by growing in lysogeny broth (LB) agar plates at 28\u0026deg;C for 14 h. The independent colony was inoculated into LB liquid medium and incubated at 28\u0026deg;C for 14 h on a rotary shaker (180 rpm). Exponential growth-phase cells were then harvested by centrifugation at 4\u0026deg;C for 15 min (4500 rpm), discarded the supernatant and resuspended individually in sterile water.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e2.2 Experimental design and sample collection\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eSoils were collected from topsoil at a depth of 0\u0026ndash;20 cm from Harbin Normal University, China. They were air-dried at room temperature (around 25℃) and then passed to a 2 mm sieve. Contaminated soil was prepared by adding Nap, Phe and BaP (\u0026gt;\u0026thinsp;98% purity; Sigma-Aldrich, Shanghai, China) stock solution (in acetone) to sieved soil with different concentrations (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe combination of parameters based on orthogonal table with 3 factors and 3 levels.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA Concentration of total PAHs (\u0026micro;g/kg)\u003c/p\u003e \u003cp\u003e(Nap/Phe/BaP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB Concentration of bacteria (DW, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC Temperature\u003c/p\u003e \u003cp\u003e(℃)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4800 (2400/800/1600)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2400 (1200/400/800)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1200 (600/200/400)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe orthogonal design was used to find the optimal PAHs degradation system. They were designed with 3 factors and 3 levels of the orthogonal table as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. PAHs concentration (Factor A), bacteria concentration (Factor B) and temperature (Factor C) were chosen as three factors. The levels of total PAHs concentrations were 4800 \u0026micro;g/kg, 2400 \u0026micro;g/kg and 1200 \u0026micro;g/kg, respectively. The levels of \u003cem\u003eC.testosterone\u003c/em\u003e concentrations were 0, 0.01% and 0.05%. The levels of temperature were 30 ℃, 20 ℃ and 10 ℃. Samples of the soils, each weighing 200 g (dry weight, DW) was placed in a glass container with 500 g capacity and covered with aluminum foil.\u003c/p\u003e \u003cp\u003eAccording to the results of the orthogonal experiment, the optimal conditions were selected to study the changes in the degradation process of soil PAHs. Two groups of the experiment were carried out, including soil with Nap, Phe and BaP (CK), and inoculated of \u003cem\u003eC.testosteroni\u003c/em\u003e in soil with Nap, Phe, BaP (CT). The experiment continued for 25 days and each experimental treatment was repeated three times. The samples were collected on days 0, 2, 4, 6, 10, 15, 20 and 25. Each sample was divided into two parts, one part was sealed with tinfoil bags, and quick-frozen with liquid nitrogen, then stored at -80℃ for microbial community and molecular biological analysis, the other part was stored at 4℃ for PAHs analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Soil PAH analysis\u003c/h2\u003e \u003cp\u003eSample extraction and purification were performed following the USEPA Method 3550B (USEPA \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) with some modifications. Briefly, an amount of 10 g of each soil sample with diatomite mixtures was extracted with the ASE 150 (Dionex Corp, USA) through n-hexane/dichloromethane (1:1, v/v) solvent mixtures. The extraction was evaporated by a rotary vacuum evaporator, concentrated to about 1 mL, and then loaded on a silica gel column for purification, and the residual solvent was removed by nitrogen. The residue was dissolved in 1 mL of n-hexane. PAHs were analyzed by Agilent 7890A gas chromatography system combined with 5975C mass selective detector (GC/MS), and PAHs were separated by HP-5MS (30m\u0026times;0.32mmi.d.\u0026times;0.25\u0026micro;m film thickness), details could be found in Li et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 qPCR and high throughput sequencing\u003c/h2\u003e \u003cp\u003eSoil microbial DNA was extracted by using the Ezup column soil genomic DNA extraction kit (Sangon Biotech, Shanghai, China). The genes (\u003cem\u003e16SrRNA\u003c/em\u003e, \u003cem\u003e3α-HSD/CR\u003c/em\u003e and \u003cem\u003eNahAc\u003c/em\u003e) abundance were determined by real-time fluorescent quantitative PCR (qPCR). It was performed on each DNA template by using the SYBR Green Master Mix on the ABI 7500 Real-Time PCR system. The primers and amplification conditions were listed in Table S1. The qPCR reaction conditions as follows: pre-denaturation for 30s at 95℃, denaturation for 10s at 95℃, annealing for 30s at 60℃, 40 cycles. The qPCR reaction mixture consisted of 2\u0026micro;L of DNA template, 10\u0026micro;L of 2\u0026times;ChamQ Universal SYBR qPCR Master mix, 0.4\u0026micro;L of 50\u0026times;Rox Reference Dye 2, 0.4\u0026micro;L each forward and reverse primer, to a final volume of 20\u0026micro;L with ddH\u003csub\u003e2\u003c/sub\u003eO.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003e16SrRNA\u003c/em\u003e gene comprising V3 and V4 hypervariable regions was amplified by PCR using the forward primer 341F (5'- CCTACGGRRBGCASCAGKVRVGAAT-3') and reverse primer 806R (5'-GGACTACNVGGGTWTCTAATCC-3'). High-throughput sequencing of PCR product was performed on an Illumina MiSeq platform (Illumina, San Diego, CA, USA) at GENEWIZ, Inc. (China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Data analysis\u003c/h2\u003e \u003cp\u003eSPSS 25.0 and Origin 2018 were used for statistical analysis of the orthogonal experiment and PAHs content. The changes in the microorganism community and the relationships between microbes and functional gene were analyzed by using the nonmetric multidimensional scaling ordination (NMDS) and redundancy analyses (RDA), both of them were conducted by Canoco5.0 software. The relationship between PAHs and microorganisms was analyzed by network analysis (Cytoscape 3.6.1). The structural equation model (SEM) was performed by the SPSS package of Amos 20.0. Functional capacity of the bacteria was predicted based on the bacteria composition using the phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt), functional genes were predicted based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.kegg.jp/\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e "},{"header":"3. Results And Discussion","content":" \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Orthogonal analysis\u003c/h2\u003e \u003cp\u003eInoculation was a favorable way to biodegrade PAHs. However, many factors affect the degradation of PAHs by microorganisms, temperature, indigenous microbial community structure, and inoculum concentration. The orthogonal experiment is a versatile optimization and economical experimental design method for arranging experiments with multiple factors and multiple levels (Mu et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). To evaluate the effectiveness of environmental factors on PAHs degradation by \u003cem\u003eC. testosteroni\u003c/em\u003e, the orthogonal test was adopted to three factors and three levels (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), and the results were presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. A1B2C2 was the optimal condition of PAHs degradation in this study. The degradation rate of total PAHs reached up to 58.09% on day 25 when the concentration of PAHs (Nap/Phe/BaP) was 4800 (2400/800/1600) \u0026micro;g/kg, the concentration of bacteria was 0.01% and the temperature was 20℃. In contrast, under the conditions of 10℃ with lower PAHs concentration, PAHs was only decreased 9.39% (A3B1C3). The above results indicate that suitable temperature or suitable inoculation concentration of \u003cem\u003eC. testosteroni\u003c/em\u003e was beneficial to the degradation of PAHs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe contribution of orthogonal experimental factors to the degradation rate of PAHs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExperimental numbers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eResult\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal PAHs degradation rate(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA1B1C1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA1B2C2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA1B3C3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA2B1C2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA2B2C3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA2B3C1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA3B1C3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA3B2C1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA3B3C2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({K}_{1}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({K}_{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e146.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e105.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({K}_{3}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\stackrel{-}{{K}_{1}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\stackrel{-}{{K}_{2}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\stackrel{-}{{K}_{3}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOptimal Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}_{j}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{K}}_{i}\\)\u003c/span\u003e\u003c/span\u003e represents the value of the i-th level, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\stackrel{-}{{K}_{i}}\\)\u003c/span\u003e\u003c/span\u003e represents the mean of the i-th level, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{R}}_{j}\\)\u003c/span\u003e\u003c/span\u003e represents the range of the factor \u003cem\u003ej\u003c/em\u003e.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn order to analyze the influence of various factors on the degradation efficiency of PAHs, the range analysis was performed on the orthogonal experiment results. Base on the results of range analysis, the order among the factors was arranged according to the magnitude of the range (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The greater the range, the greater the influence of factor \u003cem\u003ej\u003c/em\u003e on the test index. For the PAHs degradation efficiency, the order of significant influence of various factors was as follows: bacteria concentration\u0026thinsp;\u0026gt;\u0026thinsp;PAHs concentration\u0026thinsp;\u0026gt;\u0026thinsp;temperature. These results revealed that the inoculation level of \u003cem\u003eC. testosteroni\u003c/em\u003e had significant influences on the degradation of PAHs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Concentrations and degradation of PAHs\u003c/h2\u003e \u003cp\u003eBased on the optimal system in the orthogonal experiment (A1B2C2), the dynamic characteristics of Nap, Phe and BaP degradation in the soil were further analyzed. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e showed the concentration changes of Nap, Phe and Bap at different times after inoculation during 25 days in CT. The concentration of these PAHs was showed a downward trend and the degradation trends of Phe and BaP were similar (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Initially, Nap, Phe and BaP were 2315\u0026micro;g/kg, 770\u0026micro;g/kg and 1529\u0026micro;g/kg, respectively. At day 25, these PAHs decreased to a minimum value, and there were significantly lower than the initial ones (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eThe degradation rates of Nap, Phe and BaP were analyzed in CT. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003eb showed the average PAHs degradation in the order of Phe (81.2%)\u0026thinsp;\u0026gt;\u0026thinsp;Nap (63.4%)\u0026thinsp;\u0026gt;\u0026thinsp;BaP (38.0%) at day 25. The degradation rate of Nap was rapidly increased to 54.01% on the 10th day and then increased slowly by only 9.4% on the 25th day compared with that on the 10th day. At the end of the experiment, the accumulation of Nap degradation was 1467\u0026micro;g/kg. Phe and BaP were effectively degraded and the degradation rate was 43.8% and 21.0% during 10 days, respectively. Phe had a high degradation rate in the following 15 days (37.8%), however, the degradation rate of BaP was lower than that of Phe. BaP was composed of 5-ring polyarenes, which belongs to high molecular weight PAHs (HMW-PAHs, \u0026ge;\u0026thinsp;5 rings). The solubility of PAHs was one of the limiting factors for PAHs degradation. The increases in the molecular weight of PAHs lead to a decrease in their biodegradability (Ghosal et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In the first 10 days, the degradation rate was Nap\u0026thinsp;\u0026gt;\u0026thinsp;Phe\u0026thinsp;\u0026gt;\u0026thinsp;Bap, and Nap was significantly higher than other PAHs in CT (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, in the following 15 days, Nap had the lowest degradation rate (9.4%) compared with other PAHs. Previous research has shown that HMW-PAHs were converted into low molecular weight PAHs (LMW-PAHs, \u0026lt; 4 rings) and then degraded (Minkina et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). We speculated that BaP and Phe might be converted into Nap for further degradation, which should be the main reason for the low Nap degradation rate detected from 10-25days. The degradation rate of Phe was the highest (81.2%) within 25 days, indicating that inoculation of \u003cem\u003eC. testosteroni\u003c/em\u003e effectively promoted the Phe degradation. In other words, under the condition of A1B2C2, inoculation of \u003cem\u003eC. testosteroni\u003c/em\u003e could rapidly reduce Nap in a short time, and effectively decline the concentration of Phe and BaP. The degradation of PAHs might be due to the inoculation of \u003cem\u003eC. testosteroni\u003c/em\u003e or it was promoting the synergism of indigenous microorganisms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Microbial performance under PAHs expose in soil\u003c/h2\u003e \u003cp\u003eThe microbial richness could be reflected by the Ace index (Sengupta et al., 2015). The microbial richness of CK and CT under PAHs expose was decreased, however, it was generally higher in CT than that in CK except on the 6th day (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). The main reason might be related to the relative abundance of \u003cem\u003eC. testosteroni\u003c/em\u003e, which was significantly increased on day 6 (\u0026gt;\u0026thinsp;60%) and then species richness was reduced. The diversity of microorganisms was investigated according to the Shannon index (Lu et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In this study, the diversity of the CT was different compared with CK (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Inoculation of \u003cem\u003eC. testosteroni\u003c/em\u003e could decrease the bacterial diversity during 0\u0026ndash;6 days and then increased in the later period (10\u0026ndash;25 days). Inoculation of \u003cem\u003eC. testosteroni\u003c/em\u003e could change the bacterial diversity and richness. NMDS was used to identify differences in the bacterial community for each group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003eb), which further showed that the bacterial community was different between the inoculated group (CT) and non-inoculated group (CK). Under PAHs exposure, bacterial community composition changed rapidly during 25 days. Moreover, the microbial community structure of the CK from 0\u0026ndash;6 d was relatively similar, however, it was opposite in CT, which might be caused by the inoculation of \u003cem\u003eC. testosteroni\u003c/em\u003e. The bacterial community structure was changed continuously in CK, suggesting that the PAHs might be harmful to bacterial metabolism and survival and then bacterial community succession. Notably, samples from CK and CT were grouped in diverse polygonal regions and no intersection of the bacterial communities between the two groups, suggesting that \u003cem\u003eC. testosteroni\u003c/em\u003e inoculant affected bacterial communities due to its synergistic effect on indigenous bacteria in the soil.\u003c/p\u003e \u003cp\u003eHigh-throughput sequencing results showed that the soil bacterial community mainly originated from 25 phyla. The bacterial community composition of the two groups was similar at the phylum level. The dominant phylum consisted of Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Gemmatimonadetes, and the relative abundances accounted for 21.8\u0026ndash;53.5%, 13.94\u0026ndash;37.25%, 8.27\u0026ndash;35.05%, 5.36\u0026ndash;19.51%, 3.71\u0026ndash;6.89%, 2.73\u0026ndash;6.38%, respectively (Fig. S1). Proteobacteria and Acidobacteria have the highest abundance, accounting for about 60% on average and this phenomenon was similar to the result of Delgado et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The abundance of Proteobacteria was higher in CT than that in CK, which might be caused by the inoculants of \u003cem\u003eC. testosteroni\u003c/em\u003e which belongs to Proteobacteria. The classified dominant genera in the top 30 abundance of the bacterial community composition in soils were plotted as a relative abundance map of the genera level (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). The dominant bacterial genus mainly includes \u003cem\u003eComamonas\u003c/em\u003e, \u003cem\u003eSphinomonas\u003c/em\u003e, \u003cem\u003eRB41\u003c/em\u003e, \u003cem\u003ePseudarthrobacter\u003c/em\u003e, \u003cem\u003eFlavobacterium\u003c/em\u003e, \u003cem\u003eLysobacter\u003c/em\u003e, with relative abundances ranging from 0 to 37.73%, 1.88 to 15.2%, 3.25 to 7.53%, 0.47 to 18.53%, 0.03 to 11.71%, 0.18 to 4.94%, respectively.\u003c/p\u003e \u003cp\u003eIn the CT, \u003cem\u003eComamonas\u003c/em\u003e was the main genus, showing a fluctuating change, peaking at day 6 and disappearing at day 25. The abundance of \u003cem\u003eSphingomonas\u003c/em\u003e and RB41 showed a gradual upward trend and became the main genus at day 25 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). \u003cem\u003eComamonas\u003c/em\u003e and \u003cem\u003eSphingomonas\u003c/em\u003e could effectively degrade PAHs (Smułek et al., 2020). Moreover, the concentration of Nap, Phe and BaP were decreased and reached the minimum at day 25 in this study. It was proved that the inoculants could better adapt to the soil conditions and perform their functions or cooperate with the indigenous microorganism to degrade PAHs. The abundance of \u003cem\u003eFlavobacterium\u003c/em\u003e was higher at 0-4d and then suddenly decreased from day 6 to day 25 in CT, while it was extremely low in CK (0.03\u0026ndash;0.18%). Previous research showed \u003cem\u003eFlavobacterium\u003c/em\u003e had the potential to degrade PAHs (Ahmad et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The microbial community structure of the CK was a small change in the early stage, but the inoculation had a significant effect on the microbial community. We speculated that the degradation of the PAHs in the CT was closely related to the dynamic changes of microorganisms, and \u003cem\u003eC. testosteroni\u003c/em\u003e might further degrade PAHs by affecting indigenous bacteria. It is worth noting that the abundance of \u003cem\u003ePseudarthrobacter\u003c/em\u003e was high at 25d in the CK. The study of Li et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e) reported that \u003cem\u003ePseudarthrobacter\u003c/em\u003e was affected by PAHs exposure, which could be used as an important indicator of soil PAH pollution, indicating that PAHs pollution at day 25 was worse in CK compared with CT.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Quantitative analysis of gene abundance\u003c/h2\u003e \u003cp\u003e \u003cem\u003e16SrRNA\u003c/em\u003e gene was present in all bacterial genomes, and it was generally used as a marker gene for bacterial classification. In this study, the \u003cem\u003e16SrRNA\u003c/em\u003e gene copy number was measured to determine the changes in bacterial quantity in the soil. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003ed, the average abundance of \u003cem\u003e16SrRNA\u003c/em\u003e gene in CT was generally higher than that in CK during 0-25d except for the 15d and ranged from 242.3 to 620.5 log copies/gDNA, indicating that \u003cem\u003eC. testosteroni\u003c/em\u003e could increase the abundance of bacteria. Moreover, the abundance of the \u003cem\u003e16SrRNA\u003c/em\u003e gene were obvious fluctuations in CT might due to the impact of PAHs or the competition among microorganisms.\u003c/p\u003e \u003cp\u003e3α-hydroxysteroid dehydrogenase/carbonyl reductase (3α-HSD/CR) from \u003cem\u003eC. testosteroni\u003c/em\u003e was a member of the short-chain dehydrogenase/reductases (SDRs) superfamily, which was a class of enzymes that metabolize a range of substrates including steroid, monosaccharides and PAHs, etc (Ji et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The gene abundance of \u003cem\u003e3α-HSD/CR\u003c/em\u003e has a certain effect on the degradation of PAHs. In this study, the gene abundance in the CT was significantly higher than that in the CK within 25 days (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003ee), indicating that inoculation of \u003cem\u003eC. testosteroni\u003c/em\u003e increased the degradation efficiency of PAHs. On the day of 25, the abundance of \u003cem\u003eComamonas\u003c/em\u003e was very low in CT (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003ec), but the gene abundance of \u003cem\u003e3α-HSD/CR\u003c/em\u003e was still higher in CT than that in CK. This result showed that the presence of indigenous microorganisms who contributed greatly to the \u003cem\u003e3α-HSD/CR\u003c/em\u003e gene abundance, and their potential to degrade PAHs was activated by \u003cem\u003eC. testosteroni\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003eNahAc\u003c/em\u003e was the common initial dioxygenase gene encoding the large (α) subunit of dioxygenase, which was the critical enzyme in the upper pathway of PAHs degradation (Xu et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The first step for aerobic bacteria to degrade PAHs was to hydroxylate the aromatic ring through dioxygenase to form cis-dihydrodiol and to reform the diol intermediate by the dehydrogenase. Subsequently, the hydroxylated aromatic ring was cleaved by the ortho- or inter-cleavage pathway through the diol or outer diol ring cleavage dioxygenase. Finally, it was converted into intermediates of the TCA cycle by intermediates such as catechol (Mallick et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Quantification of \u003cem\u003eNahAc\u003c/em\u003e gene abundance could evaluate the ability of PAHs degradation by indigenous microorganisms. The \u003cem\u003eNahAc\u003c/em\u003e gene abundance was significantly higher in CT than that in CK (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating that inoculation of \u003cem\u003eC. testosteroni\u003c/em\u003e might enhance the synergy of indigenous microorganisms to degrade PAHs (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). The changing trend of \u003cem\u003eNahAc\u003c/em\u003e abundance was consistent with \u003cem\u003e16SrRNA\u003c/em\u003e gene from day 0 to day15. At this period, \u003cem\u003eNahAc\u003c/em\u003e abundance might mostly be affected by the number of bacteria. After 15d, its abundance increased, indicating that the inoculation of \u003cem\u003eC. testosteroni\u003c/em\u003e gradually changed the microbial community and caused more endogenous microorganisms to participate in the degradation of PAHs. The results of RDA showed that the correlation between bacteria and functional genes in the CK was relatively scattered while concentrated in CT, which might further explain \u003cem\u003eC. testosteroni\u003c/em\u003e could increase the potential of indigenous bacteria to degrade PAHs (Fig. S2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Predicted potential function of bacterial community\u003c/h2\u003e \u003cp\u003ePICRUSt was developed to predict the functional characteristics of the microbial community based on \u003cem\u003e16SrRNA\u003c/em\u003e homology and conserved feature of functional contribution (Li et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e). All predicted functional genes were mainly associated with six components in KEGG pathways, approximately 51% associated with metabolism, 15% associated with genetic information processing and 12% associated with environmental information processing. Since the highest proportion of predicted functional genes were associated with metabolism, further exploration of the responses of the soil microbial metabolism to PAH exposure is necessary.\u003c/p\u003e \u003cp\u003eFunctional genes included the metabolism of amino acid, carbohydrate, lipid, nucleotide, energy, and xenobiotics, which were predicted in large quantities. In CT, more complex substances such as lipid and xenobiotics metabolism were improved after inoculation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). In other words, \u003cem\u003eC. testosteroni\u003c/em\u003e improved the ability of soil microorganisms to degrade complex compounds. The subsystem of xenobiotics biodegradation and metabolism involved 12 components associated with PAHs were predicted. These results were analyzed for further exploration of the responses of soil microbial metabolism to PAHs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). We found that the majority of metabolism was stronger in the CT, such as PAH degradation, especially benzoate degradation and aminobenzoate degradation. Moreover, it was interesting that the change was similar to the abundance of \u003cem\u003eC. testosteroni\u003c/em\u003e, with the peak at day 6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003ed), indicating that \u003cem\u003eC. testosteroni\u003c/em\u003e had an important impact on the metabolism of degrading PAH for bacterial communities. These metabolisms weakened at the day of 25 in CT, while there were opposite in the CK, indicating that the corresponding substances had been effectively degraded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Identifying functional microorganisms for PAHs degradation\u003c/h2\u003e \u003cp\u003eThe interaction between different genus bacteria in CK and CT were described in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ea and b, respectively. The 23 nodes and 29 nodes were found in CK and CT respectively. In addition, inoculation with \u003cem\u003eC. testosteroni\u003c/em\u003e could significantly enhance the correlation between each bacteria genus in CT, and the positive correlation was significantly increased in CT compared with CK (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u003cem\u003eC. testosteroni\u003c/em\u003e was only negative correlation with RB41 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). In order to better understand the effect of microorganisms on PAHs, the network analysis was constructed based on the relationship between PAHs and bacteria at the genus level in CT. The results showed that a total of 13,12, and 16 bacteria genera were significantly negatively correlated with Nap, Phe and BaP, respectively (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). The negative correlation represented the action of microorganisms on PAHs or the toxicity of PAHs to microorganisms, namely, more related bacteria fewer PAHs, or less related bacteria more PAHs. Microbes multiplication in a contaminated environment were able to use the contaminant as the source of energy because of their genetic adaptability which leads to bioremediation (Gupta et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The negative correlations showed that the biodegradation of PAHs by bacteria was strong, moreover, the degradation effect of PAHs in the CT was better than that of uninoculated \u003cem\u003eC. testosteroni\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These results showed that in the complex microbial community structure, \u003cem\u003eC. testosteroni\u003c/em\u003e was not only degraded PAHs by themselves, but it was mainly strengthening the interaction of endogenous microorganisms to promote the degradation of PAHs.\u003c/p\u003e \u003cp\u003eSEM was a priori approach to infer causality between factors in ecosystems (Lu et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In order to further identify functional microorganisms for PAHs degradation, SEM was employed to analyze the relationship between bacteria and PAHs, these results were shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e5\u003c/span\u003e. \u003cem\u003eFlavisolibacter\u003c/em\u003e (r = -0.195, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and \u003cem\u003eSteroidobacter\u003c/em\u003e (r = -0.818, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) affected Nap directly (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e5\u003c/span\u003ea), moreover, \u003cem\u003eFlavisolibacter\u003c/em\u003e (r = -0.391, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and \u003cem\u003eSteroidobacter\u003c/em\u003e (r = -0.67, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) impacted Phe and BaP directly, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e5\u003c/span\u003eb, c). Previous studies reported that \u003cem\u003eSteroidobacter\u003c/em\u003e and \u003cem\u003eSphingomonas\u003c/em\u003e could degrade aromatic hydrocarbons such as PAHs (Yun et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Lu et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e). In this study, \u003cem\u003eSphingomonas\u003c/em\u003e did not have a significant correlation with Nap and Phe, but it was significantly positively correlated with \u003cem\u003eSteroidobacter\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.823, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and \u003cem\u003eSteroidobacter\u003c/em\u003e were significantly positively correlated with \u003cem\u003eFlavisolibacter\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.845, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). These results illustrated that \u003cem\u003eSphingomonas\u003c/em\u003e might indirectly affect the degradation of Nap and Phe by affecting the correlationship of bacteria. It was worth noting that \u003cem\u003eRB41\u003c/em\u003e and BaP were negatively correlated with each other (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). \u003cem\u003eRB41\u003c/em\u003e was shown to be important in maintaining the metabolic and biogeochemical functions of soils under low-nutrient or stress conditions (Wang et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This result indicated that \u003cem\u003eRB41\u003c/em\u003e was affected by the exposure of BaP, however, it could degrade BaP. \u003cem\u003eComamonas\u003c/em\u003e was significantly negative correlation with \u003cem\u003eRB41\u003c/em\u003e (r = -0.718, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). With the decrease of PAHs concentration, \u003cem\u003eComamonas\u003c/em\u003e abundance decreased, while \u003cem\u003eRB41\u003c/em\u003e abundance increased, resulting in a negative correlation between them. In this study, the key microbes closely related to Nap, Phe and BaP were \u003cem\u003eSteroidobacter\u003c/em\u003e, \u003cem\u003eFlavisolibacter\u003c/em\u003e, \u003cem\u003eSphingomonas\u003c/em\u003e, \u003cem\u003eComamonas\u003c/em\u003e and \u003cem\u003eRB41\u003c/em\u003e. With the inoculation of \u003cem\u003eC. testosteroni\u003c/em\u003e, the interaction between \u003cem\u003eSteroidobacter\u003c/em\u003e and other indigenous bacteria was strengthened in CT. \u003cem\u003eSteroidobacter\u003c/em\u003e had relatively low abundance (\u0026lt;\u0026thinsp;1%), indicating the role of \u003cem\u003eC. testosteroni\u003c/em\u003e might be to trigger other bacteria genus to resistance PAHs.\u003c/p\u003e \u003cp\u003eInoculation was an effective method to degrade PAHs (Yuan et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Because of the influence of complex environmental factors, it was difficult to confirm inoculants degrade pollutants or strengthen other microorganisms to degrade pollutants. In this study, we selected \u003cem\u003eC. testosteroni\u003c/em\u003e as an inoculant which was originally existed in the soil and inoculated in PAHs contaminated soil. Previous studies were reported that \u003cem\u003eC. testosteroni\u003c/em\u003e could effectively degrade PAHs (Zalesak et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). We found the relative abundance of \u003cem\u003eC. testosteroni\u003c/em\u003e was high in CT. Moreover, the concentration of Nap, Phe and BaP were decreased continuously, which was proved that the inoculants could adapt to the soil conditions and better perform their functions to degrade PAHs. However, according to the results of network analysis and SEM, \u003cem\u003eC. testosteroni\u003c/em\u003e could degrade PAHs, moreover, it also enhanced the synergistic effect of indigenous microorganisms or changed the soil microhabitat to degrade PAHs. Based on the above results, screening of functional microorganisms not only pays attention to their functions but also needs to focus on the groups of microorganisms with interactive effects.\u003c/p\u003e \u003c/div\u003e "},{"header":"4. Conclusion","content":" \u003cp\u003eIn this study, the optimum inoculated conditions of \u003cem\u003eC. testosteroni\u003c/em\u003e in soil were revealed by orthogonal test. Inoculation of \u003cem\u003eC. testosteroni\u003c/em\u003e increased the degradation of PAHs because of inoculant increased degrading gene abundance and stimulated metabolic activities of PAHs degrading microorganisms. \u003cem\u003eC. testosteroni\u003c/em\u003e inoculated in soil could change the bacteria community structure and enhance bacteria interaction to increase the PAHs degradation. This study would be helpful to understand the function of inoculated strains in PAHs contaminated soil and identify functional microorganisms of PAHs remediation.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study wishes to thank College of Geographical Science for providing the equipment of ASE.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors participated in conceiving the study. Xin Li conducted experiments with assistance from Ziwei Jiang. Xueting Sun conducted all statistical analyses, with comments and suggestions from Xin Li and Qiao Wang. Yue Cui and Qiao Wang conducted partial experimental indexes determination. Xueting Sun wrote the manuscript with signifcant assistance and comments from Qian Lu and Jizhe Cui.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was financially supported by Special Fund Project for Harbin Science and Technology Innovation Talents (2016RAXXJ083), Innovative Talent Training Plan of Heilongjiang Provincial Education Department (UNPYSCT-2020128), Doctoral Initiation Fund of Harbin Normal University (XKB201913), and Innovative Research Project for Postgraduate of Harbin Normal University (HSDSSCX2019-25).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate \u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication \u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials \u003c/strong\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests \u003c/strong\u003eThe authors declare no competing interests\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003eAhmad, M., Yang, Q., Zhang, Y., Ling, J., Dong, J., 2019. 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BMC Microbiology. 14(1),204-208.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Soil remediation, Polycyclic aromatic hydrocarbons, Comamonas testosteroni, Functional microbial interactions, Network analysis","lastPublishedDoi":"10.21203/rs.3.rs-307586/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-307586/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study was to explore the functional role of \u003cem\u003eComamonas testosteroni\u003c/em\u003e (\u003cem\u003eCt\u003c/em\u003e) on soil indigenous microorganisms, and analyze the effect of \u003cem\u003eCt\u003c/em\u003e on PAHs degradation in PAH-contaminated soil. Results showed that inoculation of \u003cem\u003eCt\u003c/em\u003e could degrade naphthalene (Nap), phenanthrene (Phe), and benzo [α] pyrene (BaP) significantly. The degradation rate of Nap, Phe and BaP was 81.18%, 63.38% and 37.98% on day 25, respectively, suggesting that the low molecular weight of Nap and Phe were easier to be degraded by microorganisms than BaP. Network analysis showed that inoculation of \u003cem\u003eCt\u003c/em\u003e significantly increased the bacteria closely related to PAHs. Structural equation models confirmed \u003cem\u003eSteroidobacter\u003c/em\u003e as functional bacteria could affect the degradation of Nap and BaP. Inoculated \u003cem\u003eCt\u003c/em\u003e could effectively enhance the synergy among indigenous bacteria to degrade PAHs. This would be helpful to understand the function of inoculated strains in PAH-contaminated soil and identify functional microorganisms of PAHs remediation.\u003c/p\u003e","manuscriptTitle":"Interaction with Endogenous Microorganisms, Comamonas testosteroni Enhanced the Degradation of Polycyclic Aromatic Hydrocarbon in Soil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-03-29 18:59:21","doi":"10.21203/rs.3.rs-307586/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"df2dc50f-2ac7-491a-b323-b4612793c783","owner":[],"postedDate":"March 29th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":3284877,"name":"Environmental Engineering"}],"tags":[],"updatedAt":"2021-05-14T07:15:35+00:00","versionOfRecord":[],"versionCreatedAt":"2021-03-29 18:59:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-307586","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-307586","identity":"rs-307586","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}