This study presents the improved biodegradation of crude oil in aqueous phase using mutant Dietzia sp. obtained by random mutagenesis of wild Dietzia sp. using 60Co-γ irradiation. The mutants obtained were screened based on their degradation performance and the best mutant was selected for oil degradation optimization research. A four factor central composite design coupled with response surface methodology was applied to evaluate and optimize the important variables. A genetically stable mutant, designated as M22, was isolated and demonstrated significantly higher degradation efficiency (52.5%) of total petroleum hydrocarbons (TPHs) than the parental strain (28.2%) in liquid media after 14 days of incubation. Increased production of enzyme responsible for the degradation was achieved with the mutant species. Optimum conditions were determined to be pH 7.6, 0.20 g/L K2HPO4, 0.57 g/L NH4NO3, and 0.62 g/L yeast extract. Approximately 68.5% of TPH was experimentally degraded after 14 h of incubation under the optimum conditions, which agreed well with the model prediction. Gas chromatography-mass spectrum analysis showed that the mutant M22 could degrade a wide range of crude oil fractions, while optimization of culture conditions could be effective for increasing its strain's degrading ability.

INTRODUCTION

Petroleum hydrocarbons (PHCs) are a group of extremely complex natural mixture comprising thousands of compounds. Accidental spills, leaks, and other releases of PHCs often result in the contamination of soil and water body. This pollution may result in significant environmental impacts and present substantial hazards to human health, representing a huge concern for the public (ATSDR 1999).

Bioremediation is a cost-effective and environmental friendly remediation technology that can be employed for PHC contamination. Bioremediation of PHC contamination is a hot topic in environmental research, which involves the utilization of specific microbes to transform oil to materials such as water, CO2, inorganic salts, microbial biomass, and other byproducts with less hazards than the parent materials (Lu et al. 2010; Dias et al. 2012). In nature, a wide range of bacteria and fungi can degrade and/or utilize hydrocarbon substrates as sources of carbon and energy, including at least 175 genera of bacteria (McGenity et al. 2012). However, the biodegradation extent of PHCs is limited due to microbial inertness toward some specific compounds, complex composition and chemical structures of PHCs, toxicity of metabolites, etc. (Lu et al. 2009).

As an essential and often most direct and least expensive method of improving industrial organisms, mutation has been exploited and utilized in many industrial processes since the late 1930s (Rowlands 1984). Irradiation mutagenesis by use of X-rays, ultraviolet (UV)-rays, and γ-rays can cause morphological and biochemical changes in microbial cells. Recently, some researchers have used irradiation mutagenesis to enhance microbial degradation capability toward specific compounds. Chen et al. (2011) isolated one mutant by UV light irradiation, which exhibited a biodegradation rate of viscous oil about 11% points higher than its parental strain. Zhou et al. (2013) obtained a mutant of Dietzia sp. strain with high-degradation capability of crude oil by using 12C6+ heavy ion irradiation mutagenesis. In addition, Jiang et al. (2010) reported that a mutant strain of Candida tropicalis obtained by He-Ne laser irradiation could degrade 2,600 mg/L phenol and 300 mg/L m-cresol. Thus, irradiation mutagenesis may be a promising and efficient approach for improving microbial ability to degrade organic pollutants.

Essential nutrients are required for microbial growth and biodegradation of pollutants. The formulation of medium is based on typical elemental composition of microorganisms, which generally contain (cell dry weight %) carbon (50), nitrogen (7–12), phosphorus (1–3), sulfur (0.5–1.0), and magnesium (0.5) (Brinda Lakshmi et al. 2013). Moreover, essential trace nutrients are essential for the growth of microbes. Optimization of nutrient formulas and process parameters by statistical experimental designs is very useful, as it helps in understanding the interactions among the influencing factors at varying levels and in calculating an optimum level of each variable for the maximum pollutant biodegradation (Vieira et al. 2009; Bravo-Linares et al. 2013; Brinda Lakshmi et al. 2013; Huang et al. 2013; Zhou et al. 2013; Gomez & Sartaj 2014; Lv et al. 2014).

In this study, Dietzia sp. GW25 was selected as the original strain of PHC degradation. After mutagenesis of the strain by γ-ray irradiation, a mutant was obtained and named M22. Furthermore, the optimal conditions for the mutant to achieve maximum PHC degradation were established using Plackett–Burman (PB) design, central composite design (CCD), and response surface methodology (RSM).

MATERIALS AND METHODS

Reagents and materials

Multi-state hydrocarbon window defining standard (C8–C40, 500 μg/mL) was purchased from AccuStandards Inc. (New Haven, CT, USA). A chromatographic grade standard mixture consisting of the 16 polycyclic aromatic hydrocarbons (PAHs) prioritized by the US EPA was purchased from Sigma–Aldrich Co., Ltd (St Louis, MO, USA). The 16 priority PAHs are naphthalene (Nap), acenaphthene (Ane), acenaphthylene (Any), fluorine (Fle), phenanthrene (Phe), anthracene (Ant), pyrene (Pyr), fluoranthrene (Fla), benzo[ghi]perylene (Bpe), benz[a]anthracene (Baa), chrysene (Chr), benzo[a]pyrene (Bap), benzo[b]fluoranthene (Bbf), benzo[k]fluoranthene (Bkf), indeno[1,2,3-cd]pyrene(I1p), and dibenz[ah]anthracene (Daa). All the other chemicals used were of analytical or chromatographic grade.

The crude oil used in this study was obtained from the Changqing Oilfield, China. To simulate environmental weathering, the oil was exposed to the atmosphere for 10 days and then sonicated at 35 °C for 6 h before use. After this process, the oil lost about 2.4% of its original weight. The weathered oil consisted of 7.3% asphaltene, 61.5% aliphatic hydrocarbons, 19.8% aromatic hydrocarbons, and 11.4% polar materials.

Microorganisms and culture conditions

An oil-degrading strain (designated Dietzia sp. GW25) was isolated from crude oil-contaminated soil sampled from the estuarine wetland of Liaohe river, China, in our previous work (unpublished results).

The mineral medium (MM) was used in irradiation mutation and mutant screening, of which the composition was as follows (g/L) (Fan et al. 2014): KH2PO4 1.0; NaCl 1.0; Na2SO4 1.0; NH4NO3 1.0; FeCl3 0.05; CaCl2·2H2O 0.02; and MgSO4·7H2O 0.2. The pH was adjusted to 7.2.

Bacteria were cultured in Luria–Bertani (LB) medium (pH 7.2) at 28 °C, the late-exponential phase cultures were harvested by centrifugation at 12,000 g for 5 min at 4 °C, and washed three times with 0.9% NaCl solution and re-suspended in the NaCl solution to a density of about 108 colony-forming units (CFU) per mL, which were then used as the inoculum.

Mutagenesis and mutant isolation

Gamma irradiation treatment was used to isolate mutants as follows. The cell suspension (OD600nm reaching about 1.0) was transferred to sterile tubes and irradiated at room temperature using a 60Co γ-ray irradiator, with dosages of 300–400 Gy (93–99% kill rate).

Irradiated cells were grown overnight in LB liquid medium in the dark and then plated on plates with selective medium. Selective medium was composed of MM supplemented with 2% agar and 0.5% (w/v) crude oil as the sole carbon source. The flasks and plates were wrapped in aluminum foil to avoid photo reactivation. Growth after incubation was recorded as positive mutation result. After incubation at 28 °C for 14 days, formed individual colonies were grown overnight in LB liquid medium, and then 2 mL of the inoculum suspension of each isolate was inoculated to 38 mL MM plus 2% (w/v) crude oil in 100 mL Erlenmeyer flasks, incubated at 28 °C for 14 days. The control was conducted using 2 mL autoclaved (121 °C for 20 min) inoculum suspension instead of a biotic one. The residual total petroleum hydrocarbons (TPHs) in each flask were extracted with dichloromethane for three times and then measured gravimetrically after solvent evaporation under N2. TPH degradation efficiency was calculated using the following equation: 
formula
1
Cells in medium were enumerated in triplicate using the spread plate method on nutrient agar plates. Plates were incubated at 28 °C in the dark for 2 days, and colonies were counted. Results were expressed as CFU/mL.

Analysis of microbial enzyme activity

In this study, microbial enzyme activity was employed to evaluate the property of mutants. Dehydrogenase (DH) activity was measured with 2,3,5-triphenyltetrazolium chloride (TTC) according to the method of Wu et al. (2013). In brief, 1.0 mL of culture solution was mixed with 1.0 mL 3% TTC, 0.07 g CaCO3, and 2.5 mL distilled water and then incubated at 37 °C for 24 h. The triphenyl formazan (TPF) produced from TTC was extracted methanol. The control was prepared using the same procedure except that the substrate TTC was added to the control after incubation. The intensity of the reddish color developed was determined at a wavelength of 485 nm. DH activity was expressed as μg of triphenyl tetrazolium formazan/(mL solution·h).

Polyphenol oxidase (PPO) activity was determined using pyrogallic acid solution according to Ma et al. (2003). For this, each of 1.0 mL culture solution was added to 10 mL 1% pyrogallic acid solution, mixed well, and incubated at 30 °C for 1 h. Then 2.5 mL of 0.5 M HCl was added to the mixed solution and extracted three times with ether. The extract was combined and diluted to 50 mL. The control was conducted using 10 mL distilled water instead of 10 mL 1% pyrogallic acid solution. PPO activity was determined by spectrophotometry at 430 nm, and expressed as mg of purpurogallin (PPG)/(mL solution·h).

Optimization of crude oil biodegradation

The mutant exhibiting the highest oil degradation rate was selected for the degradation optimization experiments. The studies were carried out using media at constant 20 g/L (2%) crude oil at 150 rpm in the orbital shaker for 14 days. All experiments were carried out in triplicate using 100 mL Erlenmeyer flasks containing 40 mL media, and the average of the % degradation was taken as the response.

PB design

As an efficient method to screen the important factors among numbers of variables, PB design was first employed in our study to optimize initial culture conditions of strain to obtain the maximum TPH degradation. Therefore, 11 independent variables (Table 1) were investigated using PB design. For each variable, two levels were designated: +1 for the high level and −1 for the low level. A total of 12 experimental runs with eight variables were performed (Table 2).

Table 1

The Plackett–Burman design for screening the variables, and the statistical analysis of variables

Variable Code Low level (−1) High level (+1) F P-value 
Temperature (°C) X1 25 35 1.46 0.5462 
Initial pH X2 6.5 7.5 18.51 0.0325a 
Inoculation size (% v/v) X3 0.57 0.6830 
K2HPO4 (g/L) X4 0.2 0.5 21.40 0.0266a 
Na2SO4 (g/L) X5 0.5 1.0 8.36 0.7326 
NaCl (g/L) X6 0.5 1.0 13.42 0.5610 
NH4NO3 (g/L) X7 0.2 0.5 28.58 0.0175a 
FeCl3 (g/L) X8 0.02 0.08 7.63 0.3120 
CaCl2·2H2O (g/L) X9 0.01 0.03 24.52 0.2683 
MgSO4·7H2O (g/L) X10 0.1 0.5 11.23 0.2268 
Yeast extract (g/L) X11 0.1 0.5 38.25 0.0063b 
Variable Code Low level (−1) High level (+1) F P-value 
Temperature (°C) X1 25 35 1.46 0.5462 
Initial pH X2 6.5 7.5 18.51 0.0325a 
Inoculation size (% v/v) X3 0.57 0.6830 
K2HPO4 (g/L) X4 0.2 0.5 21.40 0.0266a 
Na2SO4 (g/L) X5 0.5 1.0 8.36 0.7326 
NaCl (g/L) X6 0.5 1.0 13.42 0.5610 
NH4NO3 (g/L) X7 0.2 0.5 28.58 0.0175a 
FeCl3 (g/L) X8 0.02 0.08 7.63 0.3120 
CaCl2·2H2O (g/L) X9 0.01 0.03 24.52 0.2683 
MgSO4·7H2O (g/L) X10 0.1 0.5 11.23 0.2268 
Yeast extract (g/L) X11 0.1 0.5 38.25 0.0063b 

aSignificant at 95% confidence degree (P < 0.05).

bExtremely significant level at 99% confidence degree (P < 0.01).

Table 2

The design and results of Plackett–Burman design

Run order X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 TPH degradation (%) 
−1 −1 −1 −1 −1 49.4 
−1 −1 −1 −1 −1 41.3 
−1 −1 −1 −1 −1 40.5 
−1 −1 −1 −1 −1 43.7 
−1 −1 −1 −1 −1 48.1 
−1 −1 −1 −1 −1 46.4 
−1 −1 −1 −1 −1 38.2 
−1 −1 −1 −1 −1 51.7 
−1 −1 −1 −1 −1 53.4 
10 −1 −1 −1 −1 −1 −1 −1 −1 −1 −1 −1 36.4 
11 −1 −1 −1 −1 −1 63.6 
12 −1 −1 −1 −1 −1 56.2 
Run order X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 TPH degradation (%) 
−1 −1 −1 −1 −1 49.4 
−1 −1 −1 −1 −1 41.3 
−1 −1 −1 −1 −1 40.5 
−1 −1 −1 −1 −1 43.7 
−1 −1 −1 −1 −1 48.1 
−1 −1 −1 −1 −1 46.4 
−1 −1 −1 −1 −1 38.2 
−1 −1 −1 −1 −1 51.7 
−1 −1 −1 −1 −1 53.4 
10 −1 −1 −1 −1 −1 −1 −1 −1 −1 −1 −1 36.4 
11 −1 −1 −1 −1 −1 63.6 
12 −1 −1 −1 −1 −1 56.2 

Path of steepest ascent

Based on the results of PB design, steepest ascent method is used to confirm the center point for CCD. The zero level of PB design was identified as the base point of the steepest ascent path. Experiments were conducted along the steepest ascent path until the response showed no further increase, then this point was considered as the center point of CCD.

Central composite experimental design

After confirmation of the center point, the CCD was adopted for the augmentation of oil biodegradation. In this study, coded representations of variables in the design of experiments for overall biodegradation efficiency were pH, KH2PO4, NH4NO3, and yeast extract, each of which was assessed at five different levels (−2, −1, 0, 1, and 2) as shown in Table 3. According to this design, a total of 30 experiments were conducted containing six replicates at the center point for estimating the purely experimental uncertainty variance in triplicate.

Table 3

Range of variation of the independent variables used in the central composite design

  Level of variation
 
Variable Code −2 −1 
pH A 7.1 7.3 7.5 7.7 7.9 
K2HPO4 (g/L) B 0.06 0.12 0.18 0.24 0.30 
NH4NO3 (g/L) C 0.48 0.54 0.60 0.66 0.72 
Yeast extract (g/L) D 0.38 0.46 0.54 0.62 0.70 
  Level of variation
 
Variable Code −2 −1 
pH A 7.1 7.3 7.5 7.7 7.9 
K2HPO4 (g/L) B 0.06 0.12 0.18 0.24 0.30 
NH4NO3 (g/L) C 0.48 0.54 0.60 0.66 0.72 
Yeast extract (g/L) D 0.38 0.46 0.54 0.62 0.70 

Instrumental analysis

The residual oil in each flask was extracted with dichloromethane for three times. The extracts were combined and condensed to 1 mL by rotary evaporation. Then, the concentrate was fractionated by silica gel column chromatography to separate saturate, aromatic, and polar fractions according to Bastow et al. (2007). The different elute was evaporated to dryness under N2, and calculated gravimetrically. The measurements of n-alkanes and PAHs were performed by gas chromatography–mass spectrometry (GC–MS), using an Agilent Hewlett Packard 6890 gas chromatograph interfaced with a Hewlett Packard 5973 mass-selective detector. Concentrations of each n-alkane were calculated using the standard calibration curve of each corresponding standard compound. Individual PAHs were quantified based on the retention time and m/z ratio of the PAH mixed standard.

Statistical analysis

In this study, Design Expert software 8.0.7.1 (Statease, Inc., Minneapolis, MS, USA) was used for the experiment design and regression analysis. The effect of the variables on % degradation was determined by analysis of variance (ANOVA). The quality of the fit of the % degradation was expressed by the coefficient, and its statistical significance was determined by F-test and t-test. The statistical significance of regression coefficients was 95%.

RESULTS AND DISCUSSION

Mutagenesis and screening for oil hyperdegradation

In the screening experiment, the culture of Dietzia sp. GW25 and its mutant derivatives were grown on the liquid degradation medium for 14 days and compared with respect to the TPH degradation. During the course of the screening, more than 400 resistant colonies could be selected in the fourth mutation cycle. To reduce the work involved in the flask evaluation stage and eliminate unstable mutants, resistant colonies were transferred to selective medium slants and sub-cultured weekly. Most of the resistant mutants lost their growth ability after about six sub-cultures. Eventually, nine mutant derivatives were screened. As shown in Figure 1, only the mutant M22 was improved with respect to the TPH degradation while other mutants showed decreased TPH degradation or no significant increased TPH degradation compared to its wild type. Among those, the maximum TPH degradation (52.5%) was achieved by the mutant M22 with an approximate 0.86-fold increase in oil removal when compared to that (28.2%) of its wild type (Figure 1). The mutant M22 was obtained when the lethal death rate was over 95% and treatment time was 15 s with an irradiation dosage of 400 Gy (data not shown). It was also found that the mutant M22 was still very stable after cultivation for 30 generations.

Figure 1

TPH degradation by the parental strain Dietzia sp. GW25 (A) and mutants (B) M14, (C) M25, (D) M22, (E) M27, (F) M28, (G) M29, (H) M30, (I) M31, and (J) M32 which were mutagenized by 60Co-γ-ray irradiation. Data are given as mean ± S.D., n = 3.

Figure 1

TPH degradation by the parental strain Dietzia sp. GW25 (A) and mutants (B) M14, (C) M25, (D) M22, (E) M27, (F) M28, (G) M29, (H) M30, (I) M31, and (J) M32 which were mutagenized by 60Co-γ-ray irradiation. Data are given as mean ± S.D., n = 3.

Growth characteristics

During the 14-day incubation, the viable cell number of the parental strain GW25 and the mutant M22 in culture media were determined by the culture-based method. The cell density of both strains increased with time (Figure 2(a)). Crude oil is a complex mixture mainly composed of insoluble compounds, which are not easily dispersed in aqueous phase. It is usually believed that only the water-dissolved fractions of hydrophobic organic pollutants are easily available to microorganisms (Déziel et al. 1999). However, bacterial growth may not be restricted to the suspension but also may occur on the surface of pollutant droplets/crystals where a confluent biofilm develops (Wick et al. 2001; Lu et al. 2009). In this study, oil emulsification was observed in the culture flasks (data not shown). This may lead to enhanced solubility of crude oil and thus the rapid bacterial growth in the culture mixture (Figure 2(a)). From Figure 2(a) it was found that the mutant M22 had greater adaptability to the culture conditions and higher growth rate than its parental strain. No apparent lag phase was observed for M22, whereas it lasted for about 2 days for the parental strain. The cell counts quickly increased during the initial period, followed by a slow growth period and a plateau (Figure 2(a)). The final cell density at 14 days was 4.26 × 108 and 2.38 × 109 for the parental strain GW25 and the mutant M22, respectively. There was a significant difference of bacterial colony count between the two strains (P < 0.05). This result was in agreement with that of TPH degradation by these two strains (Figure 1). In comparison to its parental strain, M22 had greater capability of utilizing crude oil as growth substrate, thus leading to higher cell numbers and oil removal.

Figure 2

Time course of (a) cell density, (b) DH activity, and (c) PPO activity in culture media during the 14-day incubation period. Data are given as mean ± S.D., n = 3.

Figure 2

Time course of (a) cell density, (b) DH activity, and (c) PPO activity in culture media during the 14-day incubation period. Data are given as mean ± S.D., n = 3.

Enzyme activity

Microbial DH activity provides a measure of overall microbial activity and can indicate whether stimulation or inhibition of the microbial communities present. Changes in culture DH activity during the 14-day period are shown in Figure 2(b). For each strain, DH activity increased immediately after incubation. The highest DH activity was 75 and 136 μg TPF/(mL h) for the parental strain GW25 and the mutant M22, respectively, which was observed at 6 and 8 days, respectively. Afterwards, DH activity continuously decreased with time. DH activity in the M22 culture was significantly higher than that of the GW25 culture (P < 0.05). DH has been found only to be useful for indicating the onset of the biodegradation process, as its activity decreases rapidly after the rate of biodegradation has declined (Maila & Cloete 2005). Moreover, the increment in DH activity may be in proportion to the rates of oil application, in which activity increased with increasing oil loading rates.

PPO plays an important role in the process of conversion of aromatic organic compounds (Durán & Esposito 2000). Thereupon, determination of this enzyme activity would be helpful to get a better understanding of the metabolic process during biodegradation. Figure 2(c) shows that culture PPO activity increased significantly after incubation. Aromatic compounds and their metabolites in the culture were likely used as substrates, thus raising the enzymatic activity. The PPO activity was higher in M22 culture relative to GW25 culture (P < 0.05). Strains GW25 and M22 showed the highest activity of 11.6 and 34.3 mg PPG/(mL h) at 6 and 10 days, respectively. PPO activity tended to decrease at the later stage of incubation (Figure 2(c)). These results demonstrated that the mutant M22 has enhanced enzyme activity, thereby increasing oil degradation.

PB experiment

The PB experimental design was based on the following first-order model: 
formula
2
where Y is the estimated target function, β0 is the model intercept, βi is the regression coefficient, and Xi is the coded independent factor. This model can be used to screen for factors significantly affecting the measured response but is unable to describe the interaction among factors (Lofty et al. 2007).

Twelve trials were conducted according to the experimental design and the results, analyzed by Design Expert Software, are listed in Table 2. The results of the 12 experiments indicated a wide difference in TPH degradation efficiency, from 36.4 to 63.6%, suggesting that the optimization was crucial for improving the oil degradation efficiency. From the results obtained, it was observed that NH4NO3 favored TPH degradation at the + level, because it provided available nitrogen nutrient for the bacteria. The + level of yeast extract favored TPH degradation by the mutant M22; thus, it can enhance microbial growth and enzyme activity in poor nutrition conditions. Positive effects of yeast extract on hydrocarbon biodegradation by a Psychrotrophic Rhodococcus sp. has been observed (Whyte et al. 1998). The variable K2HPO4 showed negative influence on TPH degradation. It has been reported that the presence of an excess amount of phosphorus could decrease biodegradation of oil hydrocarbons (Xia et al. 2012). Inhibition of biodegradation can occur with high application rates of phosphorus due to the imbalance of C/N/P ratio. Moreover, solution pH favored TPH degradation at the + level.

ANOVA of the results provided the weights of each factor for all of the response, and is shown in Table 1. It showed that X2, X4, and X7 exhibited significant effect on TPH degradation, whose P-values were below 0.05. The P-value for yeast extract (X11) was less than 0.01 with a 99% confidence, indicating that yeast extract concentration had an extremely significant effect on TPH degradation. However, other variables with confidence levels below 95% (P > 0.05) were considered insignificant and were not included in the next path of steepest ascent and CCD experiments.

Path of steepest ascent

To obtain the center points of four variables for CCD, the path of steepest ascent was conducted based on the zero level of the PB design. The path of steepest ascent was aimed to enhance TPH degradation efficiency through increasing the values of X2, X7, and X11, while decreasing the level of X4. The results (Table 4) from the path of steepest ascent showed that TPH degradation efficiency reached a maximum value of 66.8% when the values of X2, X4, X7, and X11 were 7.5, 0.18, 0.60, and 0.54 g/L, respectively. This point was concluded to be near the optimum point and was considered as the zero level of CCD.

Table 4

Experimental design and response value of path of steepest ascent

  Experimental value
 
  
Run order X2 X4 X7 X11 TPH degradation (%) 
6.6 0.42 0.30 0.15 46.3 
6.9 0.34 0.40 0.28 51.6 
7.2 0.26 0.50 0.41 58.2 
7.5 0.18 0.60 0.54 66.8 
7.8 0.10 0.70 0.67 63.3 
8.1 0.02 0.80 0.80 42.6 
  Experimental value
 
  
Run order X2 X4 X7 X11 TPH degradation (%) 
6.6 0.42 0.30 0.15 46.3 
6.9 0.34 0.40 0.28 51.6 
7.2 0.26 0.50 0.41 58.2 
7.5 0.18 0.60 0.54 66.8 
7.8 0.10 0.70 0.67 63.3 
8.1 0.02 0.80 0.80 42.6 

Results of CCD and RSM

To further enhance TPH degradation by the mutant M22, the CCD and RSM were employed to analyze the interactive effects of solution pH, K2HPO4, NH4NO3, and yeast extract and to determine their optimal levels. The values of the four variables in run four obtained from the steepest ascent path (Table 4) were taken as the center points with the other variables fixed at low level of PB experiments (Table 1). The design and results of the experiments carried out with the CCD are listed in Table 5.

Table 5

Experimental design and results of central composite design

  Coded level
 
    Coded level
 
  
  A B C D TPH degradation (%) Run order A B C D TPH degradation (%) 
−1 64.5 16 66.5 
−1 −1 65.3 17 −1 −1 58.3 
−1 −1 61.5 18 −1 68.5 
66.4 19 66.9 
−1 −1 −1 64.9 20 −2 64.2 
66.8 21 −1 −1 −1 −1 62.4 
−1 59.3 22 −1 −1 63.3 
63.4 23 66.4 
−1 −1 −1 60.4 24 65.6 
10 −1 −1 −1 63.6 25 −2 48.7 
11 −1 −1 67.8 26 66.5 
12 65.2 27 67.4 
13 −1 63.1 28 −1 −1 62.3 
14 66.1 29 −2 61.5 
15 −1 −1 −1 61.5 30 −2 64.1 
  Coded level
 
    Coded level
 
  
  A B C D TPH degradation (%) Run order A B C D TPH degradation (%) 
−1 64.5 16 66.5 
−1 −1 65.3 17 −1 −1 58.3 
−1 −1 61.5 18 −1 68.5 
66.4 19 66.9 
−1 −1 −1 64.9 20 −2 64.2 
66.8 21 −1 −1 −1 −1 62.4 
−1 59.3 22 −1 −1 63.3 
63.4 23 66.4 
−1 −1 −1 60.4 24 65.6 
10 −1 −1 −1 63.6 25 −2 48.7 
11 −1 −1 67.8 26 66.5 
12 65.2 27 67.4 
13 −1 63.1 28 −1 −1 62.3 
14 66.1 29 −2 61.5 
15 −1 −1 −1 61.5 30 −2 64.1 
ANOVA of CCD (Table 6) shows that the four variables displayed linear effect with P-value of 0.05 on response. All the first terms (A, B, C, D) and quadratic terms (A2, B2, C2, D2) had significant effect on TPH degradation (P <0.05). However, three interaction terms (AC, AD, CD) had no significant effect on inulinase yield (P > 0.05). Multiple regression analysis was used to analyze the response values and thus a second-order polynomial equation was derived, as follows: 
formula
3
where Y is TPH degradation efficiency, A is initial solution pH, B is K2HPO4 concentration, C is NH4NO3 concentration, D is yeast extract concentration. After neglecting the insignificant terms based on 5% level of significance, it can be expressed as follows: 
formula
4
Table 6

Analysis of variance for response surface quadratic model of total petroleum hydrocarbon degradation efficiency

Source DF SS MS F P-value 
A 2.10 2.10 0.183 0.020 
B 8.76 8.76 0.764 0.033 
C 12.47 12.47 1.088 0.047 
D 50.17 50.17 4.378 0.018 
A2 0.05 0.05 0.004 0.038 
B2 3.15 3.15 0.275 0.014 
C2 22.33 22.33 1.948 0.027 
D2 4.10 4.10 0.358 0.019 
AB 3.90 3.90 0.340 0.034 
BC 4.95 4.95 0.432 0.022 
CD 7.53 7.53 0.657 0.452 
AC 137.19 137.19 11.972 0.746 
AD 1.88 1.88 0.164 0.315 
BD 7.53 7.53 0.657 0.017 
Residual 15 171.89 11.46   
Lack-of-fit 10 171.67 17.17 375.91 <0.001 
Pure error 0.23 0.05   
Source DF SS MS F P-value 
A 2.10 2.10 0.183 0.020 
B 8.76 8.76 0.764 0.033 
C 12.47 12.47 1.088 0.047 
D 50.17 50.17 4.378 0.018 
A2 0.05 0.05 0.004 0.038 
B2 3.15 3.15 0.275 0.014 
C2 22.33 22.33 1.948 0.027 
D2 4.10 4.10 0.358 0.019 
AB 3.90 3.90 0.340 0.034 
BC 4.95 4.95 0.432 0.022 
CD 7.53 7.53 0.657 0.452 
AC 137.19 137.19 11.972 0.746 
AD 1.88 1.88 0.164 0.315 
BD 7.53 7.53 0.657 0.017 
Residual 15 171.89 11.46   
Lack-of-fit 10 171.67 17.17 375.91 <0.001 
Pure error 0.23 0.05   

SS, sum of squares; DF, degree of freedom; MS, mean square.

The results of CCD revealed that the determination coefficient (R-sq.) was 92.56%, implying that more than 91% of the sample variation was attributed to the variables and only less than 8% of the total variance could not be explained by the second-order polynomial prediction equation given in Equation (3). Low P-value of lack of fit (<0.001) and low pure error demonstrated the model was suitable to describe the response of the experiment pertaining to TPH degradation.

The interactions of the four variables and their optimum level in TPH degradation were further analyzed by the RSM. The three-dimension response surface curves are presented in Figure 3. It can be seen that the response surface was convex, suggesting that the optimum conditions are well defined and there existed a maximum for each variable. According to the results of statistically designed experiments, the optimum levels of the four variables were as follows: 7.6 of pH, 0.20 g/L of K2HPO4, 0.57 g/L of NH4NO3, and 0.62 g/L of yeast extract. At this point, TPH degradation efficiency predicted by the model was 69.4%. To confirm these results obtained above, verification experiments were performed under the concentrations: 7.6 of pH, 0.20 g/L of K2HPO4, 0.57 g/L of NH4NO3, and 0.62 g/L of yeast extract, and the rest of the variables were kept at low level of PB experiments (Table 1). Finally, a mean value of (68.5 ± 0.4)% (n = 3) was quite close to the predicted value (69.4%), confirming the model can indeed be employed for optimizing culture conditions for TPH degradation.

Figure 3

The three-dimension response surface plot of the degradation efficiency of TPH.

Figure 3

The three-dimension response surface plot of the degradation efficiency of TPH.

Comparison of biodegradation of hydrocarbon fractions under optimized and unoptimized conditions

We next compared the biodegradation efficiency of individual hydrocarbon fractions under optimized and unoptimized conditions. The unoptimized conditions are the MM conditions (52.5% TPH removal). Repeated degradation experiments were conducted and analysis was done by GC–MS method by taking the residual samples after 14 days.

As can be seen in Table 7, the mutant M22 could completely remove medium chain length n-alkanes (C8–C16) (100%) even under unoptimized conditions. The degradation efficiency of n-alkanes decreased as the chain length increased from C17 to C40. Moreover, the mutant M22 could degrade a certain ratio of 2- to 4-ring PAHs, but it was unable to degrade higher ring PAHs. Furthermore, it can be found that the degradation efficiency was higher under optimized conditions than under unoptimized conditions for most of the hydrocarbon fractions. The results clearly indicated that optimization was effective for crude oil biodegradation.

Table 7

Removal percentages of n-alkanes and polycyclic aromatic hydrocarbons after 14 days of incubation

Fraction  Optimized Unoptimized 
n-alkanes C8–C12 100 100 
C13–C16 100 100 
C17–C20 98.3 91.6 
C21–C24 96.4 84.5 
C25–C28 91.9 76.0 
C29–C32 80.5 62.4 
C33–C40 67.1 48.3 
PAHs 2-ring 53.2 43.5 
3-ring 42.3 31.7 
4-ring 27.4 20.6 
5-ring ND ND 
6-ring ND ND 
Fraction  Optimized Unoptimized 
n-alkanes C8–C12 100 100 
C13–C16 100 100 
C17–C20 98.3 91.6 
C21–C24 96.4 84.5 
C25–C28 91.9 76.0 
C29–C32 80.5 62.4 
C33–C40 67.1 48.3 
PAHs 2-ring 53.2 43.5 
3-ring 42.3 31.7 
4-ring 27.4 20.6 
5-ring ND ND 
6-ring ND ND 

ND: not detected (non-degraded).

It is likely that during the experiment, the microbes in the optimized medium were growing at an optimum environmental condition. Biodegradation process is strongly correlated with oil properties and environmental conditions. Optimal culture composition is important for enhancing oil biodegradation using submerged cultures. Many previous studies have demonstrated that oil biodegradation could be remarkably enhanced by the optimization of cultivation conditions and medium compositions (Vieira et al. 2009; Xia et al. 2012; Bravo-Linares et al. 2013; Huang et al. 2013; Zhou et al. 2013; Gomez & Sartaj 2014).

CONCLUSIONS

Results of the present study have demonstrated that the mutant strain M22, obtained by 60Co-γ irradiation mutagenesis treatment, possessed the strong potential to degrade crude oil compounds. In addition, the results indicate that CCD coupled with RSM is a useful technique to optimize the important parameters of medium for oil degradation. However, the relationship between the nutrients and the composition of oil and the degrading bacteria was not explored. Needless to say, this needs to be further investigated. Moreover, further research is required to explore the transformed functional genes and regulated metabolic network, which are related to hydrocarbon degradation in Dietzia sp. M22 cells mutated by nuclear irradiation.

ACKNOWLEDGEMENTS

This work was funded by the Key Project of National Natural Science Foundation of China (No. 41030426), National Natural Science Foundation (No. 41202097, 41340004), and ‘12th Five-Year Plan’ Major National Science and Technology Projects (Nos. 2011ZX05001-005-03 and 2011ZX05004-005-01).

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