Bioremediation of Oil-Contaminated Soils Using Biosurfactants Produced by Bacteria of the Genus Nocardiopsis sp.

Abstract

One of the effective and safe methods of soil cleanup from oil pollution is bioremediation by introducing microorganisms or their metabolites. In this study, the effect of biosurfactants produced by Nocardiopsis sp. 3mo on the rate of bioremediation of oil-contaminated soils was assessed. Biosurfactants were introduced into soils contaminated with 2% oil at a concentration of 0.05 and 0.1%, and the degree of hydrocarbon degradation was estimated within 63 days. It was found that the studied biosurfactant belonged to the glycopeptide type. The aeration and irrigation of oil-contaminated soil (PSA) resulted in a 5% decrease in the number of hydrocarbons. The introduction of biosurfactants into oil-contaminated soil at a concentration of 0.5 (BS(0.5)) and 1 g kg⁻¹ (BS(1)) resulted in a 29 and 35% decrease in the content of hydrocarbons, respectively. The state of the soil microbiome was assessed by its metabolic activity. Thus, the respiratory activity of microorganisms on the first day after contamination increases by 5–7 times, and urease activity by 3–4 times. The introduction of oil into the soil during the first day reduces the activity of dehydrogenase by 2.3–1.6 times. In the process of bioremediation, the indicators of microbial activity returned to values close to the original. Thus, it was established that the use of biosurfactants produced by Nocardiopsis sp. 3mo increases the ability of the native soil community to degrade hydrocarbons.

1. Introduction

Oil pollution of soils causes serious damage to ecosystems and human health. The necessity of bioremediation for human health is increasingly recognized due to the pervasive nature of environmental pollutants, particularly hydrocarbons from oil spills and industrial activities. These contaminants pose significant risks to public health, as they can enter the food chain, contaminate drinking water sources, and lead to various health issues, including respiratory problems, skin diseases, and even cancer [1,2]. Traditional methods of remediation often may exacerbate environmental damage and pose additional health risks [3,4,5]. In contrast, bioremediation employs naturally occurring or engineered microorganisms to degrade pollutants into less harmful substances, thereby restoring contaminated environments without introducing toxic byproducts. This approach not only mitigates the immediate health risks associated with pollution but also contributes to the long-term sustainability of ecosystems. Such methods include bioaugmentation, which involves the introduction of microorganisms capable of degrading hydrocarbons, and biostimulation, which involves adding nutrients to enhance the activity of native soil microflora [6]. One of the promising approaches to bioremediation is also the stimulation of the activity of native soil microorganisms using biosurfactants [7]. Biosurfactants are secondary metabolites of microorganisms of various structures that have amphiphilic properties [8].

The structure of biosurfactants determines their emulsifying properties and the ability to reduce the surface tension of water. The use of surfactants can increase the rate of desorption, leading to the solubilization or emulsification of hydrocarbons in soils [9,10]. These properties provide the potential of biosurfactants to increase the bioavailability of hydrocarbons, thereby improving their biodegradation by indigenous microorganisms [11,12,13,14].

A key aspect in this case is the study of the microbial communities involved in the bioremediation process and their metabolic capabilities. The diversity and abundance of microorganisms present in contaminated environments directly affect the success of bioremediation. Biosurfactants are highly biodegradable and biocompatible, which makes them suitable for use in the environment, unlike chemical surfactants [12,15]. Studies show that the addition of biosurfactants can significantly improve the bioremediation of oil-contaminated sites by enhancing the biodegradation activity of indigenous microorganisms [14,16,17]. The availability of a contaminant and its ability to penetrate the cell membrane of microorganisms determine the rate at which it can be absorbed and degraded. This is due to the fact that the contact of bacterial cells with hydrocarbon substrates is a prerequisite for the introduction of molecular oxygen into molecules by functional oxygenases [10]. The advantage of using biosurfactants is their high stability to pH and temperatures [7,18], as well as the absence of the need for careful storage of the biopreparation due to the possibility of using only metabolites, and not living cultures of producers. Biosurfactants are produced by various microorganisms, including bacteria, yeasts, and fungi, and common types of biosurfactants include rhamnolipids, sophorolipids, surfactin, iturin, and others [19]. Due to their properties, biosurfactants are currently used in the field of environmental protection for the bioremediation of soils contaminated with heavy metals and hydrocarbons, for the biodegradation of dyes [20,21,22]. Although there are studies on the use of biosurfactants for bioremediation, most of them study biosurfactants produced by the genera Pseudomonas and Bacillus. However, it is known that representatives of other taxa can also be biosurfactant producers. One of the microorganisms known for its ability to degrade oil is Nocardiopsis sp, which is also a producer of biosurfactants [15,23]. Nocardiopsis sp. is a genus of filamentous actinomycetes known to produce various bioactive compounds, including biosurfactants and substances with antimicrobial properties. There is evidence that Nocardiopsis sp. plays an important role in the degradation of PAHs in soils [24]. Researchers have noted the potential for the use of Nocardiopsis bacteria in the bioremediation of soils contaminated with nickel [25], zinc, cadmium, and cesium [26,27].

In addition, representatives of the genus Nocardiopsis are capable of synthesizing various types of biosurfactants, including rhamnolipids and glycolipids, trehalolipids, and others [28]. In the study by Jenifer et al. (2019) [29], using the analysis of the nonribosomal peptide synthetase gene in Nocardiopsis sp. AJ1 strain, they suggest a close similarity to the surfactin synthetase gene, synthetase C, which may indicate the ability to synthesize surfactin. In the work of Roy et al. (2015) [30], biosurfactants produced by Nocardiopsis VITSISB were characterized by FTIR and GC-MS as rhamnolipids. Gandhimathi et al. (2009) [24], analyzing biosurfactants produced by Nocardiopsis alba MSA10, note that TLC and HPLC data allow them to be characterized as lipopeptides. Despite the widespread use of representatives of the genus Nocardiopsis for the purpose of bioremediation of contaminated soils, there are critically few works where the contribution of the biosurfactants produced by them to the process of hydrocarbon degradation in soil experiments was assessed. In addition, the efficiency of using biosurfactants in bioremediation largely depends on the metabolic potential of the native microbial community. The aim of this work was to evaluate the effectiveness of using biosurfactants produced by the Nocardiopsis sp. 3mo strain for the bioremediation of oil-contaminated soils, as well as the influence of biosurfactants on the state and activity of the indigenous microorganisms.

2. Materials and Methods

2.1. Biosurfactant Production and Extraction

The strain Nocardiopsis sp. 3mo, previously isolated from oil-contaminated soil [31], was cultured in a mineral medium (g L⁻¹) containing the following: NaNO₃ 2.0, KH₂PO₄ 0.5, K₂HPO₄ 1.0, MgSO₄ 7H₂O 0.5, KCl 0.1, and FeSO₄ 7H₂O 0.01 with a sunflower cake substrate. The pH was adjusted to 7.0 with 1 N HCl/NaOH. For the preparation of the sunflower cake, it was dried at 55 °C for 4 days, crushed into fine powder, and subsequently, a 10% (w/v) solution of the powder in distilled water was autoclaved. The solution was filtered through gauze to obtain a clear filtrate, which was then added sterilely at a 4% (v/v) concentration to the mineral medium. Bacterial strains were inoculated in 250 mL flasks containing 100 mL of medium and incubated at 120 rpm at 28 °C for 72 h.

In order to obtain the biosurfactants, the cell-free supernatant was obtained by centrifugation at 3000 rpm for 40 min and then was pH-adjusted using 2N HCl, incubated overnight at 4 °C, and centrifuged at 3000 rpm and 4 °C for 40 min. The precipitated fraction was dissolved in a chloroform/methanol (2:1, v/v) mixture, and the crude biosurfactant mixture was obtained using a rotary evaporator under vacuum.

2.2. Characteristics of Biosurfactant Properties

The assessment of emulsifying ability was conducted using the E24 method [32]. This procedure involved combining an equal volume of cell-free strain culture supernatant with crude oil. The cell-free supernatant was obtained via centrifugation of the liquid cell culture (40 min, 3000 rpm). The resulting mixture was vortexed and allowed to stand for 24 h at room temperature. Subsequently, the height of the emulsified column was measured, and E24 was calculated using the following formula:

$$\mathrm{Е}24={\displaystyle \frac{\mathrm{e}\mathrm{m}\mathrm{u}\mathrm{l}\mathrm{s}\mathrm{i}\mathrm{o}\mathrm{n} \mathrm{l}\mathrm{a}\mathrm{y}\mathrm{e}\mathrm{r} \mathrm{h}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}}{\mathrm{t}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l} \mathrm{h}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{l}\mathrm{i}\mathrm{q}\mathrm{u}\mathrm{i}\mathrm{d} \mathrm{c}\mathrm{o}\mathrm{l}\mathrm{u}\mathrm{m}\mathrm{n} \mathrm{i}\mathrm{n} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{t}\mathrm{e}\mathrm{s}\mathrm{t} \mathrm{t}\mathrm{u}\mathrm{b}\mathrm{e}}}\times 100\%$$

(1)

The cell-free strain culture supernatant was analyzed for the reduction in water surface tension (ST) using the Du Nouy ring method with a K20 tensiometer (KRUSS, Hamburg, Germany).

The separation of different surfactant fractions was performed by employing TLC. To assess the composition of the biosurfactants obtained, the crude mixture was dissolved in CHCl₃/CH₃OH (1:1 v/v) and spotted on a silica gel plate (G60, Merck, Darmstadt, Germany). The TLC solvent was a mixture of chloroform/methanol/ammonia solution (65:35:5, v/v/v). The Rf values of the spots obtained were calculated from the TLC plate exposed to UV light. To detect sugars, lipids, and free amino groups in the TLC spots, the following chromogenic agents were used: (i) 100 mL of acetic acid supplemented with 2 mL of sulfuric agent and 1 mL of p-anisaldehyde; (ii) iodine vapor; and (iii) 1% ninhydrin reagent. After staining, the plates were incubated at 110 °C for 10 min for spot development. To determine the type and structure of biosurfactants, Fourier transform infrared spectroscopy with attenuated total reflection technique (ATR-FTIR) was performed using LUMOS I (BRUKER, Billerica, MA, USA). The spectra were collected from 400 to 4000 wavenumbers (cm⁻¹).

2.3. Experimental Design

Soil samples belonging to the vermic chernozem type were collected for the experiment in the Republic of Tatarstan, Russia. The experiment was conducted using the following variants: petroleum-contaminated soil (PS), oil-contaminated soil with aeration (PSA), soil with biosurfactant at a concentration of 0.05% (BS(0.5)), soil with biosurfactant at a concentration of 0.1% (BS(1)), and clean soil (S) was used as a control. All contaminated samples were contaminated with oil at a concentration of 20 g kg⁻¹. The bioremediation process was carried out for 63 days, assessing the physicochemical parameters of the soil and the activity of microorganisms once a week. Once a week, water was added to the soil to maintain 60% of field water capacity.

2.4. Determination of Petroleum Hydrocarbon Content

The content of easily utilized compounds of hydrocarbons was obtained using an AN-2 automatic analyzer (OOO NEFTEKHIMAVTOMAT-IKA-SPb, St. Petersburg, Russia) based on the intensity of the region of IR radiation absorption by methyl and methylene groups of hydrocarbons (-CH₃ and -CH₂) with water numbers in the range from 2700 to 3150 cm⁻¹, which corresponds to the symmetrical and asymmetrical stretching vibrations of these groups. The total petroleum hydrocarbon content (TPH) was determined by the gravimetric method. TPH extracts were dissolved in n-pentane and separated into soluble and insoluble fractions (asphaltene). The soluble fraction was loaded on top of a silica gel G (60–120 mesh) column (2 cm × 30 cm) and eluted with solvents of different polarities. The alkane fraction was eluted with 100 mL of hexane and then the aromatic fraction was eluted with 100 mL of toluene. The resin fraction was eluted with 100 mL of methanol and chloroform [32].

2.5. Evaluation of Microorganism Activity

The respiration activity of the soil microbial community was assessed according to ISO 16072:2002 using gas chromatography [33].

The dehydrogenase (DHA) activity of microorganisms was determined according to the method described in Garcia et al. (1997) [34]. Soil (1 g) adjusted to 60% water-holding capacity was treated with 0.2 mL of 4% 2-p-iodophenyl-3-pnutrophenyl-5-phenyltetrazolium chloride and incubated at 22 °C in darkness (autoclaved soil samples were used as controls). After 20 h, the iodonitrotetrazolium formazan (INTF) was extracted with 10 mL of ethylene chloride/acetone (2:3), measured spectrophotometrically at 490 nm, and the results were expressed as mg INTF g⁻¹ dry soil h⁻¹.

Urease activity was estimated by hydrolysis of urea according to the method described in Ibekwe et al. (2001) [35] with modifications, as follows: 4 mL of phosphate buffer (pH 6.7) and 0.2 mL of toluene were added to soil (2 g) adjusted to 60% water-holding capacity, and after 5 min, 4 mL of 10% urea was added. The mixture was incubated at 37 °C for 24 h. The samples were adjusted to 20 mL with 1M KCl, filtered. Next, 1 mL of filtrate was transferred to a Falcon tube, adjusted to 50 mL with distilled water, and then 2 mL of Nessler’s reagent was added, and extinction was measured at 400 nm. The results were expressed as mg ammonia per kg dry soil [36].

To estimate the functional diversity of soil microbial communities, the Biolog system (Biolog Inc. Hayward, CA, USA) was used. For this, the soil extract was previously prepared (1:40) for 30 min. Soil extracts were inoculated into Biolog EcoPlates by pipetting 140 µL of water into the wells. All microplates were incubated in the dark at in situ temperature. The mineralization of carbon substrates was revealed by the development of a purple color due to the reduction of tetrazolium dye. The substrate consumption rate was assessed using a Thermo Scientific Multiskan FC microplate reader at 595 nm after incubation in the dark at 25 °C for 24 and 120 h. Using the obtained results, the following parameters were calculated: AWCD (average well color development) and alpha-biodiversity Shannon index (H).

2.6. Estimation of Bacterial Abundance by qPCR

The total genomic DNA of the samples was extracted using the FastDNA SPIN Kit for Soil (Bio101, Qbiogene, Heidelberg, Germany), according to the manufacturer’s instructions. The number of 16S rRNA genes in each sample was quantified using quantitative PCR analysis. PCR analysis was performed using the primers 341F-534R [37]. Master Mix contained 0.1 U μL⁻¹ of SynTaq Polymerase, 1 ×SYBR Green Buffer, 2.5 mM of MgCl₂, 200 μM of each dNTP, 0.2 μM of each primer, and 1 μL of DNA template. PCR amplification was performed using the CFX96 Touch Real-Time PCR Detection System (BioRad, Munich, Germany) according to the following protocol: 15 min at 95 °C, followed by 39 cycles at 95 °C for 30 s, 30 s at T_m, and 30 s at 72 °C. A standard curve for estimating the number of 16S rRNA genes was plotted using Pseudomonas fluorescens. The DNA of a positive clone carrying the gene of interest was diluted to various concentrations and amplified to generate a standard curve. The DNA concentration was measured using a Qubit 3.0 Fluorometer (Thermo Fisher Scientific, Waltham, MA, USA). Three replicates for each sample were used for the qPCR analysis. The efficiency of qPCR assays was 94%, and the R2 value was greater than 0.99.

2.7. Statistical Analysis

The experiment was carried out in two replicates, and all analyses were carried out in three replicates. Statistical analysis of the data including Shapiro–Wilk and one-way ANOVA tests with significance set at p < 0.05 was performed using Python (Python 3.12.4) (Supplement Tables S1–S5). Normalized data at a selected time point were used for diversity indices and multivariate analysis. The Shannon index is a measure of biodiversity that takes into account both the abundance and evenness of the species represented. It is calculated using the following formula:

$$H^{\prime }=-\sum _{i=1}^S{p}_i\ln \left(p_i\right)$$

(2)

The AWCD is calculated as the average of the color development in the microtiter plate analysis using the Biolog EcoPlates method. The metabolic diversity of the soil microbiome was calculated using non-metric multidimensional scaling (NMDS) based on the Bray–Curtis coefficient according to the procedure presented by Clark et al. (1993) [38,39].

3. Results and Discussion

3.1. Evaluation of Biosurfactants Produced by Nocardiopsis sp.

The ability of the Nocardiopsis sp. 3mo strain to synthesize biosurfactants was analyzed, for which the surface activity and emulsifying capacity of the culture fluid were assessed. It was found that the culture fluid on the 36th day of cultivation has a surface tension of 3.45 mN m⁻¹, and an E24 value of 30%. These values suggest the significant potential of the biosurfactant produced by Nocardiopsis sp. for reducing surface tension in the acellular supernatant, while also demonstrating favorable emulsifying properties with respect to non-polar hydrocarbon mixtures. The absence of a correlation between surface tension and emulsifying activity has been previously reported by other researchers [40]. This phenomenon can be attributed to the molecular weight of the biosurfactants, indicating that the biosurfactants we isolated are of low molecular weight. The characterization of the biosurfactant extracted from the culture fluid was performed using Fourier-transform infrared spectroscopy (FTIR) and thin-layer chromatography (TLC). Thin-layer chromatography (TLC) analysis of the biosurfactant isolated from Nocardiopsis sp. was performed using silica gel plates treated with ninhydrin and para-anisaldehyde solutions after elution (Supplement Figure S1).

Ninhydrin treatment, aimed at detecting amino acid fragments, did not yield any colored spots, indicating the absence of amino acids and peptides in the sample. At the same time, a number of studies report the ability of Nocardiopsis sp. to produce lipopeptide biosurfactants [24]; however, in our case, the absence of a qualitative reaction in this case implies that the biosurfactant does not contain the expected peptide components, as well as impurities of a similar nature. The demonstration of the absence of amino acid fragments in the extracted product supports the validity of the extraction protocol employed, which may ensure success in applications where peptide residues are undesirable, as they could serve as potential substrates for foreign microbiomes—such as in plant protection agents, for example [13]. In contrast, treatment with p-anisaldehyde allowed us to identify a spot with an Rf value of 0.22, demonstrating a pinkish-red color at the periphery. This observation suggests the presence of a glycolipid biosurfactant in the product, since para-anisaldehyde is commonly used in biosurfactant assays to detect such compounds. This result is consistent with another pool of studies on biosurfactant production by Nocardiopsis sp., reporting the glycolipid nature of its biosurfactants [41,42,43]. The qualitative reaction indicates that the extracted biosurfactant has structural features characteristic of glycolipids, which are known for their surface-active properties.

The ATR-FTIR spectrum of the glycolipid biosurfactant obtained from Nocardiopsis alba MSA10 shows several characteristic absorption bands that provide insight into its chemical structure and functional groups (Figure 1).

The peak at 3299 cm⁻¹ corresponds to the stretching vibrations of hydroxyl groups (–OH), which is characteristic of carbohydrate moieties and confirms the hydrophilic nature of the biosurfactant. The typical doublet of absorption bands observed in the region from 2937 to 2883 cm⁻¹ is attributed to the stretching vibrations of the C–H bonds in the methyl and methylene groups, suggesting the presence of alkyl chains—the hydrophilic tails of biosurfactants. A separate peak at 1653 cm⁻¹ can be attributed to the vibrations of carbonyl groups (C=O), indicating the presence of ester functional groups commonly found in glycolipid biosurfactants. The IR absorption band at 1410 cm⁻¹ is likely due to COO⁻ vibrations, which further characterize the acidic moieties present in the metabolites of the genus Nocardiopsis. The glycolipid nature of the biosurfactant is further supported by the peaks at 1206 cm⁻¹ and 1107 cm⁻¹, which suggest asymmetric C–O–C stretching vibrations associated with glycosidic bonds. The absorption band at 1033 cm⁻¹ is also attributed to C–O vibrations, confirming the structural characteristics typical of glycolipids. Additional peaks at 986 cm⁻¹ and 922 cm⁻¹ may be due to the absorption region of specific C–O and C–C vibrations in the biosurfactant molecule. Finally, the peak at 851 cm⁻¹ is often associated with vibrations of glycosidic bonds, again indicating the presence of carbohydrate components in the biosurfactant. Thus, the nature of the spectrum and the mutual intensity of the absorption bands correspond to the spectra of glycolipids described in the literature [43]. However, glycolipids are a broad class of biomolecules, including rhamnolipids with different ratios of hydrophilic and hydrophobic parts, sophorolipids, galactolipids, etc. [19]. The unambiguous identification with clarification of the structural characteristics of molecules is possible with additional studies using chromatography with mass spectrometry and NMR on ¹H and ¹³C, but our goal was to prove the amphiphilic nature of the compound, in confirmation of the results of the E24 technique and surface tension measurements.

3.2. Laboratory Modeling of the Bioremediation Process

Then, the biosurfactant Nocardiopsis sp. 3mo was used as a biopreparation in the process of oil biodegradation. The effect of the biosurfactant in two concentrations (0.5 and 1 g kg⁻¹) on the process of the biodegradation of hydrocarbons by the native microbial community was assessed. Analysis of the total hydrocarbon content, estimated using the gravimetric method (

Table 1. Level of biodegradation of hydrocarbons in the process of bioremediation.

Sample	Level of Biodegradation of Hydrocarbons, %
	Gravimetric Method	IR Spectroscopy
PS	2.0 ± 0.1	65.3 ± 2.0
PSA	5.0 ± 0.1	68.2 ± 2.7
BS(0.5)	29.4 ± 0.9	86.6 ± 3.5
BS(1)	35.0 ± 1.2	83.5 ± 3.3

), showed that in oil-contaminated soil without the use of bioremediation methods, the reduction in hydrocarbon content reached 2% of the original content, which is most likely due to the evaporation of light fractions in their composition. Aeration and irrigation of oil-contaminated soil (PSA) led to a decrease in the number of hydrocarbons by 5%, due to the activity of the native microbial community. The addition of biosurfactants to oil-contaminated soil at a concentration of 0.5 (BS (0.5)) and 1 g kg⁻¹ (BS(1)) led to a decrease in the total content of hydrocarbons by 29.4 and 35.0%, respectively. These results clearly demonstrate their effectiveness in improving the availability of hydrocarbons to microorganisms, which is critical for successful bioremediation. The process is probably ensured by the following combination of the properties of the Nocardiopsis sp. biosurfactant used: emulsifying and reducing surface tension. The effect of biosurfactants on the rate of hydrocarbon decomposition is enhanced by emulsifying oil and improving their availability to indigenous microorganisms [44]. However, no significant difference was found between the concentration of the introduced biosurfactant and the efficiency of bioremediation (p > 0.05). When the concentration of biosurfactants doubles, the efficiency of bioremediation increases by only 6%, which may be related to their CMC (critical micelle concentration) and requires further investigation. This suggests that both concentrations might be below the CMC for this product, limiting their effectiveness. The literature generally demonstrates that exceeding the CMC values significantly enhances the efficiency of emulsification and degradation of hydrocarbons [18,19,21].

It is known that microorganisms primarily consume most easily utilized compounds, which include methyl and methylene groups of hydrocarbons [10,45]. Analysis of the content of these groups using IR spectroscopy showed a decrease in their quantity in samples of oil-contaminated soil and in soil with aeration by 65 and 68%, and in samples with biosurfactants by 86 and 83% (Table 1).

Evaluation of the dynamics of the degradation of methyl and methylene groups of hydrocarbons (Figure 2) shows a significant decrease already on the 7th day due to an increase in the activity of microorganisms due to the introduction of biosurfactants. Conversely, in samples without biosurfactants, PSA, and control oil-polluted soil PS, a more active degradation process is observed by the 28th day.

The obtained data, including the overall reduction in hydrocarbons and a decrease in the number of methyl and methylene groups of hydrocarbons, indicate that the biosurfactant really allows the soil microbial community to decompose hydrocarbons more efficiently. Our results are consistent with other studies. For example, the use of a biosurfactant produced by the Pseudomonas sp. strain in concentrations similar to ours (0.1% biosurfactant and 2.8% oil in the soil) reduced soil pollution by 42.7%, which is comparable to the results obtained in our experiment [46].

Moreover, our findings largely align with global scientific data, demonstrating similar effectiveness in bioremediation. However, it is important to note that fully analogous experiments are scarce due to variations in conditions, soil types, and soil aeration, soil microbiomes, as well as differences in biosurfactant types and their co-metabolites. There are many studies confirming the effectiveness of using biosurfactants together with bio-augmentation [44,47,48,49,50,51,52,53,54] (Table 2). Thus, bioremediation of oil-contaminated soils (1, 3, 5% contamination) using the Pseudomonas sp. SA3 strain together with a pure biosurfactant allows increasing the efficiency of oil biodegradation by 10–15% [47]. The introduction of R. planticola together with 1.0 g of intracellular lipopeptide reduced the concentration of n-hexadecane in soils by 59%, with an initial concentration of 0.7% [44]. The use of the Pseudomonas aeruginosa UCP 0992 strain and the biosurfactant produced by it for bioremediation purposes allowed achieving the efficiency of oil biodegradation in sand and seawater above 90% [55].

The articles investigating biosurfactants are mainly devoted to studies of rhamnolipids and surfactins produced by bacteria of the genus Bacillus [56,57,58] and Pseudomonas [59,60,61,62,63]. For example, the use of rhamnolipids at a dose of 1.5–2% made it possible to achieve 60% degradation of crude oil 5 and 10% [62,63]. The use of 1.9 mg kg⁻¹ of lipopeptides produced by Bacillus subtilis O9 allowed to achieve a degradation efficiency of 58% in soil contaminated with 6.7 g kg⁻¹ of total resolved aliphatics [56].

The nature of the object contaminated with hydrocarbons also affects the efficiency of oil biodegradation processes. Thus, most studies use hydrocarbon-contaminated sand samples as a model system for bioremediation. With this approach, the efficiency is quite high due to the nature of the sand grain surface and its low dispersion, and the absence of native soil organic matter can affect the affinity for non-polar phases of oil hydrocarbons. For example, the use of lipopeptides produced by B. subtilis ICA56 for bioremediation of sand samples contaminated with 10% crude oil and motor oil allows to achieve a decrease in their concentration by 76 and 88%, respectively [64]. The introduction of 0.175 g kg⁻¹ rhamnolipids into sand contaminated with 0.5% oil allows achieving 97% degradation of alkanes and 95% of PAHs [65]. However, existing experimental designs addressing similar issues are not adequate for making direct and meaningful comparisons with our results. Thus, the use of soils of different types, with different particle size distributions and different proportions of organic matter, and different mineral compositions during incubation under different conditions (shape and volume of vessels, humidity, and temperature), will inevitably lead to significant variability in the effectiveness of bioremediation measures for model pollutants. Such variability requires the expansion of further studies under conditions closer to real ones at spill sites.

3.3. Evaluation of Metabolic Activity of Microorganisms in the Process of Bioremediation

At the next stage, for a deeper understanding of the influence of biosurfactants on the bioremediation process, the metabolic and enzymatic activity of soil microorganisms was assessed. It was found that the introduction of biosurfactants affects the activity of soil enzymes and the structure of the microbial community.

To assess the metabolic activity of microorganisms in the bioremediation process, respiratory, dehydrogenase, and urease activities were analyzed, as well as the analysis of microbial metabolic diversity using the Biolog EcoPlate (Biolog, Inc., Hayward, CA, USA). Respiratory activity, dehydrogenase, and urease enzymes are sensitive to environmental changes and disturbances, making them reliable indicators of microbial activity and soil health [66]. Researchers have shown that urease and dehydrogenase activity can be used as indicators of oil contamination in soils [67]. Using the Biolog EcoPlate allows for community-level physiological profiling through the consumption of different types of carbon substrates. The Biolog EcoPlate allows you to evaluate the microbial metabolic diversity, which is an indicator of changes in the soil microbial community.

Soil contamination with oil significantly increased respiratory activity in all test samples already on the first day after the introduction of oil compared to clean soil (Figure 3A). The respiratory activity of soil microorganisms increases, reaching 1.6 and 2.3 for PS and PSA samples, and 6.5 and 6.3 μg CO₂ g⁻¹ h⁻¹ in BS(0.5) and BS(1) samples on the 21st day, respectively. By day 28, it sharply decreased for all samples; in samples with added biosurfactants, it decreased by 10 times, and for the control, by 5 times. Thus, the addition of biosurfactants increased respiratory activity compared to the control oil-contaminated soil.

During bioremediation, the dynamics of urease and dehydrogenase activity were assessed through intracellular enzymes that are an indicator of microbial activity and reflect the general oxidative potential of soil microorganisms [54,68]. Urease activity after the introduction of hydrocarbons increases for samples BS(0.5) and BS(1) from 7 to 35 days by 3–4 times compared to the initial values—from 7602 to 30,646 and 29,268 mg kg⁻¹—while the values in the control oil-contaminated soils (PS and PSA) did not increase—8337–9578 mg kg⁻¹ (Figure 3B). The urease activity of microorganisms in soils can increase due to stress exposure and the adaptation of microbiota to pollution. Urease activity can remain at a high level, which indicates the high resistance of this enzyme to hydrocarbons. However, after the completion of oil destruction processes, urease activity begins to decrease [44]. The introduction of oil into the soil during the first day reduces the dehydrogenase activity compared to uncontaminated soil by 2.3–1.6 times—from 21.3 to 9.4–13 mg kg⁻¹ (Figure 3C)—and then by the 7th day, it returns to the previous values (22–24 mg kg⁻¹). Oil pollution leads to a decrease in dehydrogenase activity in the soil. This is due to the toxic effect of hydrocarbons on microorganisms, which can cause a decrease in their numbers and diversity, as well as the suppression of their metabolic activity. During bioremediation of oil-contaminated soils, dehydrogenase activity is restored due to the consumption of hydrocarbons.

Analysis of these three indicators of microbial activity showed significant differences for samples with biosurfactants (BS(0.5) and BS(1)) and controls (PS and PSA) (p < 0.05), while no significant differences were observed between different concentrations of 0.05% and 0.1%. It can be noted that soil samples with biosurfactants demonstrate higher activity than the contaminated control [47,69,70]. These results may indicate that the microorganisms of soils treated with biosurfactants were significantly activated, and also affected the metabolic activity of soil microorganisms and enhanced the decomposition of hydrocarbons [71]. Moreover, the increased activity of these enzymes can act as a marker of adaptation of the microbial population to the presence of hydrocarbons polluting the soil.

Table 2. Publications devoted to experiments on bioremediation using biosurfactants.

Authors	Year	Biosurfactant-Producing Microorganism	Biosurfactant Type	Percentage of Biosurfactant Applied	Object	Percentage of Hydrocarbon Pollution/Type of Pollution	Bioremediation Efficiency
Feng et al. [54]	2021		sophorolipid	Soil + consortium + 1.5 g kg−1 SL	soil	0.5 g L−1/diesel oil	44.5% and 57.7%—isolated consortium and isolated consortium and 1.5 g sophorolipid (SL)kg−1
Li et al. [44]	2024	Raoultella planticola	lipopeptides	1 g kg−1 (0.1%) (R. planticola together with 1.0 g intracellular lipopeptide)	soil	7 g kg−1 (0.7%) (dichloromethane to n-hexadecane 20: 1)	59.0% (R. planticola together with 1.0 g intracellular lipopeptide)
Ambust et al. [47]	2021	Pseudomonas sp. SA3	rhamnolipids	1 L (Pseudomonas sp. SA3 + 300 mL crude biosurfactant)	soil	1, 3, 5%/crude oil	10–15% enhancement compared to negative control
Das and Kumar [50]	2018	Bacillus licheniformis	lipopeptides	B. licheniformis +lipopeptides	soil	5%/petroleum	reduction in soil toxicity by 40%
Bezza and Chirwa [58]	2015	B. subtilis	lipopeptides	Bacterial cells (2% v/v) + biosurfactant 0.15% (w/v)	sand	3% (v/v)/motor oil	85%
Silva et al. [55]	2018	Pseudomonas aeruginosa UCP 0992	rhamnolipids	biosurfactant (0.6 g L−1) and (1.2 g L−1) and 15% of Pseudomonas aeruginosa (107 CFUs/mL)	sand	10%/motor oil	90% for 1.2 g L−1 concentration of biosurfactants and Pseudomonas aeruginosa
Rahman et al. [52]	2002	Pseudomonas sp. DS10-129	(i) mixed bacterial consortium (MC), (ii) poultry litter (PL), (iii) coir pith (CP), and (iv) rhamnolipid biosurfactant (BS)	0.1% and 1%	soil	gasoline	67% and 78% amended with RS + GS + MC + PL + CP + BS at 0.1% and 1%
Rahman et al. [53]	2007	Pseudomonas aeruginosa	rhamnolipids with bacterial cell	0.4 mg kg−1	soil	10%, 20%/tank bottom sludge	100% (nC8–nC11), 83–98% (nC12–nC21), 80–85% (nC22–nC31), and 57–73% (nC32–nC40)
Patowary et al. [59]	2018	Pseudomonas aeruginosa SR17	rhamnolipids	1.5 g L−1	soil	6800 ppm, 8500 ppm/TPH	86.1% and 80.5% in two soil samples containing 6800 ppm and 8500 ppm TPH
Cubitto et al. [56]	2004	Bacillus subtilis O9	lipopeptides	1.9, 19.5, 39 mg kg−1	sandy loam soil	5%/crude oil	1.95 and 19.5 mg Bs kg−1 soil—58% and 40% in the RAH concentration
Lai et al. [57]	2008		rhamnolipids, surfactin	0.2%	soils	3000, 9000 mg kg−1/THP	rhamnolipids, surfactin—23% and 14% (3000 mg kg−1), 63% and 62% (9000 mg kg−1)
Szulc et al. [60]	2014		rhamnolipids	150 mg kg−1	soils	1%/crude oil	52 and 53% for non-bioaugmented plots as well as 88 and 89% for bioaugmented plots
Joe et al. [63]	2019	Shewanella sp. BS4	rhamnolipids	2%	soil	10%/crude oil	60%
Jorfi et al. [61]	2014	Pseudomonas aeruginosa	rhamnolipid	240 m L−1	soil	500 mg kg−1/pyrene	biosurfactant, without biosurfactant, and controls—86.4%, 59.8%, and 14%
Bezza et al. [58]	2017	Bacillus cereus SPL-4	lipopeptide	0.2 and 0.6% (w/w)	soil	6745.5 mg kg−1/PAHs	0.2 and 0.6% (w/w)—34.2 and 63%
Millioli et al. [62]	2009		rhamnolipid	1–15 mg g−1	soil	50 mg g−1/crude oil	60%
Guadarrama et al. [46]	2024	Pseudomonas sp.	rhamnolipids	0.1%	soil	28 g kg−1 (2.8%)/crude oil	42.7% vs. chemical surfactants—32.3%
de França et al. [64]	2015	B. subtilis ICA56	lipopeptides	40 mL crude biosurfactant	sand	10%/crude oil or motor oil	76 and 88% for crude oil and motor oil
Nikolopoulou et al. [65]	2013		rhamnolipids	0.175 g kg−1	sand	0.5%/crude oil	97% (n-alkane), 95% (PAH)
Wang et al. [71]	2014		rhamnolipids	0.2 g·kg−1 (0.02%)	soil	PAH	71.5%
Whang et al. [51]	2008	Bacillus subtilis ATCC 21332, Pseudomonas aeruginosa J4	surfactin, rhamnolipid	0.05 g kg−1 of rhamnolipids and 0.04 g kg−1 surfactin	sandy loam soil	7 g kg−1 (0.7%)/diesel	97% by rhamnolipid

Table 2. Publications devoted to experiments on bioremediation using biosurfactants.

Authors	Year	Biosurfactant-Producing Microorganism	Biosurfactant Type	Percentage of Biosurfactant Applied	Object	Percentage of Hydrocarbon Pollution/Type of Pollution	Bioremediation Efficiency
Feng et al. [54]	2021		sophorolipid	Soil + consortium + 1.5 g kg−1 SL	soil	0.5 g L−1/diesel oil	44.5% and 57.7%—isolated consortium and isolated consortium and 1.5 g sophorolipid (SL)kg−1
Li et al. [44]	2024	Raoultella planticola	lipopeptides	1 g kg−1 (0.1%) (R. planticola together with 1.0 g intracellular lipopeptide)	soil	7 g kg−1 (0.7%) (dichloromethane to n-hexadecane 20: 1)	59.0% (R. planticola together with 1.0 g intracellular lipopeptide)
Ambust et al. [47]	2021	Pseudomonas sp. SA3	rhamnolipids	1 L (Pseudomonas sp. SA3 + 300 mL crude biosurfactant)	soil	1, 3, 5%/crude oil	10–15% enhancement compared to negative control
Das and Kumar [50]	2018	Bacillus licheniformis	lipopeptides	B. licheniformis +lipopeptides	soil	5%/petroleum	reduction in soil toxicity by 40%
Bezza and Chirwa [58]	2015	B. subtilis	lipopeptides	Bacterial cells (2% v/v) + biosurfactant 0.15% (w/v)	sand	3% (v/v)/motor oil	85%
Silva et al. [55]	2018	Pseudomonas aeruginosa UCP 0992	rhamnolipids	biosurfactant (0.6 g L−1) and (1.2 g L−1) and 15% of Pseudomonas aeruginosa (107 CFUs/mL)	sand	10%/motor oil	90% for 1.2 g L−1 concentration of biosurfactants and Pseudomonas aeruginosa
Rahman et al. [52]	2002	Pseudomonas sp. DS10-129	(i) mixed bacterial consortium (MC), (ii) poultry litter (PL), (iii) coir pith (CP), and (iv) rhamnolipid biosurfactant (BS)	0.1% and 1%	soil	gasoline	67% and 78% amended with RS + GS + MC + PL + CP + BS at 0.1% and 1%
Rahman et al. [53]	2007	Pseudomonas aeruginosa	rhamnolipids with bacterial cell	0.4 mg kg−1	soil	10%, 20%/tank bottom sludge	100% (nC8–nC11), 83–98% (nC12–nC21), 80–85% (nC22–nC31), and 57–73% (nC32–nC40)
Patowary et al. [59]	2018	Pseudomonas aeruginosa SR17	rhamnolipids	1.5 g L−1	soil	6800 ppm, 8500 ppm/TPH	86.1% and 80.5% in two soil samples containing 6800 ppm and 8500 ppm TPH
Cubitto et al. [56]	2004	Bacillus subtilis O9	lipopeptides	1.9, 19.5, 39 mg kg−1	sandy loam soil	5%/crude oil	1.95 and 19.5 mg Bs kg−1 soil—58% and 40% in the RAH concentration
Lai et al. [57]	2008		rhamnolipids, surfactin	0.2%	soils	3000, 9000 mg kg−1/THP	rhamnolipids, surfactin—23% and 14% (3000 mg kg−1), 63% and 62% (9000 mg kg−1)
Szulc et al. [60]	2014		rhamnolipids	150 mg kg−1	soils	1%/crude oil	52 and 53% for non-bioaugmented plots as well as 88 and 89% for bioaugmented plots
Joe et al. [63]	2019	Shewanella sp. BS4	rhamnolipids	2%	soil	10%/crude oil	60%
Jorfi et al. [61]	2014	Pseudomonas aeruginosa	rhamnolipid	240 m L−1	soil	500 mg kg−1/pyrene	biosurfactant, without biosurfactant, and controls—86.4%, 59.8%, and 14%
Bezza et al. [58]	2017	Bacillus cereus SPL-4	lipopeptide	0.2 and 0.6% (w/w)	soil	6745.5 mg kg−1/PAHs	0.2 and 0.6% (w/w)—34.2 and 63%
Millioli et al. [62]	2009		rhamnolipid	1–15 mg g−1	soil	50 mg g−1/crude oil	60%
Guadarrama et al. [46]	2024	Pseudomonas sp.	rhamnolipids	0.1%	soil	28 g kg−1 (2.8%)/crude oil	42.7% vs. chemical surfactants—32.3%
de França et al. [64]	2015	B. subtilis ICA56	lipopeptides	40 mL crude biosurfactant	sand	10%/crude oil or motor oil	76 and 88% for crude oil and motor oil
Nikolopoulou et al. [65]	2013		rhamnolipids	0.175 g kg−1	sand	0.5%/crude oil	97% (n-alkane), 95% (PAH)
Wang et al. [71]	2014		rhamnolipids	0.2 g·kg−1 (0.02%)	soil	PAH	71.5%
Whang et al. [51]	2008	Bacillus subtilis ATCC 21332, Pseudomonas aeruginosa J4	surfactin, rhamnolipid	0.05 g kg−1 of rhamnolipids and 0.04 g kg−1 surfactin	sandy loam soil	7 g kg−1 (0.7%)/diesel	97% by rhamnolipid

Analysis of the consumption of carbon substrates using the Biolog Ecoplate method showed that after soil contamination with oil, the AWCD index and H index increased, and within 63 days, they decreased again, but did not reach the values for uncontaminated soils (

Table 3. Indicators of metabolic activity of the soil microbial community.

Sample	AWCD		Shannon Index (H)
	1 Day	63 Day	1 Day	63 Day
PS	0.80	0.75	3.08	2.98
PSA	0.81	0.80	2.98	3.13
BS(0.5)	0.66	0.30	2.88	2.79
BS(1)	0.55	0.35	2.89	2.83
S	0.24		2.72

).

On the first day after oil pollution, the AWCD and H index values increase sharply compared to clean unpolluted soil. The AWCD values increase by 333% in the control PS and PSA samples compared to unpolluted soil, and by 275 and 229 times from the experimental BS(0.5) and BS(1) samples. During the bioremediation process, the following decrease in AWCD values is observed: by 30% in the PS sample, and 54.5 and 36.4% in the BS(0.5) and BS(1) samples, respectively.

An increase in the AWCD and H index values may indicate that the microbial community is activating the metabolic pathways responsible for consuming additional substrates—hydrocarbons. This may occur due to an increase in the diversity of substrates, which leads to an increase in the functional diversity of microorganisms [72]. In this case, the functional adaptation of microorganisms is manifested with the appearance of new substrates; a shift towards the degradation of the new substrate occurs, in this case, hydrocarbons [73].

It can be observed that the addition of biosurfactants somewhat suppresses microbial activity compared to the oil-contaminated control (PS and PSA). The specific effects of biosurfactant molecules on cell walls require special attention when used in natural biological consortia; although biosurfactants increase the rate of degradation, their use may not be beneficial for all microbial populations, since the presence of biosurfactants can lead to a decrease in the metabolic activity of some local microorganisms due to the toxicity of biosurfactants for them or due to the competitive advantages of some groups of microorganisms [74]. In any case, changes in the AWCD and Shannon index indicate the diversity of metabolic pathways in microorganisms and their adaptation to new environmental conditions.

By the end of the bioremediation process, the metabolic activity indicators in the biosurfactant-treated samples decrease, possibly due to a decrease in the available hydrocarbon fractions. Such a significant decrease was not found in the control samples. According to the spatial NMDS analysis of metabolic activity, it can be noted that the experimental samples BS(0.5) and BS(1) in the process of bioremediation become closer to the uncontaminated soil sample than the control samples PS and PSA (Figure 4).

Quantitative PCR (qPCR) was used to determine the dynamics of the total bacterial population during bioremediation by amplifying the 16S rRNA genes. This approach is widely used to measure the total bacterial counts in soil [75]. Analysis of the number of bacteria by the 16S rRNA genes in the soil (

Table 4. Dynamics of the number of 16S rRNA genes in the process of bioremediation.

Sample	1 Day	28 Day	63 Day
PS	(1.7 ± 0.0) × 106	(1.5 ± 0.0) × 107	(1.7 ± 0.0) × 107
PSA	(1.5 ± 0.0) × 106	(8.1 ± 0.0) × 106	(2.1 ± 0.0) × 107
BS(0.5)	(8.4 ± 0.0) × 105	(7.8 ± 0.0) × 106	(2.8 ± 0.0) × 107
BS(1)	(1.9 ± 0.0) × 106	(6.6 ± 0.0) × 106	(3.3 ± 0.0) × 107
S	(1.3 ± 0.0) × 107

) showed that oil pollution causes some decrease in their number in all experimental samples; by the 28th day, the number of bacteria in all samples returns to the previous level. The virtually unchanged number of bacteria with an increase in the functional diversity of microbial communities indicates the inclusion of metabolic pathways responsible for the degradation of hydrocarbons, which is also confirmed by the works of other authors [73,76,77].

4. Conclusions

The study found that the use of biosurfactants produced by Nocardiopsis sp. 3mo increases the metabolic activity of native microorganisms in oil-contaminated soil. The use of biosurfactants increased the activity of microorganisms and increased the efficiency of oil product decomposition compared to the control oil-contaminated soil. Thus, the use of biosurfactants produced by Nocardiopsis sp. 3mo can be used for bioremediation of oil-contaminated soils. The advantages of using stable bacterial metabolites instead of the bacteria themselves, such as resistance to temperature, environmental conditions during transportation, and storage, make the use of biosurfactants attractive. There were no significant differences in the effectiveness of using 0.05 and 0.1% biosurfactants. In this regard, further evaluation of the influence of biosurfactants of different concentrations on the efficiency of bioremediation and the state of the soil microbial consortium under real conditions is necessary.