Biodegradation of C20 carbon clusters from Diesel Fuel by Coriolopsis gallica: optimization, metabolic pathway, phytotoxicity

Abstract

This study is to test the capacity of the white rot fungus Coriolopsis gallica for the biodegradation of Diesel Fuel hydrocarbons (DHs). Using the experimental face centered central composite design (FCCCD), culture conditions of the Diesel-mended medium were optimized to reach 110.43% of DHs removal rate, and l5267.35 U L⁻¹ of laccase production by C. gallica, simultaneously. The optimal combination of the cultural parameters was: Diesel concentration range of 2.95–3.14%, inoculum size of 3%, incubation time of 15 days, Tween 80 concentration of 0.05%, and the ratio glucose/peptone (G/P) range of 10.15–10.27. Further, the degradation ability of C. gallica for Diesel Fuel was evaluated through mycelial pellets uptake and oxidative action of fungal enzymes in the optimized degrading-medium using gas chromatography–mass spectrometry (GC–MS). Cyclosiloxanes and C20 PAHs detected as the major compound in Diesel Fuel (46%) was completely bio-transformed to simple metabolites including, essentially benzoic acid ester (71%), alcohols (1.52%) epoxy alkane (1.07%), carboxylic acids (1.24%) and quinones (0.33%). Germination rate and root elongation, as a rapid phytotoxicity test demonstrated that toxicity of Diesel’s PAHs is minimized by fungal treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-021-02769-w.

Introduction

In recent years, there is a drastic increase in the discharge of petroleum hydrocarbons and their derivatives into the environment as a consequence of urbanization, industrialization, and high demand for energy.

Diesel, as a distillate fuel, is a mixture of several structures of hydrocarbons consisting of paraffin (alkanes), cyclic alkenes, and polycyclic aromatic hydrocarbons (PAHs) (Das and Chandran 2011).

Additionally, Diesel Fuels may contain persistent hazardous silicon compounds like polydimethylsiloxanes (PDMS) which is frequently used as antifoaming in the petrochemical processes.

The thermal degradation of PDMS released cyclic methylsiloxanes known to be toxic and poison for catalysts in the industrial processes (Camino et al. 2002).

Petroleum PAHs and their isomers with alkylated groups, are environmentally persistent organic compounds with hazardous chemical structures such as naphthalene, benzo(a)anthracene and benzo(a)pyrene (Chainet et al. 2013; Rengarajan et al. 2015; Dubreuil et al. 2017).

Several alkyl-PAHs and their epoxides are highly toxic, mutagenic, and/or carcinogenic to humans, animals, and microorganisms (Rengarajan et al. 2015; Kim et al. 2016).

PAHs are highly soluble in lipids allowing their accumulation, absorption by the gastrointestinal tract, and distribution in mammalian tissues.

Many PAHs are of special concern since 16 of them have been listed as priority pollutants by the US Environmental Protection Agency (USEPA) and are monitored continuously in industrial effluents (Polidoro et al. 2017).

Pollution, due to PAHs in the environment has become a serious problem. Therefore, the cleanup of petroleum hydrocarbon pollutants in the contaminated sites is one of the greatest scientific and industrial challenges.

Different conventional physic-chemical treatment strategies have been extensively tested in efforts to remove or degrade PAH including, biodegradation (Moghimi et al. 2017), photochemical oxidation (Frena et al. 2014), adsorption to soil particles, leaching, and bioaccumulation (Guarino and Sciarrillo 2017).

However, all of them are not completely effective; costly which makes them nearly abandoned and with limited prospects (Salleh et al. 2003).

As an alternative, bioremediation has become a promising biological treatment for restoring petroleum-contaminated areas.

It has been established as one of the efficient, economic, versatile, and environmentally eco-friendly (Pointing 2001; Clarkson and Abubakar 2015). Bioremediation uses living organisms such as bacteria, fungi, and plants to metabolically breakdown hydrocarbon and organic contaminants (Hildebrandt and Wilson, 1991).

Generally, microbes are selected based on their metabolic diversity and performance to remove or reduce contaminant levels (Boopathy 2000).

In the literature, a wide variety of bacterial, fungal, and algal species have shown their potential to degrade Diesel Fuel, among which bacteria and fungi mediated degradation has been studied most extensively (Olowomofe et al. 2019). Also, fungal-bacterial co-cultures or microbial consortia have been studied to enhance the biodegradation process (Arun et al. 2008).

Due to their robust and biodegradative actions, fungi are well recognized to be potent in the remediation and elimination of various kinds of persistent organic structures, especially petroleum hydrocarbons.

In this regard, white rot fungi (WRF) have been mostly described in 30% of the literature on mycoremediation, as efficient PAHs-degraders (Singh 2006).

Their lignin-degrading enzyme system including laccase (Lac), lignin peroxidase (LiP), and manganese peroxidase (MnP) are the most implicated in the biodegradation processes of petroleum hydrocarbons (Pointing 2001). Other studies reported the role of non-ligninolytic enzymes in degrading PAHs (Bhattacharya et al. 2014; Reyes-Cesar et al. 2014).

Furthermore, mycelial structures of fungi help to pick up and adsorb pollutants, so to improve the removal rate in the mycoremediation processes (Al-Hawash et al. 2018).

The degradation of commercial Diesel oils has been studied by several authors (Bücker et al. 2011; Chaudhary et al. 2019). Many of these studies performed with WRF reported the complete degradation of Diesel oil.

Several fungal species are isolated and characterized as efficient hydrocarbons Diesel fuel degraders such as; Dentipellis sp. (KUC8613), Phanerochaete chrysosporium, Trametes versicolor, Pleurotus ostreatus, Pleurotus eryngii, Cochliobolus lunatus (Park et al. 2019; Wang et al. 2009; Bhattacharya et al. 2014; Young et al. 2005; Czaplicki et al. 2018).

In the Scientific Literature, PAHs from crude oil can be oxidized by fungi via various pathways yielding epoxides, alcohols, diols, and carboxylic acid units (Kadri et al. 2017; Daccò et al. 2020).

Mycoremediation is the remediation with living fungal cultures also known as whole-cell cultures—that have different requirements compared to enzymatic systems. Indeed, fungal degradation of PAHs mostly depends on several environmental conditions; the bioavailability of PAH, nutrients, the biological ability, and microbial inoculum size, nature, and chemical structure of the PAH being degraded.

Meanwhile, these limitations can be overcome by laboratory studies of limiting factors, optimal conditions, and screening of efficient PAH microbial degraders.

The cost-effectiveness of the biological treatment process can be enhanced using statistical and experimental design approach.

Recent studies have indicated the use of face centered central composite design (FCCCD) conducted a minimum quantity of trials to achieve the highest rates (Ravanipour et al. 2015; Ghanem et al. 2016).

The present study employed C. gallica (KJ 412304) for the biodegradation of PAHs from Diesel fuel. FCCCD was used to determine the optimal circumstances of the significant factors affecting the fungal treatment of the Diesel fuel.

For more evidence on PAHs biodegradation and to obtain more information on nature, structural class, and metabolic pathway, experiments have been supported by the technology of gas-chromatography (GC–MS).

Material and methods

Microorganisms

The fungus C. gallica (KJ 412304) was isolated from the decaying wood in the vicinity of Jerusalem, Northwest Tunisia, (Daâssi et al. 2016a). C. gallica was previously identified as an ideal candidate that metabolizes numerous phenolic xenobiotic compounds such as; textile dyes (Daâssi et al. 2013) phenolic compound in olive mill wastewaters (Daâssi et al. 2016b), and bisphenol A (Daâssi et al. 2016c).

The strain was maintained on 2% malt extract agar (MEA) Petri plates fortified with streptomycin (50 mg L⁻¹) to prevent bacterial growth at 4 and sub-cultures every 2 months. Mycelia suspension of the fungal strain was obtained by inoculating four plugs (1 cm²), cut from the growing zone of a 5-day-old fungus grown on Petri plates, into 1000 mL cotton plugged Erlenmeyer flasks containing 250 mL of malt extract medium (18 g L⁻¹).

Coriolopsis gallica was characterized by adaptability to fluctuating pH and temperature, robust growth with the large hyphal network, production of versatile extracellular ligninolytic enzymes, and resistance to heavy metals.

Diesel Fuel and chemical products

The physical properties of the used Diesel Fuel were as follow a molecular formula (C9–C20 compounds), liquid density (kg L⁻¹) (0.80–0.87), lower heating value (MJ kg⁻¹) (42.33), cetane number (48.7), flashpoint (°F) (165), kinematic viscosity (mm² s⁻¹) (2.6).

The Diesel Fuel was sterilized by membrane filter (pore size 0.22 µm) and placed in a previously sterilized dark glass container to prevent photo-oxidation of the fuel.

All ingredients of media were of certified reagent analytical grade, obtained from recognized chemical suppliers.

Growth assay

The degradation studies were performed in a liquid mineral medium (MM) that contains Diesel Fuel as the sole carbon source. The mineral medium (MM) used contained (g L⁻¹): KH₂PO₄, 1.0; KCl, 0.5; MgSO₄ 7 H₂O, 1.0 and 1 mL trace element solution. The trace element solution was used to improve mycelia growth (Daâssi et al. 2016a).

The composition per liter of this solution was as follow: B₄O₇Na₂⋅10H₂O, 0.1 g; CuSO₄⋅5H₂O, 0.01 g; FeSO₄⋅7H₂O, 0.05 g; MnSO₄⋅7H₂O, 0.01; ZnSO₄⋅7H₂O, 0.07 g; (NH₄)6Mo₇O₂₄⋅4H₂O, 0.01 g. The pH of the solution was adjusted to 5.0 before autoclaving. The sole carbon source was Diesel.

Coriolopsis gallica was cultivated with Diesel as the sole carbon source in MM to test their growth and potential to degrade Diesel hydrocarbons (DHs). For this test, 2 mL of Diesel was added to 100 mL of sterilized MM in a 250 mL conical flask, which was inoculated with a (6 mm dia.) of the fungal mycelium from Malt Extract plat.

The flasks were incubated at 30 °C for 25 days in a rotary shaker gyrating at 150 pm. Cultures growing under the same conditions, in MM without Diesel Fuel were used as controls.

For the statistical optimization tests, a stock Diesel Fuel, Tween 80 solution, glucose, and peptone solutions, sterilized by syringe filter (0.22 µm) were separately added to the medium at the desired concentration. Before using in the biodegradation experiments, the strain was first precultivated for 3 days. Cultures were incubated at 30 ºC on a rotary shaker (150 rpm). Then, homogenized mycelium prepared by homogenizer-mixer, was used at the desired proportion, as inoculum to the liquid medium (MM).

All cultures were supplemented with CuSO₄ (150–300 µM) at the beginning of the cultivation to induce laccase production [CuSO₄ (60 mM) solution was sterilized separately].

The flasks were incubated in a shaking incubator (150 rpm) at 30 °C for 20 days. To control the abiotic degradation of Diesel, inoculum-free flasks were prepared. According to the statistical experimental design, the composition of the medium was modified.

Biomass and adsorption determination of Diesel Fuel hydrocarbons

After sequential incubation periods of 3, 6, 9, 12, 15, 18, 20, and 25 days, fungal biomass was determined after filtering 50 mL of the culture medium through Whatman No 1 filter paper. The retained biomass samples were weighed and dried in pre-weighted receipt at 60 °C until constant weight. The dry mass was obtained by subtraction. Inoculated culture but without Diesel Fuel was used as control.

The gain in biomass under each treatment and the corresponding control were calculated. The biodegradation due to the enzymatic activity of C. gallica was calculated by subtraction between the gain in treatment and the control flask. For the adsorption test, the residual DHs in mycelial pellets were extracted according to the method of Chen and Wang (2011). After culture incubation times, mycelia were obtained by centrifugation at 7000g for 5 min at 4 °C. The separated mycelial pellets were taken under agitation in an ice bath for 5 min then washed twice with a solvent mixture of isopropanol/butanol/chloroform 10:10:1 v:v:v) to extract the adsorbed DH on the mycelial pellet surface.

Residual concentrations of DHs in the medium and mycelial pellets were determined. Three replicate flasks were maintained for each assay.

The percentage of Diesel oil degradation was then calculated gravimetrically according to Oudot (1984).

$$\text{Degradation}\%=\left(\text{Weight of diesel oil initial}-\text{the weight of diesel oil after treatment}\right)/\text{weight of diesel oil initial}\times 100.$$

Laccase activity assay

At different incubation times of Diesel Fuel cultures with C. gallica as described above, aliquots of cultures were centrifuged for 5 min at 10,000 pm and 4 °C to measure laccase activity in the supernatant.

Laccase (Lac) activity was determined using 500 µM of 2,2-azimo-bis-3-ethyl-benzothiazole-6-sulfonic acid (ABTS) in 50 mM sodium tartrate buffer (pH 4.5) with 50 µL of culture filtrate and monitoring absorbance at 420 nm using a 2600 UV–Vis spectrophotometer (Shimadzu) (Ɛ 420 nm = 36,000 M⁻¹ cm⁻¹) (Eggert et al. 1996). One unit (U) of laccase activity was defined as the production of 1 µmoL product per min at 30 °C and pH 4.5.

Statistical optimization of simultaneous laccase production levels and Diesel Fuel hydrocarbons removal by C. gallica

Face centered central composite design (FCCCD) under RSM methodology was used to determine the effects of five selected factors: Diesel concentration (X1; 1, 5, 9%), inoculum concentration (X2; 1, 2, 3%), Time culture incubation (X3; 5, 12.5, 20 days), Tween 80 concentration (X4; 0.01, 0.03, 0.05%) and the ratio (glucose/peptone) (X5; 5:1, 20:2, 30:2) for enhancing the rate of DHs removal (Y1) and the level of secreted laccase (Y2). Design Expert Statistical software (version 6.0.8) was used to generate the experimental matrix.

Fifty experimental runs shown in Table 2 were conducted with 8 runs at the central point for five process parameters. Ranges and levels (− 1, 0, + 1) of the independent variables and the experimental design used for the study were shown in Table 1 and 2 (in supplementary material).

Table 2.

Main compounds identified in the extracted of diesel fuel hydrocarbons from the supernatant of C. gallica culture

	RT	Compound name	Compound nature	Molecular weight	Molecular formula	SI	Area%	E1a	E2b	E3c
1	5.03	Benzoic acid,3,4,5trihydroxy, propyl ester	Ester compounds	212	C10H12O5	480	70.17			****
2	5.24	N-a,N-e-Dicarbo-benzoxy-l-arginine	Cyclic amine compound	442	C22H26N4O6	622	0.67	*
3	5.27	4-acetyl4(benzene-sulfonyl)1,2-dimethyl1cyclohexene	Aromatic compound	292	C16H20O3S	466	0.57			*
4	5.42	7,4etheno1-2(9-triptycyl)3Hbenzo[a]anthracene	Alcoholic aromatic compound	506	C40H26	478	0.80			*
5	5.68	2-isopropyl-4-methy-2-5-dihydrooxazole	Aromatic amide	127	C7H13NO	507	2.62			*
6	5.83	dl2,6diaminoheptanedioic acid	Carboxylic acids	190	C7H14N2O4	409	0.57			*
7	5.9	Pregn5en20one,3,16,17,21tetrakis[(trimethylsilyl)oxy],O(phenylmethyl)oxime	Aromatic compound	757	C40H71NO5Si4	349	3.14		*
8	6.09	DL-leucine, benzyl ester	Amino-ester	221	C13H19NO2	456	0.72			*
9	6.30	2,5-pentadecadien-1-ol	Unsaturated alcoholic compound	224	C15H28O	434	0.69			*
10	6.59	Diethyl 3,4bis(methylene)cyclopentane-1,1-dicarboxylate	Aromatic alkaloids	238	C13H18O4	341	3.22		*
11	6.65	Heptane,2,3-dimethyl	Alkanes	128	C9H20	541	2.18			*
12	6.75	Dodeca-chloro-3,4-benzo-phenanthrene	Aromatic compound	636	C18Cl12	346	2.76		*
13	7.16	Methyl1{4methoxy3chloro6[2[3(2′methoxy3′chloro5′(1,3dioxan2yl)phenyl)4methoxyphenyl]ethyl]phenyl}2methoxybenzene4carboxylate	Aromatic alkaloids	666	C36H36Cl2O8	448	1.65		*
14	7.69	(12,12,17,18,22,23)-Hexamethyl2,7-anthraquinono(26,27b-)phthalocyanine))zinc	Polyphenols	638	C38H30N4O2Zn	374	2.98		*
15	7.93	Heptane,2,3-epoxy	Epoxy alkanes	114	C7H14O	481	1.07			*
16	8.20	6,6-dimethylhept-2-en-1,5-diol	Alcoholic compounds	158	C9H18O2	326	0.44			*
17	8.63	Tetramethyltetraphenyl cyclotetrasiloxane	Cyclic-silica compounds	544	C28H32O4Si4	353	2.12		*
18	8.96	Hexa-deca-methyl-cyclo-octa-siloxane	Aromatic silica compound	592	C16H48O8Si8	580	0.87	*
19	9.19	Phenyl[1 + 1]cycloamide	Cyclic-amide compound	668	C45H68N2O2	497	1.71		*
20	9.41	7-hydroxy-7-methyl 1,5-octen4-one	Ketones	156	C9H16O2	350	0.44			*
21	10.69	Dodecachloroperylene	Aromatic compound	660	C20Cl12	387	0.32			*
22	11.55	Cyclononasiloxane, octadecamethyl	Aromatic silica compound	666	C18H54O9Si9	595	3.59	*
23	12.62	1,2 benzenedicarboxylic acid, dibutyl ester (butyl phthalate)	Plasticizer compound	278	C16H22O4	507	0.53			*
24	13.54	Pregn5en20one,3,16,17,21tetrakis[(trimethylsilyl)oxy],O(phenylmethyl)oxime, (3á,16à)	Aromatic alkaloids	757	C40H71NO5Si4		1.94		*
25	14.26	1,2-benzenedicarboxylic acid, dibutyl ester	Esters	278	C16H22O4	694	12.4	***
26	14.40	Pyrrolo[1,2a]pyrazine1,4dione,hexahydro3(2methyl propyl)	Polyphenol compound	210	C11H18N2O2	439	0.86	*
27	14.81	(2-methoxyethoxy)methyl-2,12-dibromo7phenyl 5,6,8,9tetrahydrobenz[a,j]anthracene14carboxylate	Aromatic alkaloids	646	C33H28Br2O4	436	3.38		*
28	15.19	Dodeca-chloro-perylene	Aromatic compound	660	C20Cl12	389	1.86		*
29	15.44	Methyl1{4Methoxy3chloro6[2[3(2′methoxy3'chloro5′(1,3dioxan2yl)phenyl)4methoxyphenyl]ethyl]phenyl}2methoxybenzene4carboxylate	Esters	666	C36H36Cl2O8	332	1.83
30	15.91	1acetyl4,4bis[4(3bromopropoxy)3,5dime thoxyphenyl]piperidine	Bromine aromatic compound	617	C38H68Br2	437	0.31			*
31	16.10	Glycyl-l-histidyl-l-lysine acetate	Amine acetate	470	C14H24N6O4	418	0.31	*
32	16.78	Cyclodecasiloxane, eicosamethyl	Aromatic silica compound	740	C20H60O10Si10	668	8.83	*
33	19.22	Cyclononasiloxane-octadecamethyl	Aromatic silica compound	591	C18H54O9Si9	666	10.94	***
34	21.51	Eicosa-methylcyclodecasiloxane	Aromatic silica compound	740	C20H60O10Si10	618	10.24	***
35	23.67	Eicosamethylcyclodecasiloxane	Aromatic silica compound	740	C20H60O10Si10	567	5.68	**
36	24.57	Dodecachloro-3,4-benzophenanthrene	Aromatic compound	636	C18Cl12	343	2.05		*
37	25.71	Eicosamethylcyclodecasiloxane	Aromatic silica compound	740	C20H60O10Si10	544	3.63	*
38	27.62	1HPurin-6-amine,[(2fluorophenyl)methyl	Aromatic amine compound	243	C12H10FN5	506	3.17	*
39	29.19	Norcollatone	Alcohols	494	C28H30O8	366	1.72		*
40	29.41	Eicosamethylcyclodecasiloxane	Aromatic silica compound	740	C20H60O10Si10	474	3.45	*
41	31.08	Eicosamethylcyclodecasiloxane	Aromatic silica compound	740	C20H60O10Si10	457	3.30	*
42	31.40	lValine	Amine	117	C5H11NO2	314	0.34			*
43	32.48	Dodecachloroperylene	Chloro-Aromatic compound	660	C20Cl12	312	1.6		*
44	34.42	Glycocholic acid methyl ester TMS	Fatty acids ester	695	C36H69NO6Si3	320	0.55			*
45	34.86	4-hydroxy-3-(2-oxo-2H-1-oxa-3-Phenalthryl)-2(1H)-quinolinone	Alkaloids	355	C22H13NO4	356	0.37			*
46	35.85	3,5di(4bromophenyl)methylene1ethylpiperidine4one	Aromatic aminecompound	346	C21H19Br2NO	346	1.75	*
47	36.57	4-(4methoxycarbonylphenyl) 7,7-dimethyl-2–5-dioxo-1, 2,3,4,5,6,7,8octahydro-quinoline	Polyphenols	327	C19H21NO4	335	2.98		*
48	37.84	Naphtho(2,3c)furan-1(3H)one, tetrahydro-6 hydroxyphenyl)-7-methoxy	Aromatic compound	356	C20H20O6	323	1.65		*

RT retention time, SI direct matching factor

(*)The intensity of the area (%): (< 5% _*) (5–10% _**) (10–20%_***) (> 20%_****)

^aE1: ethyl acetate extracts of treated diesel fuel hydrocarbons (DHs) at time 3 days

^bE2: ethyl acetate extracts of adsorbed DHs into mycelial pellets in 15 days

^cE3: ethyl acetate extracts of treated DHs in 15 days

The second-order polynomial equation related to the variables of the independent process and response to attention:

$$y={\beta }_0+\sum _{i=1}^n{\beta }_i{X}_i+\sum _{i=1}^n{\beta }_{\mathit{ii}}{X}_i^2+\sum _{i=1}^{n-1}\sum _{j=i+1}^n{\beta }_{\mathit{ij}}{X}_i{X}_j,$$

where Y is the response of the system, β₀ is constant, β_i is linear constant, β_ii is quadratic constant and X_i is the independent variable.

Design expert, version 7.0 (STAT-EASE Inc., Minneapolis, USA) was employed for the experimental designs and statistical analysis of the experimental data. The analysis of variance (ANOVA) was used to estimate the statistical variables.

The results obtained were used to develop a regression model by analyzing the values of the regression coefficient and analysis of variance (ANOVA). The fitness of the quadratic polynomial model equation was expressed by the coefficient of determination, R². Validation of the experimental model: the adequacy of the experimental model was verified for all three parameters and five sets of experiments were carried out comparing the experimental values obtained with those predicted by the model.

The face-centered central composite design (FCCCD) was used for laccase production and Diesel hydrocarbon removal by C. gallica. The obtained results were used for analysis. The complete design matrix generated with FCCCD with coding variants, the reported response from experiments, and the predicted response for laccase production and Diesel hydrocarbon removal by C. gallica.

Samples preparation for GC–MS analysis

After incubation periods, the filtrate (liquid medium) and residue (fungal biomass) were separated by filtration, and both were acidified with concentrated HCl to pH 2.5 and sequentially extracted twice with 2 volumes of ethyl acetate, respectively (Mittal and Singh 2009).

Extracted samples were dried by passing through the funnel containing the anhydrous sodium sulfate.

The dried extract was concentrated by rotator evaporator at room temperature. The residual fraction of DHs adsorbed on mycelial pellets surface and absorbed by mycelial pellets (DHs mp) were (E2) extracted according to the method of Chen and Wang (2011).

Dried samples were finally dissolved in 0.5 mL ethyl acetate and kept at 4 ºC for further analysis by gas chromatography (GC). The Hydrocarbon extracts were weighed to calculate the remaining weight of hydrocarbons.

The removal rate of DHs was determined by a comparison of the remaining Diesel between the control and samples. The extracted samples were collected at time 3 days of the culture (E1), after 15 days from the adsorbed Diesel hydrocarbons into mycelial pellets (E2), and after 15 days from the supernatant of C. gallica culture.

Gas chromatography–mass spectrometry (GC–MS) analysis

GC–MS data were acquired using (Trace GC-IQS mass spectrometer, Thermo Scientific, USA) equipped with an A3000 autosampler. GC is equipped with a TG-5MS Capillary column (30 m × 0.25 mm internal diameter; 0.25 µM film thickness). The temperature was programmed from 50 to 280 °C at a rate of 10 °C min⁻¹. The total run time spanned 41 min. A mass spectrometer in EI mode at 70 eV, source temperature, 200 °C; interface temperature, 220 °C; injector temperature, 220 °C. Diluted sample of 1 μL injected in splitless mode and mass scan, 50–600 amu (atom to mass unit). Helium was used as the carrier gas, at a flow rate of 1 mL min⁻¹ using electronic pressure control. The GC/MS interface temperature was maintained at 280 °C (Xie and Luo 2012).

The residual Diesel after treatment with C. gallica culture and the compounds extracted from the control sample were identified tentatively by comparing their relative retention times and mass spectra with those of WILEY mass spectra database.

The removal of DHs as a whole was expressed as the percentage of removal in relation to the amount of the remaining fractions in the appropriate abiotic control samples. The removal efficiency (RE), based on the reduction in the peak area of selected hydrocarbons from the chromatogram of Diesel from the control culture, was evaluated using the following expression:

$$\text{RE}\left(\%\right)=100-(A_{\text{s}}\times 100/A_{\text{c}}),$$

where A_s is the total area of the peak in each sample, A_c is the total area of the peak in the control, and RE (%) is the efficiency of removal (Michaud et al. 2004).

Phytotoxicity assay

Phytotoxicity of Diesel degradation compounds was tested using tomato plants (L. esculentum) as biological material.

First, tomato seeds (Red Cherry) were surface sterilized by sodium hypochlorite (2.5%) and rinsed with sterile distilled water before being placed in Petri dishes to germinate. Seeds were soaked in water (control condition or treated Diesel solutions (100% concentration), diluted treated Diesel (1/2, 1/4, 1/8). Phytotoxicity can be studied at the germination stage by testing several parameters such as the seed germination percentage, root elongation and germination index.

When the Germination Index (GI) values were (< 50%), in the range of (50–80%) and (> 80%) indicated a high toxicity, low and non-toxicity effects, respectively (Zucconi et al. 1985). Secondly, tomato seeds were sown in alveolus plates and irrigated with distilled water (control condition) or treated Diesel solutions (100% concentration), diluted treated Diesel (1/2, 1/4, 1/8). Three weeks later, tomato seedling were Harvested from soil to be used for different measures (Fresh weight, length of seedlings and photosynthetic pigments which are determined as described by Armon et al. (1956).

Data analysis

The mean and standard deviation (SD) of the results from at least three independent experiments were calculated using Microsoft Excel software (Microsoft). Significant readings were recorded when p was < 0.05.

Results and discussion

Diesel Fuel biodegradation by C. gallica in mineral medium

To explore the ability of the fungal strain C. gallica to degrade and detoxify Diesel Fuel-amended medium, kinetic of laccase production, biomass accumulation, adsorption, and Diesel hydrocarbons (DHs) removal rates were evaluated and their evolution is shown in Fig. 1.

Fig. 1.

Representative kinetics of laccase production (U/mL), gain of biomass (%), and Diesel’s hydrocarbons removal (%) during co-cultivation of C. gallica with Diesel Fuel (1% V:V) as the sole carbon source in MM medium supplemented with 0.15 mM of CuSO4, 150 rpm at 30 °C. Symbols: (Δ) Laccase activity (U/mL); (*) gain of biomass (%), (+) adsorption (%) and (○) Diesel’s hydrocarbons removal rate (%)

During the cultivation of C. gallica with Diesel Fuel (2% v:v) as the sole substrate, it was observed that mycelial pellets successfully adsorbed 10% of the initial DHs concentration in 3 days.

The adsorption of Diesel in fungal biomass suggested that the mycelial pellets entrapped DHs as they occurred in the aqueous phase. This observation is similar to the results of Ghanem et al. (2016) who used A. ustus and A. alternate.

Several other studies on the biodegradation potential of fungi also reported hydrocarbons adsorption under similar conditions.

As it can be seen in Fig. 1, during the initial stage of cultivation, there is slow assimilation of DHs.

The rate of DHs was 14 ± 1.2% in 6 days of incubation. The cultivation of C. gallica with Diesel Fuel as the sole source of carbon showed a greater production of biomass as compared with the corresponding controls, indicating that the fungus was able to feed upon DHs. A significant weight gain of C. gallica on Diesel Fuel culture was recorded (52 ± 0.6%) in addition to the removal of DHs from the cultivation system (45 ± 1.2%) in 20 days of incubation. In the same line with our study, Saraswathy and Hallberg (2005) found that there was biomass accumulation of Penicillium ochrochloron species due to exposure to pyrene. Also Ameen et al. (2015) reported biomass gain during the biodegradation of engine oil by fungal isolates from mangrove habitat in the red sea.

Figure 1 indicated that as the incubation duration increased, there is a simultaneous increase in laccase secretion and DHs removal rates than a pronounced decline in laccase activity pointing to the situation where no more substrate is available. C. gallica laccase levels during the DHs degradation process increase greatly between days 3 and 9, with correlation with the DHs removal yield. Figure 1 showed a steady-state of laccase activity within 10–18 days of inoculation and after that, a decrease in enzyme activity is detected. High laccase activity is measured at 15 days (2774 ± 0.62 U L⁻¹), corresponding to over 45% of Diesel degradation after 20 days. Similar studies have shown that C. gallica is capable of petroleum hydrocarbons mineralization and that rates of mineralization correlate with the secretion of laccases. The study of Agrawal and Shahi (2017) showed the efficiency of Pyrene degradation by novel fungal strain Coriolopsis byrsina strain APC5.

Overall, these results confirmed that C. gallica can grow in Diesel-amended media using different structures of hydrocarbons as individual carbon sources. Accordingly, Daâssi et al. (2013, 2016a; b, c) reported the bio-remediate potential of C. gallica in the biodegradation of various pollutants like textile dyes, BisphenolA, phenols in Olive mill wastewaters.

Statistical optimization of Diesel Fuel degradation by C. gallica culture

To determine the optimized C. gallica culture conditions for the Diesel Fuel hydrocarbons degradation process, five parameters were tested including Diesel concentration (X1), inoculum (X2), time culture (X3), Tween 80 (X4), and C/N ratio (X5), aiming to enhance the laccase secretion (Y1) and the rate of Diesel hydrocarbons removal (Y2).

Those factors and the levels of their variation were selected based on preliminary tests using the single factor design and previous studies on the fungal strain properties (Daâssi et al. 2016a, b, c).

In Literature, different fungal cultures also emphasize the requirement of Diesel concentration, inoculum concentration, time of culture, surfactant concentration, and the ratio C/N, to enhance the rate of laccase production in the presence of petroleum hydrocarbons pollutants (Sliva et al. 2015; Imron and Titah 2018).

RSM using FCCCD was applied to determine the optimal levels of the five selected parameters.

Fifty experimental runs were conducted with 8 runs at the central point for five process parameters.

Ranges and levels (− 1, 0, + 1) of the independent variables and the experimental design used for the study are shown in Table 2 (in supplementary material).

The maximum experimental responses were 99.03% and 5287.60 U L⁻¹ for Diesel Fuel hydrocarbon removal rate and laccase activity respectively.

Whereas its predicted values were 101.80% and 4952.34 U L⁻¹ indicating a strong concurrence between them.

The experimental results analyzed by standard ANOVA (Table 1) and FCCCD design was fitted with the polynomial equation to describe the correlation between the responses [Eq. 1 (Y1); hydrocarbon removal rate (%) and Eq. 2 (Y2): laccase yield (U mL⁻¹)] and the independent variables in terms of coded factors, as follows:

$$\begin{array}{cc}\hfill Y1& =+96.64-11.32\times X1+5.15\times X2+19.32\times X3+4.33\times X4+1.25\times X5-2.91\times X1\times X3\hfill \\ \hfill & -1.86\times X2\times X4+3.87\times X3\times X5-4.20\times X4\times X5-19.89\times X{1}^2-15.40\times X{3}^2-10.69\times X{5}^2.\hfill \\ \hfill \end{array}$$ 1

$$\begin{array}{cc}\hfill Y2& =4637.51-257.78\times X1+314.83\times X2+885.25\times X3-4.61\times X4+212.69\times X5-125.18\hfill \\ \hfill & \times X1\times X2-171.54\times X1\times X4+100.14\times X2\times X3+213.79\times X3\times X5-213.83\times X4\times X5\hfill \\ \hfill & -540.65\times X{1}^2-1375.15\times X{3}^2-1013.15\times X{5}^2.\hfill \\ \hfill \end{array}$$ 2

Table 1.

Statistical analysis of the quadratic models (ANOVA) for laccase (Lac) levels and Diesel’s hydrocarbons (DHs) removal rate during DHs degradation by C. gallica

Source	Sum of squares		df		Mean square		F value		P value
	Lac level	DHs removal	Lac level	DHs removal	Lac level	DHs removal	Lac level	DHs removal
Model	121,102,036.16	40,328.17	13	12	9,315,541.24	3360.68	109.21	88.84	*< 0.0001
Residual	3,070,782.03	1399.63	36	37	85,299.50	37.83
Lack of fit	2,688,925,16	1149,56	29	22	92,721,56	52,25	1.7	49,39	0.240
Cor total	124,172,818.19	41,727.81	49	49

Lac levels				DHs removal rates
Std. dev.	292.061	R2	0.975	Std. Dev.	6.150	R2	0.966
Mean	2645.821	Adj R2	0.966	Mean	65.375	Adj R2	0.956
C.V. %	11.039	Pred R2	0.949	C.V. %	9.408	Pred R2	0.926
PRESS	6,393,813.270	Adeq precision	31.495	PRESS	3093.947	Adeq precision	29.2639834

F Fishers’s function, P level of significance, C.V. coefficient of variation

*Significant values

The significance of each process variable and the overall model significance was studied using analysis of variance (ANOVA), and the results are presented in Table 1.

Statistical regression analysis parameters such as R-squared (R²), the predicted (Pre), and the adjusted (Adj) of R² values; F value and Lack of fit were established and evaluated for the model's reliability.

The current R2 of studied models (R² = 0.975 and R² = 0.966, respectively for laccase production level and DHs removal rate) were above 0.9 showing a good fit. The results also indicated that the Adj-R² value (0.966 and 0.956), is in good agreement with the Pred-R² value (0.949 and 0.926), for Lac level and DHs removal rate, respectively, showing there is a good agreement between the experimental values and the expected values in the model.

Besides, a relatively small value of the coefficient of variation % (C.V. = 11.039% for lac level and 9.408% for DHs removal rate) reflects high precision and accuracy of the experiments values.

The current model's adequate precision value of 31.49 and 29.26; The PRESS (predicted residual sum of squares) value of 6,393,813.2 and 3093.94; the Std. Dev. (standard deviation) value of 292.061 and 6.150, reveal the statistical significance of the model for Lac production level and DHs removal rate, respectively.

Moreover, the model F value of 109.21 and 88.84 implied the models of Lac production and DHs removal % was significant. At the same time, P value was less than 0.05 (P < 0.0001) and the lack of fit for the two models is not significant (Table 1). Overall, these models can be used to navigate the design space.

Figure 1 (in supplementary material) represented a graph of the predicted response values versus the actual response values for DHs removal rate and lac production level. All of the values are predicted by the models.

Graphical interpretation of the response surface model

Three dimensional (3D) plots for diesel removal

3D graphs of response surface are used to graphically represent the regression equation. Figures 2, 3 represent the 3D response surface to optimize the DHs degradation conditions and components of the degrading medium simultaneously with the enhancing of laccase level.

Fig. 2.

3D surface plot for laccase section during the Diesel’s hydrocarbon-degradation bioprocess by C. gallica culture showing the interactive effects of two variables (other variables were kept at zero in the coded unit)

Fig. 3.

3D surface plot for Diesel’s hydrocarbons removal rate by C. gallica culture showing the interactive effects of two variables (other variables were kept at zero in the coded unit)

Each figure demonstrates the effect of two factors while the others were held at zero levels.

The model predicted the maximum DHs degradation rate of 101.8% with 5% (v:v) Diesel concentration, 3% fungal inoculum, 0.03% Tween 80 concentration, and 20/2 the ratio C/N during 12 days of Culture Time.

Subsequent experiments with the optimized nutrient amendment condition yielded results that were consistent with the prediction.

The optimized results were verified by growing C. gallica in the optimized medium containing Diesel Fuel as the sole carbon source for 12 days at 30 °C.

The results shown in table 2 (in supplementary material) indicate that the degradation rate of Diesel oil in the optimized medium was 99.03%.

This was 53% higher than that in MM; furthermore, a four-fold enhancement was observed for the laccase secretion levels in the optimized medium as compared to unsupplemented MM.

The interaction between factors affecting the Diesel biodegradation process showed in Fig. 2 can assist in visualizing the additional effect of Diesel oil concentration, inoculum size, Time Culture, tween 80, and G/P ratio level to the percentage of Diesel degradation.

The plot in Fig. 2a clearly showed that the highest percentage of DHs removal is located close to the center level of Diesel Fuel concentration (X1) and the maximum level of the fungal inoculum density (X2). At a dose of 1–5%, Diesel Fuel stimulated the growth of fungi that provided Diesel removal rates.

Further, up to 5%, a high dose of hydrocarbons resulted in a reduction in the degree of fungal growth rate (seen previously in Fig. 1) so, on DHs removal yield.

By analyzing plots a, b, c, and d in Fig. 3, results indicated that a high concentration of Diesel extensively decreased DHs degradation percentage by varying two variables (other variables were kept at zero in the coded unit) of the treatment process.

The high content of persistent hydrocarbons in Diesel, therefore, may influence the fungal biodegradation activity, resulting in the inhibition of the metabolic pathway.

These findings demonstrated that the initial hydrocarbons concentration can critically influence the rates of fungal growth, metabolic activity so DHs break down.

This result is consistent with that of Palanisamy et al. (2014) who attributed the decrease consumption of Diesel oil at high concentrations (up to 5%) to the stress of hydrocarbons on bacterial species.

The presented results agreed with those of Ghanem et al. (2016), who demonstrated the inhibitory effect of the highly persistent aromatic hydrocarbons on the fungal degradation activity.

By analyzing plots a, f, and g in Fig. 2 and solving the Eq. (1), results indicated that the removal of DHs mainly depends on the fungal biomass introduced in the degrading-medium.

Literature studies demonstrated that the density of fungal cells and the systems of mycelial pellets are directly involved in the process of hydrocarbons degradation.

The surface of Hyphae plays a critical role in the adsorption of petroleum hydrocarbons resulted in the bioavailability of DHs to the fungus that enhances the yield of DHs removal.

In the same context, Saraswathy and Hallberg (2005) indicated the role of mycelial pellets of Penicillium ochrochloron sp. in the transfer of nutrients and oxygen also in the adsorption and absorption of PAHs mechanisms.

Furthermore, many studies reported the effect of inoculum size on a laccase production level so on Diesel removal rates (Ghanem et al. 2016; Agrawal and Shahi 2017).

Plots b, e, and i in Fig. 2 showed the effect of the incubation time of C. gallica culture on Diesel degradation. As can be seen in Fig. 2b, DHs bio-removal rate was slightly improved with a longer incubation period. The effect of incubation time of the culture on Diesel degradation was illustrated in number runs of 17 and 21 (Table 2). It showed similar biodegradation conditions with the difference in the incubation time of the fungal culture. These results indicated that the longer incubation time (20 days) slightly increased Diesel bio-removal rates from 23.75 to 92.60%. Also, Fig. 2e showed this amelioration of Diesel degradation during C. gallica culture with the different introduced size of the fungal inoculum. The rate of change in DHs concentration is proportional to several mechanisms during C. gallica culture including metabolic activities, bioaccumulation of fungal biomass, adsorption, and absorption of DHs into hyphae surface.

Results recorded in this research are in line with that of other researchers (Ameen et al. 2015; Ghanem et al. 2016; Al-Hawash et al. 2018), who reported that hydrocarbons levels could be significantly remedied with a longer incubation period during the treatment of Diesel oil. Accordingly to Imron and Titah (2018), the percentage of Diesel degradation was a dependent variable for 14 days of the remediation period.

Moreover, the work of Agrawal and Shahi (2017) reported that maximum pyrene degradation of 91.6% by Coriolopsis byrsina strain APC5 occurred after 18 days of incubation.

Figure 2c represented the effect of varying concentrations of tween 80 at different Diesel concentrations on hydrocarbons removal amount under 2% fungal inoculum, 20:2 ratio C/N and 12 days incubation time.

The results indicated that increase surfactant concentration favored the bio-removal of hydrocarbons in Diesel Fuel. A maximum DHs rate at the center level of Tween 80 as well as the proportions of Diesel Fuel in the degrading-medium was more than 97.87%.

Further, the role of tween 80 as a surfactant to overcome to limited availability of petroleum hydrocarbons to microorganisms and to decrease the surface tension between water and Diesel molecules, has been demonstrated in many investigations (Das and Chandran 2011; Chen et al. 2011; Hu et al. 2019). Similar results were presented by Imron and Titah (2018) who demonstrated that the supplement of Tween 80 at 9.33 mg L⁻¹ on the Diesel degradation process increases the efficiency of Diesel degradation up to 98% for 15 days.

Figure 2d showed the change in DHs removal rate under the variation of glucose/peptone ratio (G/P) and the initial concentration of Diesel introduced during the process of biodegradation.

As well, the effects of the G/P ratio were indicated in number runs of 41, 42, and 43 (Table 2). It showed similar degradation conditions with a different value of G/P ratio. These results demonstrated that the maximum degradation Diesel rate was obtained in the level zero attributed to the ratio (95.93%). On both sides of level zero, the percentage of DHs degradation decrease in function of the G/P ratio.

These results indicated that the addition of nutrients can increase the efficiency of Diesel degradation in C. gallica culture. Imron and Titah (2018) similarly reported an increase in Diesel biodegradation with the addition of bio-stimulants such as nitrogen and phosphorus as macronutrients for bacterial growth.

Thus, the addition of Nitrogen to the biodegradation process was used for the synthesis of amino acids and nucleic acids so to enhance the rapid growth of microorganisms. On the other hand, the supplement of the Diesel degrading-medium by Phosphorus was for adenosine triphosphate (ATP) and DNA synthesis (Borah and Yadav 2014). Furthermore, the carbon to nitrogen (C/N) ratio is required to overcome limitations in fungal growth and metabolic activity.

The C/N ratio should be high to achieve optimal fungal growth and laccase production (Gao et al. 2007).

Three dimensional (3D) plots for laccase production

The interaction between factors affecting lac production during the Diesel degradation process showed in Fig. 3 can assist in visualizing the influence of Diesel concentration, C. gallica inoculum size, time culture, Tween 80 concentration, and G/P ratio on the laccase production level.

The interaction between inoculum size and initial Diesel concentration with 0.03% of tween 80, 20:2 of G/P ratio and during 12 days of culture incubation depicted in Fig. 3a.

As can be seen in Fig. 3a, the higher level of laccase secreted by C. gallica in the co-culture with Diesel Fuel was attained with the increase in inoculum size. An inoculum size of 3% was adequate for an optimum laccase secretion (5287.60 U L⁻¹). Previous studies demonstrated that the high density of inoculum improved fungal growth but may inhibit oxygen transfer then laccase activities during the biodegradation process (Agrawal et al. 2018a, b).

According to plots a, b, c, and d of Fig. 3, high concentrations of Diesel negatively influence the level of Lac production during the fungal treatment of Diesel Fuel. Thus, an increase of Diesel proportions in the degrading-medium (up to 5%), caused the decrease of the Lac production level. As previously explained the high content of Diesel in persistent hydrocarbons affect fungal growth so laccase production level. Moreover, the effect of Diesel proportion on laccase activity was observed in number runs of 15 and 16 (Table 2).

It illustrated the same conditions with the difference in the Diesel concentration.

All parameters were at the upper level except the G/P ratio.

A decline in Laccase activity from 3824 to 2823 U L⁻¹ has been recorded at 1 and 9% of Diesel Fuel respectively. Maximum laccase yield of 5287.6 U L⁻¹ occurred at 5% Diesel Fuel dose favored the efficiency of Diesel degradation by C. gallica.

These findings demonstrated that Diesel at high concentrations negatively affects the fungal growth and its metabolic activities, so its efficiency in Diesel degradation bioprocesses.

Plots in Fig. 3b, e, h, and i demonstrated that laccase yield was slightly enhanced with a longer incubation period of the Co-culture of C. gallica with Diesel Fuel. The maximum activity was attained after 12 days of incubation (5287.6 U L⁻¹). Culture Time is a key factor for the fungal growth and secretion of extracellular enzymes to remediate xenobiotic compounds such as petroleum-pollutants (Majeau et al. 2010; Daccò et al. 2020).

Also, fungal laccase synthesis in the Diesel degrading-medium was strongly influenced by the inoculum size, substrate composition, and nitrogen concentration (Fig. 3).

According to Fig. 3c, tween 80 and the G/P ratio increased the laccase yield up to central value; the further increase of G/P ratio resulted in a decrease in Laccase secretion. Literature studies mentioned that the major limiting factors of petroleum biodegradation are the bioavailability of hydrocarbons and the carbon/nitrogen (C/N) balance.

Thus, surfactants enhance the solubility so the bioavailability of hydrocarbon and facilitate subsequent biodegradation of the DHs by direct cell contact. Similarly, according to (D'Souza-Ticlo et al. 2009), the addition of Tween 80 as surfactant positively impacted biomass and increased the laccase activity to around 1300 U L⁻¹ secreted by Cerrena unicolor MTCC 5159.

On the other hand, to overcome limitations in the fungal growth and activity during Diesel bio-removal, bio-stimulation agents are commonly used. As can be seen in Fig. 4d, the higher laccase yield was observed at the center level of the G/P ratio (20:2). These results indicated that the C/N ratios lower than 10 stimulated laccase production due to the activation of enzyme synthesis. Similar results were found by Kachlishvili et al. (2005) who reported that the addition of nitrogen leads to repression of hydrolytic enzyme synthesis and induces laccase production. In the same tends, D'Souza-Ticlo et al. (2009) recorded that the combination of low nitrogen and high carbon concentration favored both biomass and laccase production.

Fig. 4.

GC–MS chromatogram of the remainder Diesel in the optimized degrading-medium a at time 3 days of the C. gallica cultivation and b adsorbed into mycelial pellets after 15 days of cultivation, c after 20 days of C. gallica cultivation

Response surfaces curves plotted in Figs. 2 and 3 demonstrated the correlation between the efficiency of Diesel degradation by C. gallica and the level of laccase in the culture. In the same context, many studies illustrated the contribution of the catalytic proprieties of fungal laccases to significant oxidation of the hydrocarbons in Diesel Fuel (Agrawal and Shahi, 2017; Daccò et al. 2020). Wu et al. (2010) similarly recorded that laccase was the main active enzyme during the degradation of anthracene and benz[a]anthracene by Fusarium solani. Also, Eibes et al. 2006 reported that in the case of wood-decaying fungi, the average activities of Ligninolytic enzymes have been correlated with the average rates of PAH biodegradation. Thus, elevated laccase levels in the co-culture of Diesel Fuel with C. gallica are a direct indicator of biodegradation activity.

Optimization using the desirability functions

The optimization process was carried out to determine the optimum conditions for the Diesel degradation process using the Design-Expert version 7.0 (STAT-EASE Inc., Minneapolis, USA) software.

The desired goal for each operational condition was chosen ''in range'' to achieve the highest DHs removal rates and Laccase level in the degrading-medium.

As illustrated in Table 3 shown in supplementary material section, solutions were found with a desirability range from 0.916 and 0.980, respectively.

Table 3.

Diesel Fuel Phytotoxicity on some tomato plants growth parameters (Lycopersicon esculentum L). Values are means of three dependent replicates per treatment

Irrigation condition	Control	100% TD	1/2 dTD	1/4 dTD	1/8 dTD
Phytotoxicity parameters
Germination %	100	47	100	100	100
Root elongation %	–	52.17	82.61	126.69	124.35
Germination index %	–	24.51	75.01	126.69	124.35
Shoot height (mm)	60±3.211a	51.6±2.01a	55.4±4.33a	63.8±3.841a	63±5.03a
Shoot fresh weight (mg)	139.1±9.01a	108±5.592a	142.3±8.65a	184±10a	176±8.816a
Chlorophyll a Chlorophyll b Pheophetines	1.014±0.06a	0.872±0.056a	0.954±0.09a	1.158±0.105a	1.42±0.012a
	1.797±0.133a	1.542±0.012a	1.57±0.108a	2.241±0.02a	2.052±0.021a
	2.161±0.182a	1.86±0.011a	2.042±0.18a	2.68±0.017a	2.49±0.2a

Control = Distilled Water, Treated Diesel = 100% TD, diluted Treated Diesel = dTD, dilution factors = 1/2, 1/4 or 1/8

^a Values are means ± SE and values within rows sharing the same letter are not significantly different (Tukey-Kramer HSD; P < 0.05)

The optimal values of the five variables predicted by the model using a global desirability function (0.980) were: Diesel concentrations range of 2.95–3.14%, Inoculum size of 3%, Culture Time of 15 days, Tween 80 concentrations of 0.05%, and the ratio G/P range of 10.15–10.27. The maximum predicted rates were 110.43% and 5267.35 UL⁻¹ for DHs removal rate and laccase activity, respectively.

Characteristics of diesel degradation

Diesel Fuel hydrocarbons were characterized during the degradation by C. gallica culture in the optimized conditions. The remained DHs were extracted from mycelial pellets and the supernatant of the fungal culture after 15 days of cultivation.

The profiles of DHs in the degrading-optimized medium were examined by GC–MS (Fig. 4a–c). Chromatograms showed an effective reduction in the intensity of Diesel oil peaks after fungal treatment (Fig. 4b, c) compared with the control (Fig. 4a). Both Diesel Fuel hydrocarbons adsorbed on mycelial pellets or remained in the supernatant of C. gallica culture, showed a decrease in the area of major peaks suggesting a breakdown of the main compounds; while new peaks appearing in these samples represented breakdown products or presumed metabolites. C. gallica culture was effective in degrading both short straight-chain saturated hydrocarbon (< C12) and the aromatic hydrocarbons in treated Diesel.

The results show approximately a complete degradation effect on the n-alkenes (octadecane, C18, icosane C20, and docosane C22).

GC–MS profiles demonstrated the ability of C. gallica to biodegrade multiple hydrocarbon compounds; particularly Aliphatics hydrocarbons. Similar results were found by Dacco et al. (2020). For instance, GC-data was used by Li et al. (2008) to analyze the biodegradation of Diesel oil by Cladosporium that strongly degraded Diesel with an amount of degradation up to 34% after 5-day treatment. Our results provided enough evidence that C. gallica could effectively degrade the Diesel substrate.

To understand the DHs degradation process by the fungal system, the components, and metabolic intermediate products were identified based on the comparison of their retention indices and mass spectra with those standards, Wiley library mass spectra database of the GC/MS system, and published data (Joulain and Koenig 1998; ESO 2000).

The main volatile organic components (VOCs) identified in the DHs҅ extracts from the supernatant of C. gallica culture at different incubation times (E1, E2, and E3) were illustrated in Table 2 and listed in order of their elution from the GC column.

Cyclodecasiloxane-eicosamethyl or Dodecachloroperylene was detected as the main C20 carbon cluster compound in the Diesel Fuel. Some volatile silicons were detected in the Diesel hydrocarbons extract (E1) (up to 46%) belonging to the classes of cyclic siloxanes; hexadecamethyl-cyclooctasiloxane (C16), cyclononasiloxane octadecamethyl (C18), and eicosamethyl-cyclodecasiloxane (C20). Cyclic siloxanes were followed by peaks of benzene dicarboxylic acid, dibutyl ester (12.4%) at time 3 days of the fungal treatment with C. gallica.

Accordingly, Dubreuil et al. (2017) reported that Silicon compounds especially Cyclic Siloxanes were the major species recovered in petroleum products using GC-ICP/MS. Schmidt et al. (1985) Reported that the use of GC is often limited by stationary phase degradation at high temperature. Cyclosiloxanes were detected as the thermal degradation products.

In general, silicon is issued from the thermal degradation of poly-dimethyl-siloxanes (PDMS) that frequently used in petroleum products as an antifoaming (Chainet et al. 2013; Dubreuil et al. 2017). This compound is very toxic and known to be poison for catalysts using in petrochemical processes.

Some VOCs listed in Table 2, could be the result of cell metabolism and fungal growth in the Diesel-degrading medium at the first 3 days of treatment (Simona et al. 2017).

In agreement with our study, Fadle et al. (2020) reported that the GC–Ms analysis of petroleum ether fermented wood Nikhra gave tetra-cosamethyl-cyclododecasiloxane and eicosamethylcyclodecasiloxane as the main terpenoids (aromatic fraction) compounds.

Some GC–MS data illustrated the presence of fatty acid, 9,12-octadecadienoic acid (34%) as dominant compound followed by peaks initially identified as a cyclic volatile, eicosamethyl-cyclodecasiloxane oligomers in Alternaria sp. MHE 68 extract (Manganyi et al. 2019).

The presence of cyclic dipeptide such Pyrrolo[1,2a] pyrazine1,4dione, hexahydro3(2-methyl-propyl), and glycyl-l-histidyl-l-lysine acetate was detected in the Diesel degrading-medium (data shown at E1). Those substances supported the growth of fungus during the Diesel Fuel degradation process.

In the same line, cyclopeptide was previously isolated from various fungal broth media (Stopsack et al. 1991; Miosoa et al. 2015).

Besides, the DHs degradation products adsorbed on mycelial pellets were quantified in the extract E1. The major volatile compounds were aromatic heterocycle products with high molecular weight (> C18) including dodeca-chloro-perylene (1.57%), hexamethyl-anthraquinone-phthalocyanine (2.98%), dodecachloro-3,4-benzophenanthrene (2.76%), octahydroquinoline (2.98%) anthracene (1.72%), nitrogen compounds such as isoindoline (1.94%), 1,2-diarachidonoyl-n-glycero-3-phospho-ethanolamine (0.94%).

Most of the identified compounds were with a high molecular weight, of chain lengths up to C18 such as fatty acid methyl esters (C20–C22) or associated with benzene rings or connected with isoindole groups (C32, C45). Thus the highly branched alkanes, cycloalkanes, and condensed aromatics compounds were adsorbed into the mycelial pellets with an amount less than 30%. These findings demonstrated the essential role of fungal hyphae as it determines the surface adsorption and cell absorption influencing the bio-removal of Diesel oil through C. gallica culture. Similar studies reported that the systems of hyphae are, generally, capable of rapidly colonizing and penetrating DHs as well as their transporting and distributing which provides the DHs degradation process (Saraswathy and Hallberg 2005; Zhou et al. 2018). According to Al-Hawash et al. (2018), mycelial pellets of Aspergillus sp. exhibited an effective absorption of petroleum hydrocarbons.

Additionally, the identified metabolites resulting from the Diesel Fuel hydrocarbons degradation process by the supernatant of C. gallica culture in the optimized degrading-medium after 15 days. Benzoic acid ester was the predominant constituent (71%) including Benzoic acid, 3, 4,5trihydroxy, propyl ester.

Furthermore, other classes were found such alcohols (1.52%) including hydrophenanthren9-ol and pentadecadien-1-ol, epoxy alkane (1.07%) like heptane,2,3-epoxy, carboxylic acids (1.24%), quinones (0.33%), and carotenoids (0.38%).

Those metabolites are well reported in the literature as byproducts of the hydrocarbons degradation (Zemo et al. 2016; Wang et al. 2020).

Other VOCs including (dimethyl1cyclohexene, acetyl acetate, carotenoids, and terpenes were resulting from primary metabolism or secondary metabolic pathway during fungal growth in the Diesel degrading-medium (Simona et al. 2017).

Previous studies demonstrated the involvement of various cassettes of ligninolytic and non-ligninolytic enzymes in the hydrolysis process of Diesel hydrocarbon.

The integral-membrane enzymes like cytochrome 450, mono- and dioxygenases were well proven to catalyze the initial metabolic step and release simple metabolites (Ostrem Loss and Yu 2018; Tripathi et al. 2017).

These compounds are followed by further metabolism such as β-oxidation and entry into the tricarboxylic acid (TCA) cycle (Varjani 2017; Simona et al. 2017).

Besides, data presented in Table 2 indicated a significant amount of esters and carboxylic acids such as methylbutanoic acid and benzoic acid with molecular weight ranged between (C10–20). Similarly, Watson et al. (2002) found that the degradation of crude oil released carboxylic acids and esters, parallel to the removal of the n-alkanes.

Based on the identified metabolites (Table 2), the pathway of C20 carbon clusters degradation was suggested as shown in Fig. 5. We found the formation of hydroxylated and dihydrodiols which further transformed to form Trans-Tetraols then Benzoic acid ester (Juhasz and Naidu 2000).

Fig. 5.

Proposed pathway of Decachloroperylene (C20 carbon clusters) degradation by C. gallica, based on the identified metabolites through GC–MS analysis

These findings indicated that the removal of hydrocarbon mainly depends on the cell metabolic activities of C. gallica in which, intracellular non-ligninolytic enzymes (cytochrome 450, mono or dioxygenases, reductases, hydrolases) and extracellular ligninolytic enzymes (phenol oxidases, peroxidases) mediated several bioprocesses such as oxidation, hydrolysis of hydrocarbons or polymerization among the Diesel metabolites.

Previous studies presented evidence for the involvement of laccase enzymes in the white-rot fungal degradation of Diesel Fuel hydrocarbons.

Biological degradation of petroleum hydrocarbon substances can mediate principally via particular extracellular ligninolytic enzymes such as laccase (Nazifa et al. 2018).

In agreement with our study, Agrawal and Shahi (2017) reported that the extracellular ligninolytic enzymes of Coriolopsis byrsina strain APC5 are the most significant enzymes operating in pyrene removal, although there is an amount of biosorption to the fungal hyphae.

Based on GC–MS profiles and characterization of the metabolic metabolites resulting from the DHs degradation process, the amount of DHs removal was the results of two mechanisms: the adsorption or the bioaccumulation of petroleum hydrocarbons into the surface of hyphae and the oxidation of hydrocarbons involving the intra and the extracellular ligninolytic and non-ligninolytic enzymes secreted by the fungus.

Phytotoxicity effect

Tomato seeds germination was variably affected by dilution of treated Diesel solution. When imbibed with water or diluted treated Diesel (1/8 and 1/4), seed germination (%), root elongation (%) and germination index (GI) were maximum (Table 2). Data presented in Table 3 showed that the use of undiluted treated Diesel clearly influences the seeds germination and all the different parameters as similarly found by Agrawal and Shahi (2017).

Our data demonstrated that tomato seedlings irrigated with treated Diesel and diluted at 1/4 and 1/8 showed the more enhanced growth compared to those moisten respectively by distilled water, diluted treated Diesel (½) and finally 100% treated Diesel. The growth enhancement is coherent with the different parameters measured as shoot height, shoot fresh weight, and photosynthetic pigments (Table 3). To explain, we should return to Fig. 1 and plots in Fig. 3, which showed the correlation between the efficiency of Diesel degradation by C. gallica and the level of laccase during the treatment process.

These results, confirmed that laccase played critical role in petroleum hydrocarbons bio-degradation as previously suggested by Nazifa et al. (2018).

Far from, Nitrogen-containing compounds present in treated Diesel (Table 2) improve nitrogen fertilizing soil which presents the major limiting factor of tomato growth (Nasraoui and Gouia 2014). More that, amino acids amount observed in the solution of irrigation (Table 2), is another important factor which improved tomato development.

In 2017, an important study was published by Agrawal and Shahi, confirmed that pyrene metabolites degradation by C. gallica affect positively growth of Cicer arietinum plant. According to these authors and Andriani et al. (2016) and basing on the results described in Table 2 we can suggest that the toxicity of PAHs usually expressed in Diesel is minimized by fungal treatment and Phytotoxicity was attenuated.

However, the important area % occupated by fatty acid ester in the Diesel treated solution was another factor explaining the growth enhancement of tomato plants. This comes back to the significatives roles of organic acids and esters played in plants (signal molecules, phytoalexins, abiotic stress resistance, UV-filters…) (Samanta et al. 2011).

In another way, when we determined the photosynthetic pigments contents, we found that growth enhancement was accompanied by Chla, Chlb, and pheophytines accumulation.

These results confirmed that irrigation with treated Diesel didn’t induce photo-inhibition in plant. Based on the large discussion presented by Medeiros et al. (2019), we can suggest that the different mechanisms and function regulation of TCA cycle, stomata and others were not negatively affected by the treated Diesel solution used for irrigation.

As recapitulation, the enhancement of tomato growth and development under the irrigation state with treated Diesel, approved that the different internal process and metabolisms responsible for tomato growth were maintain.

It is necessary to notify, that the biodegradation of Diesel is a benefic strategy resolving different environmental problematic as water deficit, soil fertilizers, and eliminate organic pollutant causing environment pollution.

Conclusion

This study was designed to optimize the Diesel biodegradation by C. gallica using RSM with FCCCD. The analysis of the degraded products by GC–MS showed that C. gallica degraded completely DHs in the optimized medium under controlled laboratory conditions for 12 days. The major constituent formed in the DHs degradation process was benzoic acid ester (71%).

Supplementary Information

Below is the link to the electronic supplementary material.

Declarations

Conflict of interest

The authors declare that there is no conflict of interest.