Screening and characterization of Lipopeptide Biosurfactant Producing Paenibacilus Dendritiformis and its applicability for enhanced oil recovery

doi:10.21203/rs.3.rs-871557/v2

Download PDF

Research Article

Screening and characterization of Lipopeptide Biosurfactant Producing Paenibacilus Dendritiformis and its applicability for enhanced oil recovery

https://doi.org/10.21203/rs.3.rs-871557/v2

This work is licensed under a CC BY 4.0 License

Version 2

posted

You are reading this older preprint version

Read the latest preprint version →

The biosurfactants produced by microorganisms have high demand from microbial-enhanced oil recovery (MEOR) and they have focused on a chemical surfactant for the past few decades for degrading petro-based pollutants and oil spills due to its non-toxicity and increasing bioavailability. The study aims to identify and screen potential lipopeptide biosurfactant produced by Paenibacillus species employing a design experiment based on RSM. The bacterial culture was isolated from Chilika Lake, India. The data generated from the biosurfactant stability experiments were used to fit a regression model using the parameters such as ph, temp, and salinity to predict the E24 index. R-squared value 0.91 obtained from the ANOVA model explains that the regression model was significant, and the model p-value obtained was < 0.05 and was also statistically significant. Therefore the statistical regression model obtained in the present investigation can predict the E24 index by using any combination of ph, temp, and salinity parameters. The novel isolates obtained in this research were further named Paenibacillus dendritiformis ANSKLAB02 and deposited in GenBank with accession number KU518891. The growth of this species under controlled conditions has a high potential to help in environmental clean-up and is suitable for use in MEOR applications.

Biosurfactant Producing bacteria

Paenibacillus dendritiformis

16S rRNA gene sequencing

Phylogenetic assessment

biosurfactant

lipopeptide

biosurfactant stability test

MLR

Annova

The most prevalent environmental hazard is petroleum pollution, which shows harmful effects on all marine ecosystems due to rapid industrialization leading to an increase in aromatic hydrocarbons over the years. The Environmental Protection Agency, USA, reported the contamination sources are massive: leakages from underground storage tanks, accidents in fuel transportation by ships; which are subject to corrosion, oil extraction, and processing; and inadequate release of oily waste generated by industries that use oil byproducts in the production of plastics, solvents, pharmaceuticals, and cosmetics, which cannot be reused or recycled, as they are toxic, flammable, pathogenic or corrosive. Moreover, for humans, hydrocarbons are considered highly toxic, carcinogenic, and mutagenic [1]. The advancement of sustainable technologies tends towards the natural methods for the remediation of soil and water contaminants has increased based on different biological activities. Microorganisms most prominently have a great diversity of bacteria such as Actinobacteria, Mycobacterium, Penicillium, Mycococcus, Pseudomonas, Nitrosomonas, Flavobacterium, etc. that promote the cracking of hydrocarbons molecules (dioxins, benzene, polychlorinated biphenyls, toluene, etc.) by micelle formation, increasing their mobility, bioavailability and exposure to bacteria, thus favoring bioremediation[2–3]. Some microorganisms have started producing several classes of surface-active compounds such as glycolipids, lipopeptides, phospholipids, neutral lipids or fatty acids, and polymeric biosurfactants [4–6]. The surfactant-enhanced bioremediation emerges as a promising technology for the remediation of PAH or hydrophobic organic compounds contaminated from water and soil surface. In contrast to chemical surfactants, biosurfactant’s utilization for the bioremediation of contaminated water surface and oil spills is not yet well established. Interestingly, the attention of the scientific and industrial community recently focuses on determining potential biosurfactants that can be produced at a large scale because of their lower toxicity, optimal activity at extreme conditions of temperatures, pH levels, and salinity, a higher degree of biodegradability, and higher foaming capacity [7–8].

Biosurfactants contain both the hydrophilic and hydrophobic domains capable of interfacial tension and decreasing surface. Biosurfactant has various compounds like lipopeptides, neutral lipids, fatty acids, and glycolipids. These are non-toxic, biodegradable biomolecules that show the emulsification of hydrophobic compounds [9]. Based on the biosurfactant domain, the hydrophilic domain comprises a carbohydrate, an amino acid, a phosphate group, or similar compounds. In contrast, the hydrophobic domain is most commonly comprised of the carboxylic acid chain. The present property of biosurfactant sustains to cut down the interfacial tensions and surface tensions and make them a potential candidate for enhancing oil degradation [10–11]. The biosurfactant production can be affected by various factors such as the nature of carbon and nitrogen sources used; phosphorus, iron, manganese, and magnesium may also be present. Besides, pH, temperature, agitation and mode of operation are the other essential factor that directly affects the quantity and quality of produced biosurfactant [12]. Therefore, the development of more multifunctional biosurfactants is required to broaden the spectrum of properties available. The biosurfactant production on an industrial scale makes it more worthy for better and efficient bioprocesses to make them competitive because of the chemically synthesized compound's market due to inefficient bio-processing methodology and poor strain productivity [13]. If the biosurfactants are produced from cheap substrates like agro-industrial wastes, which reduces the production cost. Therefore, it is beneficial to identify, isolate and characterize new strains producing biosurfactants from various natural sources like water bodies or contaminated soil. The research anticipated analyzing the stability and efficiency of a new lipopeptide biosurfactant produced by Paenibacillus sp. and the feasibility of its use in bioremediation.

In a previous study, we reported the biosurfactant production by Bacillus subtilis novel strain ANSKLAB03 that can yield 0.324 g of BS in 100mL of the medium [9]. The phenotypic divergence and phylogenetic discreteness suggested that the mentioned Bacillus subtilis strain ANSKLAB03 was novel and submitted to the GenBank database. The identified Bacillus subtilis strain ANSKLAB03 was thermodynamically stable and had − 236.20kcal/mol of the free energy (ΔG) of the anticipated RNA structure [9]. In a study, Bacillus tequilensis ZSB10 isolated from Mexican brines, the author was apt to produce extra-cellular as well as cell-bound biosurfactant employing nine broth cultures composed from hydrolyzates procure from the cellulosic and hemicellulosic fragments of wine-trimming wastes [14]. Similarly, Paenibacillus macerans strain TKU029 can yield exopolysaccharides and the biosurfactant in a medium with 2% (w/v) of squid pen powder as the ace source of carbon/nitrogen. At a concentration of 2.76 g/L, biosurfactant can reduce water surface tension from 72.30 to 35.34 mN/m and can reach an emulsification index of up to 56% in the presence of machine oil with 24h incubation. This biosurfactant was found stable at 121°C for 20 min and a varying pH range of 3 to 11. There were no observable structural changes even in < 5% salt solutions [15].

The present study aims to examine the effect of the lipopeptide biosurfactant produced by novel gram-positive Paenibacillus sp. strain, isolated from brackish water lagoon, on oil spill degradation by a microbial consortium. The biosurfactant produced by isolated Paenibacillus sp. strain was screened, purified, quantified, and characterized by physicochemical properties. Its potential application for enhancing bioremediation was evaluated. The optimum dosage for the maximal output was evaluated. The study describes the location, isolation, screening, and characterization of biosurfactant-producing strain. Besides, extracellularly produced metabolites were extracted for further analysis. Series of assay confirmatory assays were performed for analysis metabolic action to determine the potential of Paenibacillus species in degrading the oil.

Subsequently, it is essential to determine the stability in the harsh environment as the biosurfactant activities are affected by physicochemical factors such as temperature, pH and salinity. Therefore the interactive to identify the effect of pH, temperature, and salinity on biosurfactant stability was tested using a design experiment-based response surface methodology (RSM) with the Box–Behnken experimental design using R programming [16].

2.1. Sample Collection

For the present investigation, the samples were collected from an oil-contaminated site in Chilika Lake, Odisha, 19° 46' 30.3780'' N and 85° 25' 4.8540'' E coordinates of India and great genetic diversity). The samples were collected in sterile 50ml tubes and were immediately stored at 4˚C until usage. This was done to preserve the microbial consortium in the water sample.

2.2. Isolation of Microbial Consortium

The water samples were enriched in sterile Mineral Salt Medium (MSM). 1 ml of sample was inoculated in 100 ml MSM containing (in g/L): 15g NaNO₃, 1.1g KCl, 1.1g NaCl, 0.00028g FeSO₄.7H₂O, 3.4g KH₂PO₄, 4.4g K₂HPO₄, 0.5g MgSO₄.7H₂O, 0.5g yeast extract. The culture was incubated at 37°C in the shaker at 100 rpm. After 48 h of incubation, morphologically different colonies were isolated and screened for biosurfactant production [17].

2.3. Screening of Biosurfactant producing Isolates

Isolates were grown aerobically in a 500 ml Erlenmeyer flask containing 100 ml MSM. The medium consisted of (gl-1) 1.0g K2HPO4, 0.2g MgSO4.7H2O, 0.05g FeSO4.7H2O, 0.1g CaCl2.2H2O, 0.001g Na2MoO4.2H2O, 30g NaCl and crude oil (1.0%, w/v). Loopful of isolated bacterial cultures were inoculated in mineral salt medium and incubated in a shaker at 200 rpm and 30oCfor 7 days. After incubation, the broth was centrifuged at 6000 rpm and 4oC for 15 minutes. The obtained supernatant was filtered using a 0.45µm pore size filter paper (Millipore). The cell-free culture broth was further used to perform drop collapse assay, emulsification assay, oil spreading assay, and surface tension measurement. The bacterial cells were used for the BATH assay. The screening tests were performed in triplicates, and the results were presented as the mean values [18].

2.3.1. Oil spread assay

The assay was performed by the method described by Morikawa et al., 2000 [19]. To 20 ml of distilled water, 20 µl of crude oil was added to the plastic Petri dish surface. 10 µl of cell-free culture broth was added to this oil surface on the Petri plate. The presence of biosurfactant in the cell-free culture broth displaces the oil around it, forming an oil-free clearing zone whose diameter indicates the surfactant activity, called oil displacement activity. Distilled water was used as a negative control and Triton X-100 as a positive control.

2.3.2. Drop collapse test

In 1998, Bodour and Maier established a qualitative test named Drop-collapse test [20–21]. Two microlitres of crude oil were applied to the wells of 96 well microplates and equilibrated 24h. 5µl of the 48h grown culture was transferred to oil-coated well drop by drop. The wells were observed after a minute with a magnifying glass. The same procedure was performed with a centrifuged sample at 15,000 rpm for 5 min to remove cells. The flat drop was indicative of positive biosurfactant production, and the rounded drop indicates negative biosurfactant production [22].

2.3.3. Hydrocarbon overlay agar

ZMA plates were used to perform hydrocarbon overlay agar test; each plate was coated individually with 40µl of kerosene, hexadecane, benzene, and toluene. Pure isolates were inoculated on coated plates and incubated for 7–10 days at 28°C. The presence of emulsified halo was considered positive for biosurfactant production.

2.3.4. Bacterial adhesion to hydrocarbon (BATH) assay

Cell hydrophobicity can be measured by its adherence to hydrocarbons in a method described by Rosenberg et al., 1980 [23]. Washed cell pellets were suspended in a buffer salt solution (g/L, 16.9 K₂HPO₄, and 7.3 KH₂PO₄) diluted to an optical density (OD) of ~ 0.5 at 610 nm. To 2 ml of cell suspension, 100 µl of crude oil was added and vortexed for 3 min. After shaking, it was allowed to stand for 1 hour that separated the oil and the aqueous phases. OD of the aqueous phase was measured at 610 nm in a spectrophotometer. With this, the percentage of cells that were attached to the oil surface was calculated using the following formula:

$$\% bacterial cell adherence=1- \frac{{OD}_{shaken with oil}}{{OD}_{original}} X 100$$

Where, OD_shaken with oil is OD of the cells vortexed with crude oil, and OD_original is OD of the cell suspension in the buffer solution, pre-mixing. A few drops of INT solution (2-(4-iodophenyl)-3-(4-nitrophenyl)-5- phenyltetrazolium chloride) were added to the BATH assay solution and observed under a light microscope. The INT turns red to reduction reaction inside the cells that indicate the cell’s viability attached to the crude oil droplets [24].

2.3.5. Surface tension analysis

Surface tension measurement of cell-free culture broth was determined with a tensiometer, using the du Nouy ring method [25]. Triton X-100 solution was prepared at 1mg/ml concentration and used as the standard.

2.4. Biochemical Characterization

Biochemical characterization of the microbial consortium was performed for the best four organisms. 48 hour activated culture was used to perform the characterization.

2.5. Optimization of Biosurfactant production by Paenibacillus(Isolate 3)

2.5.1. Effect of pH

The range of pH; 5.0, 6.0, 7.0, 8.0, 9.0, and 10.0, was selected for the optimization of pH. 1% glucose as sole carbon source was added in MSM medium, and pH was adjusted by 0.1N HCl and 0.1N NaOH solutions using pH meter. The MSM medium was sterilized in an autoclave at 121°C for 15 min. Activated culture of Paenibacillus(4.28 × 10⁸ CFU ml^− 1) was inoculated and incubated at 37°C for seven days in an orbital shaker at 150 rpm [26].

2.5.2. Effect of Temperature

In addition to the previous method stated in section 2.5.1, the temperature was optimized by carrying out the study at different temperatures;20°C, 30°C, 40°C, 50°C and 60°C. 1% glucose as the sole carbon source was added during the preparation of Mineral Salt Medium (MSM), and the pH were adjusted at 7.0 MSM medium were dispensed in the different flask to be incubated at distinctive temperatures for seven days [27].

2.5.3. Effect of Carbon

In addition to the previous method stated in section 2.5.1, to study the effect of carbon source on the isolated Paenibacillus strain, 8 carbon sources mainly, crude oil, coconut oil, diesel oil, sucrose (C₁₂H₂₂O₁₁), starch (C₆H₁₀O₅)_n, maltose, mannitol, and glycerol were used. 1% of each carbon source was added in different flasks containing MSM medium [27–28]. And the medium was incubated as per the standard protocol mentioned in the previous section [28].

2.5.4. Effect of Nitrogen

In the present study, we have selected the 8 nitrogen sources specifically are ammonium nitrate (NH₄NO₃), ammonium phosphate (NH₄)₃PO₄, ammonium sulphate (NH₄)₂SO₄, ammonium chloride (NH₄Cl), peptone, potassium nitrate (KNO₃), yeast extract, and urea (CO(NH₂)₂). In addition, MSM was prepared with 1% sucrose (C₁₂H₂₂O₁₁) as a carbon source, and 1g/l concentration of one by one nitrogen source, followed by the processor stated in section 2.5.1 [28]. The pH was adjusted at 7.0, and the medium was sterilized at 121°C for 15 min. Activated culture of Paenibacillus (4.28 × 10⁸ CFU ml^− 1) was inoculated, and it is incubated for 7 days at 37°C in an orbital shaker at 150 rpm [28].

2.5.5. Effect of the Carbon and Nitrogen Concentration

The optimized concentration of carbon and nitrogen is essential for maximum yield. In the MSM different concentrations of carbon and nitrogen were added which include: 1%, 2%, 3%, 4%, and 5% separately. The medium’s pH was adjusted to 7.0 and was sterilized in an autoclave at 121°C for 15 min. Inoculated culture of Paenibacillus (4.28 × 10⁸ CFU ml^− 1) was incubated in an orbital shaker (150 rpm) at 37°C for 7 days [28].

2.5.6. Analysis for Optimization Conditions and Biosurfactant Extraction

The bacterial cells were centrifuged for 20 min at 13, 500Xg at 4°C and the supernatant was collected for emulsification activity at the end of each optimization process. The optimal growth conditions were confirmed by emulsification activity and bacterial biomass in each parameter[27–29].

2.6. Biosurfactant Extraction

For the inoculation of Paenibacillus, 100 ml of optimized medium were used from the pure extracted culture and were incubated in a shaking incubator at 120rpm for the incubation period of 7 days at 25°C. The cells were then removed by centrifugation at 5000rpm, 4°C for 20 minutes was performed to remove cell debris. 1MH₂SO₄ were used to adjust the pH of the supernatant at pH 2.0. An equivalent volume of chloroform: methanol in the ratio 2:1 was added. After being shaken well, the mixture was left overnight to get evaporated. The biosurfactant obtained were acquired in the form of white colour sediment [28–29].

2.7. Dry weight of biosurfactant

The sediment was taken out in weighed sterile Petri plate for weight the dry residue and kept in a hot air oven at 115°C for drying for 25 minutes. After drying, the plate was weighted [28–29]. The following formula calculated the dry weight of the biosurfactant:

$$Dry weight of biosurfactant=(weight of white sediment+dish)-weight of the empty dish$$

2.8 Biosurfactant Characterization

The purified Paenibacillus dendritiformis was dissolved in chloroform for thin-layer chromatography (TLC) by using CHCl3: CH3OH: H2O in the solvent system (elute) in the ratio of 65:15:2. 10 µl of the activated bacterial sample was spotted 2.5 cm above the TLC plate’s bottom (20×20 cm, Silica gel 60, Fisher Scientific). Then, the TLC plate is placed in the developing chamber 90 degrees from the plate’s bottom edge to the solvent, and the chamber was sealed. 0.19% of Orcinol solution, 1% of ninhydrin solution and Bromothymol blue were sprayed on TLC plate in UV light(366nm) for the development of spot on the plate, followed by heating at 110°C for 15 minutes in a hot oven to detect red spots of the peptide. Iodine vapour is exposed on the TLC plate to observe yellow spots after development that indicates lipid presence [30–31].

2.9 Fourier Transform Infrared Spectroscopy (FTIR)

IR Spectrum GX (PerkinElmer, USA) was used to determine the distinct chemical structure, bonds, and functional groups present in the biosurfactant applying IR spectral analysis. Spectral lines were observed in the vicinity of 4,000- to 400-cm − 1 for resolution of spectrum applying FTIR. 1 mg of Paenibacillus dendritiformis were used in this analysis to alloyed with 100 mg of KBr and crush against to obtain a pellet. An infrared absorption frequencies database was used to interpret the peaks [32–34].

2.10 Stability Test Calculation of Emulsification index (E₂₄)

2ml of MSM was inoculated with the pure culture colonies and incubated for 48h. After incubation, 2 mL of crude oil was added. It is then vortexed at high speed for 1 min and then allowed to stand for 24 h. The emulsion index (E24) can be calculated as the percent ratio of the emulsified zone layer (mm) to the total height (mm), as described in Eq. [25]

$$Emulsification index= \frac{Height of the emulsification layer}{Total height} X 100$$

In contrast, an Experimental algorithm designed using RSM based on the Box–Behnken model was developed with three variables at three levels (+ 1, 0, − 1): pH (5, 7, and 10); temperature (30, 40, and 60°C); and salinity (4%, 6% and 8%). R programming was used to create a 3-factor Box–Behnken design. The response variable was Emulsification Index (E24)[35–37].

2.11 Statistical analysis

The effect of temperature, pH, and salinity on lipopeptide biosurfactant stability was measured in independent triplicates. The responses to the E₂₄ of the Biosurfactant produced by Paenibacillus dendritiformis were statistically analyzed by means of variance analysis (ANOVA), including Fisher's text and Student's t test, with a significant level (α) of 0.05. All statistical analyses were conducted using R programming[38–39].

2.12 DNA isolation

The purified 5 ml of overnight isolated Paenibacillus species culture was centrifuged at 10,000 rpm for 10 minutes. In the cell pellet, 875µl of Tris EDTA (ethylene-diamine-tetraacetic-acid) buffer was added to preserve the DNA from degradation. 5µl of Proteinase K and 100µl of 10% sodium dodecyl sulfate in lysis buffer were added to the extracted Paenibacillus cells. Further for 1hr solution was incubated at 37°C after the proper mixing. A specific ratio of 1 ml of phenol and trichloromethane was added in a vial and incubated at room temperature for 5 minutes. At 10,000 rpm, vials were centrifuged for 10 minutes. For collecting an adequate amount of supernatant, this process is repeated thrice. 100µl / 5M sodium acetate was added to the supernatant followed by gentle mixing. For DNA precipitation, 2 ml of isopropanol were added slowly to the vial walls (dropwise) until DNA gets precipitated at 5000 rpm for vials were again centrifuged for 10 minutes. After removing the supernatant, 70% ethanol was added, and at 5000 rpm, it is centrifuged for 10 minutes. It is air-dried, and TE buffer is used for storage. The extracted DNA was run on 1% agarose gel to check band's purity and integrity. The extracted DNA was amplified using PCR[40–43].

2.13 16S rRNA Sequencing

Amplified products were isolated from 1% agarose gels in 1x TAE (Tris-acetate-EDTA) buffer at 10 Vmm-1 for 90 minutes and examined with a UV transilluminator and recorded with Bio-Rad’s Gel Doc XR. The amplified by-product was elutriated using the thermofisher’s Gene JET PCR Purification and Gel extraction kit as instructed in the manufacturer's guidelines. Sanger dideoxy sequencing technique by ABI (Applied Biosystems) was used to sequenced elutriated PCR by-product. For the assembly of both the forward as well as reverse trace files acquired from the sequencing DNA, the DNA Baser tool was utilized [44–47]. Clean traces (fragments) were determined in both the assemble (forward and reverse). Furthermore, for the elaborated bioinformatics analysis, the assembled sequences were stored in FASTA file format [48–52].

2.14 Phylogenetic tree construction

The sequence obtained from the Sanger method was further analyzed using EMBOSS software. The sequence further performed a Blastn against 16S ribosomal rRNA sequence (Bacteria and Archaea) database using a cut-off value of > 95% [44][50–51]. All the similar sequence was further downloaded from GenBank, and the phylogenetic tree was constructed to identify the bacteria’s genus and species. Also, to study the evolutionary significance of the query bacteria and similar bacteria obtained from the GenBank. The evolutionary antiquity was rooted in employing the (NJ)Neighbor-Joining algorithm [52–54]. The most favorable tree amidst the sum of branches shows the length = 71.76000000. The tree was drawn to calibrate the evolutionary distances in the same unit concerning the branch's length toward determining the phylogenetic tree[55–56]. The evolutionary gaps have been measured applying the various methods [51] and were expressed in the number of base differences per sequence unit. The overall analysis consists of twenty nucleotide sequences. Codon was arranged in the order, 1st codon + 2nd codon + 3rd codon + Noncoding respectively. All positions encompassed gaps and lacking data were eliminated. A total of 1319 positions were present in the final dataset. Evolutionary studies were overseen using MEGA X [50–51].

2.15 Elucidation of rRNA Secondary Structure

The thermodynamics of the RNA structure has been examined successfully through the approaches like absorbance micro-calorimetry and melting curves that entail isothermal titration calorimetry and differential scanning calorimetry. The RNA 3-D structure estimates to have a confounding number of shapes which demonstrates that predicting native structure in the equilibrium to be a difficult task [51]. Also, there are various distinct motifs in RNA structure, and the quantity of feasible sequence consolidation for utmost motifs is massive. However, by the tenets of thermodynamics, it is possible to predict the stable RNA structure. The main objective of thermodynamic principles is to provide a core establishment to predict and foresee the rRNA structure from the sequence. Despite this, it is unlikely to create the models of all the established thermodynamic specifications for all inclined helices with Watson-Crick base pairs. As consequence, potent and robust models have been created to foresee the thermodynamics of helix development from a restricted set of estimated measurements. A few of the prominent endeavors include the neighbor model foreseeing strong stabilities of RNA duplexes with Watson-Crick pairs by Borer et al. proposed algorithms. Likewise, a substitute investigation for thermodynamic with thermodynamic properties has been proposed by Gray et al. [50–51]. However, in another methodology, thermodynamic principles and phylogenetic information have been unified for nearby prediction of RNA duplex formation using its structural properties that encompass the identification of RNA spectroscopic properties.

3.1. Isolation and biochemical characterization

A total of 23 different species were found in the collected samples. On screening the cultures in the crude oil, four organisms were found to survive on the MSM plates. These were pure cultured and characterized using biochemical tests. The screened microorganisms belong to 4 different species of bacteria, which includes Bacillus tequilensis species (Isolate 1–4.32x108 CFU/ml), Bacillus subtilis species (Isolate 2–4.07x108 CFU/ml), Paenibacillus species (Isolate 3–4.28x108CFU/ml), and Microbacterium species (Isolate 4–4.16x108 CFU/ml) illustrated in Table 1 that were identified and distinguished employing Bergey’s protocol as a source of reference. Bacillus tequilensis is biochemically analogous to Bacillus subtilis; however, it can be discriminated by positive production of 3 rhamnose compounds, namely ornithine decarboxylase, lysine decarboxylase, and arginine dihydrolase, as well as acid production. The biochemical test results for each isolate were verified with the literature to identify the genus. The detailed list has been mentioned in Table 1. The gram staining and bacterial colonies of Isolate 3 have been depicted in Fig. 1.

Table 1

Biochemical characteristics of the four isolates
Biochemical characterization
S.No	Parameters	Microorganisms
S.No	Parameters	Isolate 1 (Bacillus subtilis)	Isolate 2 (Microbacterium)	Isolate 3 (Bacillus tequilensis)	Isolate 4 (Paenibacillus)
1	Colonial Characters	Opaque, Off-white colonies, Large, Circular, Smooth, Uneven, Slightly Raised.	Yellow colonies, translucent, smooth, Medium, circular, slightly raised.	Opaque, Uneven, Large, Circular, Smooth, yellowish colonies, Slightly Raised.	Thin, spreading colonies, Circular Large,, smooth, Opaque, flat.
2	Microscopic characters	Rod-shaped	Rod-shaped	Rod-shaped	Rod-shaped
3	Gram's Staining	Gram Positive	Gram Positive	Gram Positive	Gram positive
4	Pigmentation	Pigmentation was off - white	Pigmentation was Yellow	pigmentation was Yellowish	Pigmentation of off - white
5	Sucrose Fermentation	+ve	+ve	+ve	+ve
6	Casein Hydrolysis	+ve	+ve	+ve	-ve
7	Lipid Hydrolysis	+ve	+ve	+ve	+ve
8	Citrate Utilization	+ve	+ve	+ve	+ve
9	Starch Hydrolysis	+ve	+ve	+ve	+ve
10	Oxidase Activity	-ve	-ve	+ve	-ve
11	Methyl Red test	+ve	+ve	+ve	+ve
12	Lactose Fermentation	-ve	-ve	+ve	-ve
13	Glucose fermentation	+ve	+ve	+ve	+ve
14	Voges Proskeur	+ve	-ve	+ve	-ve
15	Motility	+ve	-ve	+ve	+ve
16	Indole Production	-ve	-ve	+ve	-ve
17	Gas Production from Glucose	+ve	-ve	+ve	+ve
18	Catalase Activity	+ve	+ve	+ve	+ve
19	Nitrate Reduction	+ve	-ve	+ve	+ve
20	Gelatin Hydrolysis	+ve	+ve	+ve	+ve
21	H₂S Production	-ve	-ve	-ve	-ve
22	Spores	+ve	-ve	+ve	+ve
23	Urease Activity	-ve	-ve	-ve	-ve

3.2. Screening for biosurfactant production

The biosurfactant production was confirmed by performing various assays on the four isolates. The section discusses the respective efficiencies for each of the screened isolates.

3.2.1. BATH assay

The cell hydrophobicity was estimated by the BATH assay. Table 2 shows the affinity of the positive strains of bacterial cells towards the hydrophobic substrate. Isolate 3 (87.23 ± 0.71) shows the highest cell adherence property, whereas Isolate 4 (62.54 ± 1.42) was observed with the least cell adherence. Furthermore, Isolate 1 shows 84.77 ± 0.56 adherence, whereas Isolate 2 (79.46 ± 0.23) shows cell adherence. Positive hydrophobicity of the cells is proclaimed as a signal for the production of biosurfactant. The visualization of bacterial cells adhered to crude oil confirmed the affinity of cells in the crude oil droplet’s vicinity.Table 2 discusses the BATH results for each isolate.

3.2.2. Hydrocarbon overlay agar plate

The HOA plate method identifies hydrocarbon elastic Paenibacillus species as well as shows the hydrocarbon-degrading activity of the isolated bacteria. In Table 2, Quantitative assessment of the bioemulsifiers were demonstrating the zone of clearance that Isolate 3 gave 1.7 mm, 1.6 mm, 1.5 mm, and 1.4 mm with benzene plated medium, kerosene, toluene, and hexadecane, respectively. Isolate 1 demonstrated the development across the hydrocarbon plated media with 1.4 mm diameter, 1.5 mm diameter, 1.3 mm diameter, and 0.2 mm diameter of clearance zone for toluene, benzene, hexadecane, and kerosene plated media, respectively. Isolate 3 and isolate 1 gave negative outcomes with benzene and kerosene but, however, gave great outcomes with hexadecane(Isolate 3 was 1.3mm diameter, Isolate 1 was 1.4mm diameter) and toluene(Isolate 3 was 0.6mm diameter, Isolate 1 was 1.5mm diameter). Isolate 2 was 1.3 mm diameter, 1.5 mm diameter, 1.4 mm diameter, and 0.3 mm diameter zone of clearance for toluene, benzene, hexadecane and kerosene plated media. Figure 2 shows the clearance zone observed for hexadecane in the case of Isolate 3.

Table 2

BATH assay and Hydrocarbon overlay agar plate
Microorganism	BATH assay^a	Hydrocarbon overlay agar plate^b
Microorganism	BATH assay^a	Kerosene	Hexadecane	Benzene	Toluene
Isolate 1	++	Nil	++	Nil	+
Isolate 2	++	Nil	++	Nil	++
Isolate 3	++	++	++	++	++
Isolate 4	++	+	++	++	++
BATH assay^a: ‘+++’ - cell adhesion > 90%, ‘++’ − 60 to 89% cell adhesion, ’+’ – 40 to 59% cell adhesion.

Hydrocarbon overlay agar plate^b

‘+’ - clearance zone of 0.1-1 mm, ‘++’ - clearance zone of 1.1 to 2 mm, ‘+++’ - clearance zone of 2.1 to 3.5 mm.

3.2.3. Drop collapse assay

Drop collapse assay is a hypersensitive test and can give a result with even a very small measure of biosurfactant produced. A few strains give a positive outcome with BATH assay; however, the strains test negative for drop collapse assay as their cultures with high cell hydrophobicity were act as biosurfactants themselves but were unable to produce the biosurfactant extracellularly. The analysis was performed in the duplicate set. And for conducting the analysis, 10µl of surfactant solution, and the cell-free culture broth were used. The positive outcomes with a flat droplet, as confirmed by the oil spread assay were shown by all microorganisms' strains. The drop of Isolate 1, Isolate 2, Isolate 3, and Isolate 4 collapsed in 1 min 3 sec, 56 sec, 1 min 6 sec, and 1 min 52 sec, respectively (Table 3).In order to assure the production of biosurfactants, oil spreading and surface tension experiments were performed on the microorganism’s cell-free culture broths. Figure 3 shows the drop collapse test for the four isolates.

3.2.4. Oil spreading assay

The organisms with a positive drop collapse assay were found to give positive results for the oil spreading assay. It is observed in the present analysis that the surface-active compound in the Paenibacillus isolate solution is directly proportional to the oil displacement area. Furthermore, it is a qualitative study to check the presence of surfactants. Isolate 1, Isolate 2, Isolate 3, and Isolate 4 show the clearance zone of 1.4mm, 2.4 mm, 2.1 mm, and 1.8 mm. Figure 4 depicts the oil spread assay for Isolate 3.

3.2.5. Surface tension measurement

Surface tension was measured in the cell-free culture broth, and it showed a reduction in surface tension. A direct correlation was observed between drop collapse, oil spreading, and surface tension assays. Microorganisms with slight activity in any one of the assays were active in the other two. Isolate1 to Isolate 4 gave positive results with a reduction in surface tension to 41mN/m, 38 mN/m, 36mN/m, and 42mN/m surface tension, respectively, given in Table 3.

Table 3

Oil spreading assay, Drop collapse assay, and Surface tension measurement
Microorganism	Drop collapse assay^b	Oil spreading assay^a	Surface tension measurement^d
Isolate 3	++	+	++
Isolate 1	+++	++	+++
Isolate 4	++	++	+++
Isolate 3	++	++	++

Surface tension^d

‘+++’- indicates surface tension which is less than 40 mN/m, ‘++’- indicates surface tension between 40 to 50mN/m,’+’- indicates surface tension between 51 to 70mN/m.

Oil spreading assay^a

‘+’ - indicates a clear zone of oil spread with a zone of 0.5–1.5 mm diameter, ‘++’ – indicates a clear zone of oil spread with a zone of 1.6 to 2.5 mm diameter, ‘+++’ – indicates a clear zone of oil spread with a zone of 2.6 to 3.5 mm diameter.

Drop collapse assay^b

‘+++’- indicates adrop collapse within 1 minute, ‘++’- indicates a drop collapse after 1minute and ‘+’ – indicates a drop collapse after 3 minutes of biosurfactant addition.

3.3. Optimization of Biosurfactant production for Paenibacillus (Isolate 3)

The pH was optimized based on the E24 index. At pH 7.0, the E24 value was 75% that decreased gradually at pH 8.0, showing a substantial effect (Fig. 5(a)). Similarly, the optimum temperature was found to be35°C (E24: 73.37%) (Fig. 5(b)). Isolate 3 is mesophilic and exhibits effective production at moderate temperature. Starch was settled up as the most favorable (E24: 82%) amidst the 8 different carbon sources, followed by sucrose (E24: 72%) (Fig. 5(c)). Subsequently, yeast extract exhibits the maximal E24 value (82%) amidst 8 different nitrogen sources followed by Peptone (E24: 60%) (Fig. 5(d)). For the production medium preparation, all optimized condition plays an essential role in increasing the yield. On varying the carbon and nitrogen sources from 1–5%, 2% of the starch (E24:84%) (Fig. 5 (e)) as well as 3% of the yeast extract (E24: 83%) (Fig. 5 (f)) gave maximum production efficiency.

3.4. Extraction of biosurfactant and dry weight

The culture inoculated in a mineral salt medium with oil was centrifuged to collect the supernatant. The collected supernatant was mixed with chloroform and methanol in the aforementioned ratio. White sediment was retained in an empty Petri plate and was weighed as mentioned in Table 4. The maximum amount of biosurfactant was produced by Paenibacillus (Isolate 3), amounting to 0.426 g per 100 mL of medium.

Table 4

Dry weight of biosurfactant produced by the organisms
Microorganism	Empty plate weight (g)	Biosurfactant containing plate weight (g)	Dry weight of biosurfactant (g/100ml)
Paenibacillus(Isolate 3)	23.785	24.211	0.426

3.5 Thin layer Chromatography

Paenibacillus dendritiformis producing biosurfactant characterization was executed using Thin Layer Chromatography. TLC plate is exposed to different reagents after the solvent completely traveled until the top of the TLC plate and affirmed unique characteristics of the spots. The color of the developed spot depends on the reaction between the developing reagent and the sample compound. The identified Rf value for the appeared spot on the TLC plate is 0.72 indicates that the compound is non-polar. Also, the resulting Rf value was nearby to the Rf values of lipopeptide previously reported by researchers for the lipopeptides produced by Paenibacillus sp. The yellow spot in the iodine vapour indicates the organic compound's presence and the lipid moiety in the structure (Fig. 6). In the present analysis, we found the purple spot on treatment with Ninhydrin reagent, which indicates the peptides group's presence in the present organic lipid compound, whereas, the absence of a colored spot on treatment with Orcinol reagent assures the absence of carbohydrate compounds within the structure. Therefore, considering the entire observations ensure the presence of lipopeptide residues in the current structure of biosurfactant originated from Paenibacillus dendritiformis.

3.6 Fourier Transform Infrared Spectroscopy

The absorbance intensity will correlate proportionally to the quantity of functionality present in the activated TLC-purified biosurfactant isolate of Paenibacillus species. FTIR spectral peaks observed at 2,943, 2,911, 2,862, and 1,454 cm − 1 wavenumbers confirm the –C–H stretching (− CH3, –CH2) of the long hydrophobic R chain of the lipid as the similar stretching pattern for –C–H of lipid in observed in several previously completed studies of Bacillus species producing biosurfactant (Fig. 7). C = O bending of esters was indicated by the peaks at 1,739 and 1,742 cm − 1 and C–O by 1,090 cm − 1. Besides, 977–840 cm − 1 wave number peaks indicate the presence of C = C in the fatty acid chain of the lipid fraction of the biosurfactant. Furthermore, the presence of amide and hydroxyl groups of protein in the structure was identified. Furthermore, the alimentation of the amide bond, i.e., –C = O (1630 cm − 1), the carbonyl group (C = O) of amide (1,672 cm − 1), and the N–H bending of primary or secondary amides (1,630 cm − 1) illustrate the presence of the peptide fragments of the biosurfactant in the structure. The obtained peaks of biosurfactant indicate that lipopeptide biosurfactants were produced by P. dendritiformis; in a fatty acid chain, we found the presence of a double bond of the lipopeptide.

3.7 Stability test of biosurfactant

Optimization of biosurfactant production for Paenibacillus (Isolate 3) was carried out using RSM (response surface methodology) based on the Box–Behnken design of experiments. The R package RSM was used to carry out the analysis. The three factors considered in the analysis were pH (ph), temperature (temp), and salinity (sal). The three levels for each factor included in the design were pH 5, 7, and 10, temperature 30, 40, and 60, and salinity 4%, 6%, and 8%, encoded as -1, 0, and 1 respectively in the design. The experiment was conducted as per the Box–Behnken design and the E24 index was measured for each combination of the parameters. Table 5 shows the E24 values obtained from the design experiment.

Table 5

Results of Box-Behnken experimental design.
Experiment number	pH	Temp(°C)	Salinity (%)	E24 (%)
1	-1	-1	0	69.58858859
2	0	0	0	42.78678679
3	0	-1	1	32.57657658
4	1	0	1	52.53753754
5	1	0	-1	26.5015015
6	-1	0	-1	71.57957958
7	0	0	0	40.08108108
8	0	1	-1	49.32132132
9	1	-1	0	24.66366366
10	0	0	0	44.52252252
11	-1	1	0	55.3963964
12	0	-1	-1	73.36636637
13	-1	0	1	40.13213213
14	0	0	0	34.92492492
15	1	1	0	56.87687688
16	0	1	1	65.91291291

Experimental data was used to fit a linear model with a response-surface component using the R package's RSM function. While fitting the model, first-order, two-way interactions and pure quadratic terms were included. The regression equation obtained is shown below. In the equation, the first-order terms are pH, temperature (temp), and salinity (sal), while the two-way terms are ph*temp, temp*sal, and ph*sal, and the quadratic terms are ph^2 (ph square), temp^2 (temp square) and sal^2 (sal square).

E24 = 40.58–9.51pH + 3.41temp − 3.70sal + 11.60ph:temp + 14.37ph:sal + 14.35temp:sal + 1.72ph^2 + 9.33temp^2 + 5.39sal^2

The significance of the coefficients of the model is shown in Table 6. The *** mark in the pval column indicates that the p-value is < 0.001 while ** indicates p-value < 0.01 and * indicates p-value < 0.05, indicating statistical significance of the corresponding parameter (Table 6). The intercept, ph, ph*temp, ph*sal, temp*sal, temp^2 terms were statistically significant, and therefore they influence the E24 values. The E24 values varied from 24.6–73.3%, and the highest E24 was observed for pH 7, temperature 30°C, and 4% salinity (Table 7). Overall the model was found to be statistically significant (p-value 0.0008478) with F value as 19.82 (9 and 6 degrees of freedom), adjusted R-squared value as 0.91.

Table 6

Statistical significance of model parameters
Estimate or Coefficient	Standard error	Student t-test test statistics	pval
(Intercept)	40.57882883	2.243416351	1.84E-06***
ph	-9.51463964	1.586334915	0.00097***
temp	3.414039039	1.586334915	0.07488
sal	-3.701201201	1.586334915	0.05839
ph:temp	11.60135135	2.243416351	0.00207**
ph:sal	14.37087087	2.243416351	0.00068***
temp:sal	14.34534535	2.243416351	0.00069***
ph^2	1.722972973	2.243416351	0.47161
temp^2	9.32957958	2.243416351	0.00595**
sal^2	5.385885886	2.243416351	0.05324

Table 7

The results of ANOVA and lack-of-fit test of the model
Term	Df	Sum Sq	Mean Sq	F value	Pr(> F)
First order terms	3	927.0633629	309.021121	15.35000108	0.0032**
Two way interaction terms	3	2187.608863	729.2029545	36.22168641	0.0003***
Pure quadratic terms	3	476.0698311	158.6899437	7.882602973	0.0166*
Lack of fit	3	68.14782575	22.71594192	1.29454793	0.4185
Residuals	6	120.7900062	20.1316677
Pure error	3	52.64218047	17.54739349

The E24 values obtained from the design experiment are shown in two-dimensional contour plots. The x and y-axis of each contour plot indicate the parameter considered while keeping the third remaining parameter constant. The top left contour plot represents the variation in the E24 value as a pH and temperature function. In contrast, the top-right plot indicates the variation in E24 as a function of pH and salinity. The bottom contour plot indicates the variation in E24 values as a function of temp and salinity. The colour scales from green to yellow, where green indicates low E24 values while yellow indicates high E24 values. In the contour plot, the line with E24 values is also shown in Fig. 8.

3.8 DNA isolation, amplification and phylogenetic assessment

The phylogeny assessment of Isolate 3 was performed. DNA was isolated and amplified using PCR. After the amplification, the DNA was quantified using a nanodrop and qubit fluorometer. Qubit fluorometer estimated DNA yield as 1281.6 µgl − 1and had optimal purity. Thus, the obtained amplified DNA was further used for phylogenetic assessment [30–33]. 16S rRNA sequence was 1483 base pairs long and was single-stranded bearing a molecular weight of 450176.00 Daltons. GC% and AT% was 54.96% and 45.04%, respectively. Comparatively, G was the highest, and T was the lowest. The sequence was further analyzed by BLASTn against 16S ribosomal RNA sequences (16S ribosomal Bacteria and Archaea) database using a cut-off value of > 95%. The first hit shows that the query sequence matches with Paenibacillus dendritiformis strain T168 16S ribosomal RNA gene, partial sequence by 98%, whereas 4 hits were seen in the next go that showed similarity with various strains of Paenibacillus thiaminolyticus 16S ribosomal RNA gene, partial sequence. All the similar sequences were further downloaded from GenBank, and a phylogenetic tree was constructed using the neighbor-joining algorithm in Mega software. The phylogenetic tree has been depicted in Fig. 9.

In contemporary research, the secondary structure of 16S rRNA of Paenibacillus dendritiformis strain ANSKLAB02 has demonstrated helical regions with the interior, hairpin, bulge and multi-branched loops that may bind to23S rRNA. The free energy (ΔG) of the rRNA secondary structure for Paenibacillus dendritiformis strain ANSKLAB02was calculated to be − 131.00 kcal mol − 1 been elucidated using UNAFOLD software. The structure has been depicted in Fig. 10. The thermodynamics result from each base of the Paenibacillus dendritiformis strain ANSKLAB02dataset shows the average energy of external closing pair helix, stack, multi-loop, bulge loop, and hairpin loop, as,-299.80 kcal/mol, − 2.03 kcal/mol, 0.11 kcal/mol,0.210 kcal/mol and − 1.62 kcal/mol, respectively. The closing pair and interior loop had ΔG value = − 2.11 kcal/mol. Further, the two TNA structures entropy was estimated using the RNA fold server and is depicted as a hill plot in Fig. 11.

Petroleum pollution has been a threat to the environment that arises from various natural and anthropogenic sources. These complex toxic compounds have to degrade so that the by-products or the remnants are also intoxicated. The present study identifies the problem and introduces marine bacteria producing biosurfactant that was isolated from brackish water. The bacterial biosurfactant increases the surface area of hydrophobic water-insoluble substrates and hence, increases the solubility and bioavailability of hydrocarbons for their bioremediation. These can stimulate the growth of oil-degrading bacteria, thus, improving their ability to utilize hydrocarbons. The purified materials can be implemented in bioremediation processes or can even act as bioemulsifier-overproduced by the bacteria.

Further, studies need to execute on the genetic deviation or alteration of an expression vector, where the newly introduced Paenibacillus sp. ought to be promiscuous for the cause. In the current study, four isolates from coastal water surface extracellularly produced the biosurfactant. Different assays and tests evaluated all bacterial isolates to ascertain their capability to produce biosurfactants. The isolate with maximum biosurfactant yield belonging to Paenibacillus sp. (Isolate 3) was screened further by performing various assays. The isolate was biochemically characterized, and its phylogeny was estimated. The isolated Paenibacillus dendritiformis strain (ANSKLAB02) was grown on MSM medium using crude oil as the Carbon source to produce a biosurfactant producing lipopeptide, which has high stability at a wide range of pH levels, high temperature, and salinity. This bacterium had the most increased emulsification activity (E24 = 73.37%) in crude oil and was found to decrease the surface tension to 36mN/m, indicating its oil-reduction capacity. The probability of reducing the surface tension ultimately depends on the biosurfactant's molecular alignment from a broader perspective. Based on this study, RSM with Box–Behnken experimental design could be used as an effective tool for biosurfactant stability test analysis for bioremediation applications. The selected bacterial strain was modified by optimizing the various essential environmental parameters required for its biosurfactant production. The best outcome was attained in the medium at pH 7.0, 30°C temperature, 4% salinity (NaCl) with starch (2%), and yeast extract (3%). These enhanced settings are used to determine the dry weight of the biosurfactant produced by the microorganism. The novel strain of Paenibacillus species had 0.427g of biosurfactant in 100mL of the medium. The data generated from the biosurfactant stability experiments were used to fit a regression model using the parameters such as ph, temp, and salinity to predict the E24 index. R-squared value 0.91obtain from the ANOVA model explains that the regression model we fit was significant, explaining 91% of the data set, and the model p-value obtained was < 0.05, which is statistically significant. Not only the p-value but the individual coefficients of the data were also found to be significant. The most significant parameters are first-order, two-way interactions, and pure quadratic terms such as ph, ph*temp, ph*sal, temp*sal, temp^2, respectively, are significantly associated with the E24 index. Therefore the statistical model obtained in the present research can be used to predict the E24 index. The isolated Paenibacillus strain was found quite promiscuous. However, further investigation is required to increase the efficacy of lipopeptide biosurfactant activity.

Acknowledgements

1. The authors are thankful to LeGene Biosciences Pvt for 16S rRNA sequencing of the bacterium.

2. SKS thank Department of Biotechnology (DBT), New Delhi (No. BT/PR8138/BID/7/458/2013, dated 23rd May, 2013), DST-PURSE 2nd Phase Programme Order No. SR/PURSE Phase 2/38 (G dated 21.02.2017 and FIST (SR/FST/LSI - 667/2016), MHRD RUSA - Phase 2.0 (grant sanctioned vide letter No. F. 24-51 / 2014 - U, Policy (TNMulti-Gen), Dept. of Edn. Govt. of India, Dt. 09.10.2018) for providing the financial assistance.

3. SKS thankfully acknowledges the Tamil Nadu State Council for Higher Education (TANSCHE) for the research grant (Au/S.o. (P&D): TANSCHE Projects: 117/2021).

Competing interests

The authors declare that they have no competing interests.

Author's Contribution

AN involved in Conceptualization, Investigation, Methodology, Project administration, Supervision, Writing – review & editing. RK involved in Data curation, Formal analysis, Validation, Visualization. SKS involved in Investigation, Supervision, Writing – review & editing the MS.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Funding

Not applicable

Souza EC, Vessoni-Penna TC, de Oliveira S, R. P (2014) Biosurfactant-enhanced hydrocarbon bioremediation: An overview, vol 89. International biodeterioration & biodegradation, pp 88–94
Bezza FA, Chirwa EMN (2017) Pyrene biodegradation enhancement potential of lipopeptide biosurfactant produced by Paenibacillus dendritiformis CN5 strain. J Hazard Mater 321:218–227
Kumar A, Devi S, Singh D (2018) Significance and approaches of microbial bioremediation in sustainable development. Microbial Bioprospecting for Sustainable Development. Springer, Singapore, pp 93–114
Banat IM, Franzetti A, Gandolfi I, Bestetti G, Martinotti MG, Fracchia L, Smyth TJ, Marchant R (2010) Microbial biosurfactant production, applications and future potential. Appl Microbiol Biotechnol 87(2):427–444 [PMID: 20424836]
Cooper DG (1986) Biosurfactant Microbiol Sci 3(5):145–149
Klekner V, Kosaric N (1993) Biosurfactant for cosmetics.Surfactant science series,373–373
Moldes AB, Paradelo R, Rubinos D, Devesa-Rey R, Cruz JM, Barral MT (2011) Ex situ treatment of hydrocarbon-contaminated soil using biosurfactants from Lactobacillus pentosus. J Agric Food Chem 59(17):9443–9447
Muthusamy K, Gopalakrishnan S, Ravi TK, Sivachidambaram P (2008) Biosurfactant: properties, commercial production and application.Current science,736–747
Nayarisseri A, Singh P, Singh SK (2018) Screening, isolation and characterization of bio-surfactant producing Bacillus subtilis strain ANSKLAB03. Bioinformation 14(6):304–314
Cooper DG, Zajic JE (1980) Surface-active compounds from microorganisms. Adv Appl Microbiol 26(229):53
Banat IM, Franzetti A, Gandolfi I, Bestetti G, Martinotti MG, Fracchia L, Smyth TJ, Marchant R (2010) Microbial biosurfactant production, applications and future potential. Appl Microbiol Biotechnol 87(2):427–444 [PMID: 20424836]
Cortés-Camargo S, Pérez-Rodríguez N, de Souza Oliveira RP, Huerta BEB, Domínguez JM (2016) Production of biosurfactant from vine-trimming shoots using the halotolerant strain Bacillus tequilensis ZSB10. Ind Crops Prod 79:258–266
Cameotra SS, Makkar RS (2010) Biosurfactant-enhanced bioremediation of hydrophobic pollutants. Pure Appl Chem 82(1):97–116
Karanth NGK, Deo PG, Veenanadig NK (1999) Microbial production of biosurfactant and their importance.Current Science,116–126
Rahman PK, Gakpe E (2008) Production, characterisation and applications of biosurfactant-Review. Biotechnology
Purwasena, I. A., Astuti, D. I., Syukron, M., Amaniyah, M., & Sugai, Y. (2019). Stability test of biosurfactant produced by Bacillus licheniformis DS1 using experimental design and its application for MEOR. Journal of Petroleum Science and Engineering, 183, 106383
Carrillo PG, Mardaraz C, Pitta-Alvarez SI, Giulietti AM (1996) Isolation and selection of biosurfactant-producing bacteria. World J Microbiol Biotechnol 12(1):82–84
Morikawa M, Hirata Y, Imanaka T (2000) A study on the structure–function relationship of lipopeptide biosurfactant. Biochimicaet BiophysicaActa (BBA)-Molecular and Cell Biology of Lipids. 1488:211–218 [PMID: 11082531]. 3
Batista SB, Mounteer AH, Amorim FR, Totola MR (2006) Isolation and characterization of biosurfactant/bioemulsifier-producing bacteria from petroleum contaminated sites. Bioresour Technol 97(6):868–875 [PMID: 15951168]
Bodour AA, Miller-Maier RM (1998) Application of a modified drop-collapse technique for surfactant quantitation and screening of biosurfactant-producing microorganisms. J Microbiol Methods 32(3):273–280
Youssef NH, Duncan KE, Nagle DP, Savage KN, Knapp RM, McInerney MJ (2004) Comparison of methods to detect biosurfactant production by diverse microorganisms. J Microbiol Methods 56(3):339–347 [PMID: 14967225]
Rosenberg M, Gutnick D, Rosenberg E (1980) Adherence of bacteria to hydrocarbons: a simple method for measuring cell-surface hydrophobicity. FEMS Microbiol Lett 9(1):29–33
Betts RP, Bankes P, Banks JG (1989) Rapid enumeration of viable micro-organisms by staining and direct microscopy. Lett Appl Microbiol 9(5):199–202
Bodour AA, Guerrero-Barajas C, Jiorle BV, Malcomson ME, Paull AK, Somogyi A, Trinh LN, Bates RB, Maier RM (2004) Structure and characterization of flavolipids, a novel class of biosurfactant produced by Flavobacterium sp. strain MTN11. Appl Environ Microbiol 70(1):114–120 [PMID: 14711632]
Parthipan P, Preetham E, Machuca LL, Rahman PK, Murugan K, Rajasekar A (2017) Biosurfactant and degradative enzymes mediated crude oil degradation by bacterium Bacillus subtilis A1. Front Microbiol 8:193 [28232826]
Santos DK, Brandão YB, Rufino RD, Luna JM, Salgueiro AA, Santos VA, Sarubbo LA (2014) Optimization of cultural conditions for biosurfactant production from Candida lipolytica. Biocatal Agric Biotechnol 3(3):48–57
Anandaraj B, Thivakaran P (2010) Isolation and production of biosurfactant producing organism from oil spilled soil. J Biosci Tech 1(3):120–126
Patowary K, Patowary R, Kalita MC, Deka S (2017) Characterization of biosurfactant produced during degradation of hydrocarbons using crude oil as sole source of carbon. Front Microbiol 8:279
Md Badrul Hisham NH, Ibrahim MF, Ramli N, Abd-Aziz S (2019) Production of biosurfactant produced from used cooking oil by Bacillus sp. HIP3 for heavy metals removal. Molecules 24(14):2617
Janek T, Łukaszewicz M, Rezanka T, Krasowska A (2010) Isolation and characterization of two new lipopeptide biosurfactant produced by Pseudomonas fluorescens BD5 isolated from water from the Arctic Archipelago of Svalbard. Bioresour Technol 101(15):6118–6123
Chen H, Wang L, Su CX, Gong GH, Wang P, Yu ZL (2008) Isolation and characterization of lipopeptide antibiotics produced by Bacillus subtilis. Lett Appl Microbiol 47(3):180–186
Pecci Y, Rivardo F, Martinotti MG, Allegrone G (2010) LC/ESI-MS/MS characterisation of lipopeptide biosurfactant produced by the Bacillus licheniformis V9T14 strain. J Mass Spectrom 45(7):772–778
Das K, Mukherjee AK (2007) Comparison of lipopeptide biosurfactant production by Bacillus subtilis strains in submerged and solid state fermentation systems using a cheap carbon source: some industrial applications of biosurfactant. Process Biochem 42(8):1191–1199
Silva EJ, Silva e, Rufino NMPR, Luna RD, Silva JM, Sarubbo LA (2014) Characterization of a biosurfactant produced by Pseudomonas cepacia CCT6659 in the presence of industrial wastes and its application in the biodegradation of hydrophobic compounds in soil. Colloids Surf B 117:36–41
Ferreira, S. C., Bruns, R. E., Ferreira, H. S., Matos, G. D., David, J. M., Brandão,G. C., … Dos Santos, W. N. L. (2007). Box-Behnken design: an alternative for the optimization of analytical methods. Analytica chimica acta, 597(2), 179–186
Roldán-Carrillo T, Martínez-García X, Zapata-Penasco I, Castorena-Cortés G, Reyes-Avila J, Mayol-Castillo M, Olguín-Lora P (2011) Evaluation of the effect of nutrient ratios on biosurfactant production by Serratia marcescens using a Box-Behnken design. Colloids Surf B 86(2):384–389
Ebadipour N, Lotfabad TB, Yaghmaei S, RoostaAzad R (2016) Optimization of low-cost biosurfactant production from agricultural residues through response surface methodology. Prep Biochem Biotechnol 46(1):30–38
Mnif I, Elleuch M, Chaabouni SE, Ghribi D (2013) Bacillus subtilis SPB1 biosurfactant: production optimization and insecticidal activity against the carob moth Ectomyelois ceratoniae. Crop Prot 50:66–72
Coutte F, Niehren J, Dhali D, John M, Versari C, Jacques P (2015) Modeling leucine's metabolic pathway and knockout prediction improving the production of surfactin, a biosurfactant from Bacillus subtilis. Biotechnol J 10(8):1216–1234
Fang Y, Xu M, Chen X, Sun G, Guo J, Wu W, Liu X (2015) Modified pretreatment method for total microbial DNA extraction from contaminated river sediment. Front Environ Sci Eng 9(3):444–452
King MD, McFarland AR (2012) Bioaerosol sampling with a wetted wall cyclone: cell culturability and DNA integrity of Escherichia coli bacteria. Aerosol Sci Technol 46(1):82–93
Knebelsberger T, Stöger I (2012) DNA extraction, preservation, and amplification. DNA Barcodes. Humana Press, Totowa, NJ, pp 311–338
Lin HH, Yin LJ, Jiang ST (2009) Expression and purification of Pseudomonas aeruginosa keratinase in Bacillus subtilis DB104 expression system. J Agric Food Chem 57(17):7779–7784
Jaiswal M, Parveda M, Amareshwari P, Bhadoriya SS, Rathore P, Yadav M, Nayarisseri A, Nair AS (2014) Identification and characterization of alkaline protease producing Bacillus firmus species EMBS023 by 16S rRNA gene sequencing. Interdisciplinary Sciences: Computational Life Sciences 6(4):271–278 [PMID: 25118655]
Nadh G, Raj Akare A, Sharma U, Yadav P, Bandaru P, Nayarisseri S, Nair S, A (2015) Identification of azo dye degrading Sphingomonas strain EMBS022 and EMBS023 using 16S rRNA gene sequencing. Curr Bioinform 10(5):599–605
Bhatia M, Girdhar A, Tiwari A, Nayarisseri A (2014) Implications of a novel Pseudomonas species on low density polyethylene biodegradation: an in vitro to in silico approach. SpringerPlus 3(1):497
Nayarisseri A, Suppahia A, Nadh AG, Nair AS (2015) Identification and characterization of a pesticide degrading Flavobacterium species EMBS0145 by 16S rRNA gene sequencing. Interdisciplinary Sciences: Computational Life Sciences 7(2):93–99
Amareshwari P, Bhatia M, Venkatesh K, Rani AR, Ravi GV, Bhakt P, Nair AS (2015) Isolation and characterization of a novel chlorpyrifos degrading flavobacterium species EMBS0145 by 16S rRNA gene sequencing. Interdisciplinary Sciences: Computational Life Sciences 7(1):1–6
Chandok H, Shah P, Akare UR, Hindala M, Bhadoriya SS, Ravi GV, Nayarisseri A (2015) Screening, isolation and identification of Probiotic producing lactobacillus acidophilus strains EMBS081 & EMBS082 by 16S rRNA gene sequencing. Interdisciplinary Sciences: Computational Life Sciences 7(3):242–248
Nayarisseri A, Singh P, Singh SK (2018) Screening, isolation and characterization of biosurfactant-producing Bacillus tequilensis strain ANSKLAB04 from brackish river water. Int J Environ Sci Technol 16(11):7103–7112
Nayarisseri A, Khandelwal R, Singh SK (2020) Identification and Characterization of Lipopeptide Biosurfactant Producing Microbacterium sp Isolated from Brackish River Water. Curr Top Med Chem 20(24):2221–2234
Pyde AN, Rao PN, Jain A, Soni D, Saket S, Ahmed S, Nayarisseri A (2013) Identification and characterization of foodborne pathogen Listeria monocytogenes strain Pyde1 and Pyde2 using 16S rRNA gene sequencing. J Pharm Res 6(7):736–741
Phanse N, Rathore P, Patel B, Nayarisseri A (2013) Characterization of an industrially important alkalophilic bacterium, Bacillus agaradhaerens strain nandiniphanse5. J Pharm Res 6(5):543–550
Nayarisseri A, Yadav M, Bhatia M, Pandey A, Elkunchwar A, Paul N, Kumar G (2013) Impact of Next-Generation Whole-Exome sequencing in molecular diagnostics. Drug Invention Today 5(4):327–334
Nayarisseri A, Hood EA (2018) Advancement in microbial cheminformatics. Curr Top Med Chem 18(29):2459–2461
Krishnan SN, Nayarisseri A, Rajamanickam U (2018) Identification and characterization of cresol degrading Pseudomonas monteilii strain SHY from Soil samples. Bioinformation 14(9):455–464

Download PDF

Version 2

posted

You are reading this older preprint version

Read the latest preprint version →

Screening and characterization of Lipopeptide Biosurfactant Producing Paenibacilus Dendritiformis and its applicability for enhanced oil recovery

Status:

Version 2

Abstract

Figures

1. Introduction

2. Materials And Method

2.1. Sample Collection

2.2. Isolation of Microbial Consortium

2.3. Screening of Biosurfactant producing Isolates

2.3.1. Oil spread assay

2.3.2. Drop collapse test

2.3.3. Hydrocarbon overlay agar

2.3.4. Bacterial adhesion to hydrocarbon (BATH) assay

2.3.5. Surface tension analysis

2.4. Biochemical Characterization

2.5. Optimization of Biosurfactant production by Paenibacillus(Isolate 3)

2.5.1. Effect of pH

2.5.2. Effect of Temperature

2.5.3. Effect of Carbon

2.5.4. Effect of Nitrogen

2.5.5. Effect of the Carbon and Nitrogen Concentration

2.5.6. Analysis for Optimization Conditions and Biosurfactant Extraction

2.6. Biosurfactant Extraction

2.7. Dry weight of biosurfactant

2.8 Biosurfactant Characterization

2.9 Fourier Transform Infrared Spectroscopy (FTIR)

2.10 Stability Test Calculation of Emulsification index (E24)

3. Results And Discussion

3.1. Isolation and biochemical characterization

3.2. Screening for biosurfactant production

3.2.1. BATH assay

3.2.2. Hydrocarbon overlay agar plate

3.2.3. Drop collapse assay

3.2.4. Oil spreading assay

3.2.5. Surface tension measurement

3.3. Optimization of Biosurfactant production for Paenibacillus (Isolate 3)

3.4. Extraction of biosurfactant and dry weight

3.5 Thin layer Chromatography

3.6 Fourier Transform Infrared Spectroscopy

3.7 Stability test of biosurfactant

3.8 DNA isolation, amplification and phylogenetic assessment

4. Conclusion

Declarations

References

Status:

Version 2

2.10 Stability Test Calculation of Emulsification index (E₂₄)