Bioremediation of phenolic compounds in contaminated soil using white rot fungusSupervisor - Submitted by-Dr. Anand Mohan Pritpal Singh Reg. no- 3440070045( Asst. professor ) Roll no- RB1R09A26Lovely Professional University Date- 20/05/2012

INTRODUCTIONBioremediation can be defined as any process that uses microorganisms or their enzymes to destroy or render harmful contaminants that are altering the environment.Both fungi and bacteria are capable of doing bioremediationIt can be used to degrade wide range of compounds like Poly aromatic hydrocarbons, chlorinated phenols, explosives, dyes, etc.

Mycoremediation Process of using fungi in order to degrade various harmful contaminants in environment Can be used for treatement of contaminated soils and industrial effluentsMost commonly used fungi are white rot fungus capable of degrading lignin (ligninolytic fungi) Eg. Phanerochaete chrysosporium , Trametes versicolor , Agaricus bisporus , etcLigninolytic enzymes of white rot fungus are extracellular and the use of these enzymes generally forms the basis of our bioremediation process

Literature review

S.NO.FINDINGSREFERENCES 1

2. Lignin is a three-dimensional, naturally occurring polymer and it constitutes one of the most structurally complex and therefore resistant materials to microbial degradation. The ability of white rot fungi to mineralize lignin is generally attributed to the secretion of extracellular ligninolytic enzymes, mostly laccase

The degradation of lignin and other recalcitrant compounds by basidiomycetes is mediated by the coordinated action of an enzymatic system .The expression of the enzymatic system involved in the degradation of xenobiotics has been shown to mainly depend on the culture conditions

Naresh Magan , Silvia Fragoeiro and Catarina Bastos . Mycobiology 38(4) : 238-248 (2010) The Korean Society of Mycology

Renata Yamanaka; Clarissa F. Soares; Dcio R. Matheusand and Ktia M.G. Machado(2008)

S.NO.FINDINGSREFERENCES 3.

4.

A main feature of laccase is its highly non-specific nature with regard to the breakdown of substrates. Many xenobiotics share at least one of many sub-structures (e.g.,functional groups) present in the lignin molecule. This explains the ability of white rot fungi to tolerate and degrade such a wide range of environmental organic pollutants

The key step in lignin degradation by laccase or the ligninolytic peroxidases involves the formation of free radical intermediates, which are formed when one electron is removed or added to the ground state of a chemical Naresh Magan , Silvia Fragoeiro and Catarina Bastos . Mycobiology 38(4) : 238-248 (2010) The Korean Society of Mycology

Reddy C.A. and Mathew, Z. 2001. Fungi in bioremediation. G. M. Gadd Cambridge, U.K.: CambridgeUniversity Press

S.NO.FINDINGSREFERENCES 5.

6.Laccases oxidize aromatic pollutants, such as phenols, in the presence of oxygen (1, 2, 8). In this reaction, the substrates are oxidized by one electron to generate the corresponding phenoxy radicals, which either polymerize to yield a phenolic polymer or are further oxidized by laccase to produce a quinone

The substrate nonspecificity of laccases has led to them being examined as agents for the biodegradation of xenobiotic compounds, and their ability to oxidize compounds such as chlorinated phenols and polyphenols as well as aromatic aminesMURALIKRISHNA CHIVUKULA AND V. RENGANATHAN(1995).

PATRICK J. COLLINS, MICHIEL J. J. KOTTERMAN, JIM A. FIELD AND ALAN D. W. DOBSON(1996)

S.NO.FINDINGSREFERENCE

7.

8. Chlorophenols constitute a significant category of pollutants and are major components of paper pulp bleach plant effluents and its nearby soils.

The large-scale use of chlorophenols has led to the contamination of terrestrial and aquatic ecosystems, resulting in the classification of chlorophenols as priority pollutants

White-rot species, particularly Phanerochaete chrysosporium, have been used for decontamination ofPCP-polluted soils and aqueous effluents.Khadar valli and Michael.H.GoldJournal of bacteriology, Jan. 1991, p. 345-352

Lamar, R.T. and Dietrich, D.M. (1990). Appl. Env. Microbiol., 56, 3093-3100

OBJECTIVECollection of white rot fungi from wood samples and purification of culture.Mass culture of white rot fungus on spawn for adjusting against different variable parameters.Optimization of ligninolytic activity for pH, temperature, time, carbon source, nitrogen source, and surfactants using one variable at a time approach. Response Surface Methodology Standardization for multiple parameters for phenol degradation and laccase activity optimization and checking the activity under real time environment.To reduce the toxicity level of soil by reducing 2-4- dichlorophenol concentration in soil using optimized conditions.

SIGNIFICANCESoil pollution is one of the major threats to environment and to biodiversity.Compounds causing pollution needs to be degraded or inactivated The use of bioremediation to remove pollutants is typically less expensive than the equivalent physical-chemical methods.Use of white rot fungus to degrade xenobiotics such as chlorophenols is an efficient method as these group of fungi can withstand extreme conditions and concentration of contaminants.

MATERIAL AND METHODS

FUNGUS SAMPLE :- White rot fungus samples were collected from various sources ( on trees and in soil)

2. CULTURING :- Potato Dextrose Agar (PDA) was used for culturing fungi. Sample of white rot fungus was cultured on PDA petri dishes and was incubated at 30C for 5 to 7 days. Sub culturing was performed after 8-10 days continuously until pure culture was obtained. Tetracycline (antibiotic) was used as an antibacterial agent.

3. SPAWN PREPARATION:- Boiled wheat (200g) was added with 1% (w/w) calcium carbonate and 2 % (w/w) calcium sulphate in a polyethene bag and autoclaved. Autoclaved spawn bags are inoculated with the pure culture with 5% w/w i.e. 10 g of inoculum in 200 g spawn bag and incubated at 30C for 12 to 15 days.

4. ENZYME ACTIVITY ASSAY :- Laccase enzyme assay was carried out using ABTS (2,2'-azino-bis 3-ethylbenzothiazoline-6-sulphonic acid) as a substrate.Stock solution of ABTS was prepared by adding 0.164g ABTS in 30 ml distilled water (10mM).Working solution was prepared by diluting 10 mM ABTS to 1mM ABTS with 0.1 M acetate buffer. Assay was carried out by mixing 1 ml of 1 mM ABTS with 50l of enzyme. Activity = 700* ( Ai A0 ) Inc. time(t)

5. OPTIMIZATION (OVAT) :- The conditions for the excess yield of laccase have to be optimized.One variable at a time approach was as first step for optimization. Each packet contained single variable with 10 g of wheat straw and 30 ml czapadox medium.Media constituents include KCl (Potassium chloride), MgSO4 ( Magnesium sulphate), NaNO3 ( Sodium nitrate ) and the variable selected.List of variables that have to be selected are enlisted in the table.

S. No. Variables Sets 1. Carbon SourceGlucose , Starch , Galactose , Cellulose , Dextrose , Lactose , Sucrose , Fructose , Control ( 0.6 g for each source ) 2. Nitrogen SourceUrea , Peptone , Yeast Extract , Ammonium chloride, Sodium nitrate , Control ( 0.6 g for each source) 3.MetalsNaCl , KCl , MgCl2, FeCl3, CaCl2 , CuSo4 , Control (0.15 g for each metal) 4. Temperature 27 C, 30 C, 32 C, 37 C 5. pH 4.0 , 4.5 , 5.0 , 5.5 , 6.0 , 6.5 , 7.5 , 8.0 , 8.5 , Control ( 7.0 )

6. PREPARATION OF SOIL SAMPLE :- Soil sample was collected and mixed with 2-4-DCP (200 mg/l) in ratio 1:1 i.e. 50 ml phenol solution (2mg 2-4 dichlorophenol in 1litre distilled water) in 50 g soil. Allowed the samples to stay for 48 hrs

7 RESPONSE SURFACE METHODOLOGY:-Response surface methodology (RSM) is a collection of mathematical and statistical techniques for empirical model building.The objective was to optimize a response (output variable) which is influenced by several independent variables (input variables)Box-Behnken taking glucose as a carbon source and Tween -80 as a surfactant along with pH, temperature, inoculum amount and incubation time was designed having 54 runs.

DESIGN SUMMARY(Design Expert 8.0.7.1)

BOX-BEHNKEN DESIGN RUNSAfter getting the design order, different run order experiments were performed to find out phenol degradation and laccase activitys experimental results.White rot fungus was grown in each packet containing wheat straw and czapexdox medium. 2-4-dichlorophenol (0.02%w/v) was added in czapexdox medium to check the degradation ability of white rot fungus during solid state fermentation.Each packet (run order) contained 10g wheat straw, 30 ml contaminated czapexdox medium and the corresponding variables from DOE.

Growth was observed in each packet with respect to the conditions. One set of control was kept without inoculum.White rot fungus growth observed

8. PHENOL DEGRADATION ANALYSIS:-Phenol degradation analysis was carried out using 4-aminoantipyrine method. Phenolic materials react with 4- amino antipyrine in the presence of potassium ferricyanide to form a stable antipyrine dye. Added 1ml of sample in 5 M NH4OH +25 M of 4 - aminoantipyrine and 1% potassium ferricyanide. Centrifuged at 2000 rpm for 2 minutes followed by measuring absorbance at 510 nm. Degradation (%) = 100 [Absorbance (control) - Absorbance (r.o.) ] Absorbance (control)

9. DEGRADATION OF 2-4-DCP:- Two approaches; Whole cell culture approach and Treatment with crude laccase were used for degradation of 2-4-DCP. Both approaches were followed using optimized conditions.In whole cell culture approach white rot fungus was grown on czapekdox media containing 2-4 dichlorophenol and wheat straw. 2-4- dichlorophenol containing water was extracted from phenol mixed soil. It was done by ultrasonication of soil samples followed by vortexing and centrifugation at 10000 rpm for 10 minutes. Water collected from phenol containing soil was subjected to biological treatment with white rot fungus

Crude laccase treatment approach involves direct treatment of phenol contaminated water extracted from contaminated soil with crude laccase enzymeCrude laccase was the supernatant left after centrifugation of cell extract of white rot fungus grown on czapekdox media and wheat straw. Conditions optimized for obtaining maximum laccase activity using response surface methodology were used to grow white rot fungus.

pHTempInoculum AmountCarbon SourceSurfactantI.P.6.4300C10.002.00% (w/v)0.22% (w/v)27

RESULTS AND DISCUSSIONS

Pure culture was obtained and grown on spawn to get enough culture so as to go for one variable at a time approach. Maximum enzyme activity was observed at pH=6 (53.97 IU/ml) ,glucose as a carbon source( 48.3 IU/ml ), urea as a nitrogen source (33.46 IU/ml) , CuSo4 as metal source ( 46.62 IU/ml) and optimum temprature 32 degree celcius (24.85 IU/ml) during one variable at a time approach.Enzyme activities during one variable at a time approach analysis were given in the table.

1. Carbon Source was the first variable and in this glucose, starch, cellulose and galactose had shown better activity

S. No.Carbon SourceAbsorbance at t= 0Absorbance at t= t1 Enzyme Activity( IU/ml ) 1.Control0.7610.8929.17 2.Glucose0.4111.10148.3 3.Fructose0.2030.2946.37 4.Starch0.7981.31936.4 5.Lactose0.7960.96611.9 6.Cellulose0.3430.63220.23 7.Galactose1.1331.45622.61

2. Next variable is the different pH conditions and best activity was observed at 6.0, 6.5 as shown below:-

S.No.pHAbsorbance at t= 0Absorbance at t= t1 Enzyme Activity(IU/ml) 1. Control (7)0.3940.4403.2 2. 4.50.1400.1893.43 3. 5.50.4990.76318.48 4. 6.00.2641.03553.97 5. 6.50.4110.90834.79 6. 7.50.2080.3107.14 7. 8.00.3480.4668.26

3. Nitrogen Source is the next variable and it was clear that best activity is achieved using urea and yeast extract as nitrogen source as shown in the table below :-

S.No. Nitrogen Absorbance at t= 0Absorbance at t= t1Enzyme Activity (IU/ml) 1.NaNO30.3490.549 14.00 2.Urea0.4560.934 33.46 3.Peptone0.2870.287 0 4.Yeast extract0.5510.825 19.18

4. Next variable was concentration of metals and the best variables for which there was maximum activity are copper sulphate and potassium chloride (KCl) as shown in table below:-

S. No.MetalsAbsorbance at t= 0Absorbance at t= t1 Enzyme Activiy(IU/ml ) 1.Control0.4570.520 4.41 2.KCl0.2990.625 22.82 3.CuSo40.4211.087 46.62 4.FeCl30.2260.227 0 5.CaCl20.2000.668 32.76

5. Next variable was the incubation temperature and optimum temperature was found to be in between 30 32 degree celcius.

S. No. Temperature (degree celcius)Absorbance at t= 0Absorbance at t= t1 Enzyme Activity ( IU/ ml) 1. 27 0.133 0.166 2.31 2. 30 0.149 0.251 7.14 3. 32 0.706 1.061 24.85 4. 37 0.259 0.265 0.42

RSM EXPERIMENTAL RESULTS (BOX-BEHNKEN)

S. NopHTemperatureInoculum AmountCarbonSurfactantI.P%degradationLaccase Activity1625620.32070.0524.012625620.12061.1316.173530830.12050.349.84730810.12065.3214.355530620.21040.566.1666351020.12066.4719.397630820.22077.7333.8886301010.21060.8122.759635820.33081.2123.1710735810.22059.812.9511625820.31047.3211.912525830.22038.475.32

S.No.pHTemperatureInoculum AmountCarbonSurfactantI .P% degradationLaccase activity13635820.31046.7116.8714535830.22043.547.42157301020.23080.8829.26165301020.23060.6712.39176251020.32070.2727.9318630820.22079.8834.9319630820.22074.3233.8120635820.11040.3711.7621735830.22062.9913.5822635620.32067.2617.57236351020.32068.0818.13246301030.21062.1723.73

S.No.pHTemperatureInoculum AmountCarbonSurfactantI .P% degradationLaccase Activity256251020.12069.928.07266301010.23082.536.98276301030.23083.7937.1285301020.21044.388.1229630820.22076.9435.9130635620.12065.181731530810.32049.949.1732730830.12068.718.8333630820.22079.2335.4934530620.23059.5113.9335630820.22081.4237.5436630610.23077.1624.08

S.No.pHTemperatureInoculum AmountCarbonSurfactantI .P% degradationLaccase Activity37635820.13070.8419.6738730620.23076.0822.1939630610.21054.1410.2240630630.21063.2111.0641730830.32070.8820.58427301020.21067.7422.7543535810.22036.895.8144630630.23078.9118.7645725810.22059.5414.2846625820.13071.2817.1547625820.11053.8110.9948625820.33073.7518.76

S.No.pHTemperatureInoculum AmountCarbonSurfactantI .P% degradationLaccase Activity49730620.21064.9613.7250730810.32074.5719.1851530830.32056.7910.0852725830.22063.8516.5953530810.12049.38.8954525810.22040.624.83

ANALYSIS OF RESULTSExperimental data obtained from experimental runs was analysed using Design Expert 8.0.7.1. Fit summary program looked for highest order model that was significant for our data without any lack of fit.This program calculated the effects for all model terms. Statistically significant model was detected and suggested model was underlined. This became the default model on model screenDiagnostics Program determines the predicted value of experimental data for each particular run.

MODEL DESIGN SUMMARYQuadratic model was suggested for my design.

OPTIMIZATION OF PHENOL DEGRADATION Optimization was done using the statistical model generated during analysis process. Optimization program searches the design space, using the models created during analysis to find factor settings that meet the defined goals. This program needs to define the criteria required for optimization of the response. To maximize the degradation, goal would be "maximize" and the upper limit would be 100%.

Lower limits were kept at 70%. After determining the optimization criteria, this program looked through all the given solutions to see which ones best meet our requirements as specified in maximization criteria.

78 solutions were given for maximizing the degradation. Solution 1 was selected as most desirable solution. OPTIMIZED SOLUTIONS- PHENOL DEGRADATION

SolutionspHTempInoculum AmountCarbon SourceSurfactantI.P.(days)%degradation1.6.3930.4310.001.920.3030.0089.83362.6.2930.1010.001.680.2227.4588.05423.6.3830.2210.001.820.3030.0088.97424.6.1931.176.002.430.3029.5987.7163

RESPONSE SURFACE PLOTS: SOLUTION 1 This plot represents the interaction between pH and temperature towards phenol degradation. Shape of response surface plot indicates that there was very high interaction between pH and temperature Changes in pH and temperature has very high impact on degradation efficiency.

In this plot, there was not much interaction being observed between pH and carbon source. Response surface lied between pH 6.00 to 7.00 and carbon source of 1.5 to 2.5%. Both of the factors were approximately contributing equally to degradation efficiency.

In this response surface plot, no interaction was observed between inoculum amount and surfactant It indicates that these factors did not contribute for much variation in degradation efficiency.

Laccase Activity OptimizationThe criterias were specified for optimization of laccase activity. Lower limit was kept at 15 IU and upper limit was kept at 40 IU. Sixty three solutions were given for maximization of laccase activity.Most desirable solution for maximizing laccase activity is given below:-

pHTempInoculum AmountCarbon SourceSurfactantIncubation PeriodLaccaseActivity6.3529.8310.001.990.2227.0138.767

RESPONSE SURFACE PLOTS: LACCASE ACTIVITY In this plot, interaction between pH and temperature towards laccase enzyme activity was shown. Optimized surface lied between pH range 6.0 to 7.0 and temperature of 27 0 c to 30 0 c.

In this plot, no interaction was observed between two factors (inoculum amount and surfactant) which means that these factors did not show much variation for the response (laccase activity).

In this plot, effect of pH and carbon source on response was shown. Shape of graph indicted that both the factors are equally contributing toward response

DEGRADATION OF 2-4-DCP USING OPTIMIZED CONDITIONS Whole cell treatment approach was found to be more prominent than treatment of 2-4- DCP with crude laccase.The optimal degradation of 2-4-DCP was found at pH 6.4, temperature of 310C, incubation period of 30 days and using 1.9% carbon source (glucose) and 0.3% surfactant (Tween 80).Approximately 85% removal of 2-4 DCP from contaminated soil was observed using whole cell treatment process.Degradation of phenol was analysed using 4-aminoantipyrine method.

Crude laccase enzyme treatment had shown 72% removal of 2-4 dichlorophenol. Colour difference was observed between control and treated sample. Spectrophotometric analysis of sample indicated the degradation of phenol from sample. Colour difference during phenol degradation analysis

References Naresh Magan ,Silvia Fragoeiro and Catarina Bastos ; Environmental Factors and Bioremediation of Xenobiotics Using White Rot Fungi ; Mycobiology 38(4) : 238-248 (2010) The Korean Society of MycologyRenata Yamanaka1; Clarissa F. Soares1; Dcio R. Matheus2; Ktia M.G. Machado ; Ligninolytic enzymes produced by trametes villosa ccb 176 under different culture conditions ; Brazilian Journal of Microbiology (2008) 39:78-84.Muralikrishna Chivukula and V. Renganathan ; Phenolic Azo Dye Oxidation by Laccase from Pyricularia oryzae ; Applied and Environmental biology, Dec. 1995, p. 43744377 0099-2240/95/$04.0010 Copyright q 1995, American Society for Microbiology

Patrick J. Collins , Michiel J.J.Kotterman,Jim A.Field, Alan D.W.Dobson ; Oxidation of Anthracene and Benzo[a]pyrene by Laccases from Trametes versicolor ; Applied and environmental biology, Dec. 1996, p. 45634567 Copyright q 1996, American Society for Microbiology Khadar Valli and Michael H. Gold ; Degradation of 2,4-Dichlorophenol by the Lignin-Degrading Fungus Phanerochaete chrysosporium ; Journal of bacteriology , Jan. 1991, p. 345-352 Copyright 1991, American Society for Microbiology Richard T. Lamar and Diane M. Dietrich ; In Situ Depletion of Pentachlorophenol from Contaminated Soil by Phanerochaete spp.; Applied and environmental biology, Oct. 1990, p. 3093-3100