"Change everything so that everything can remain the same"

Giuseppe Tomasi di Lampedusa

5 DECOULORIZATION, DETOXIFICATION AND

COMMUNITY DYNAMICS OF MICROORGANISMS

DURING TREATMENT OF DISTILLERY SPENT WASH IN

THREE STAGE BIOREACTOR

5. Decolourization, detoxification and community dynamics of

microorganisms during treatment of distillery spent wash in three stage

bioreactor

5.1. Introduction

The commercial production of ethanol is carried out by distillation process using

molasses as the raw material because of its easy availability and low cost. The process of

effluent generation and its composition is given in detail in chapter three. The wastewater

generated at the various stages of distillation process is termed as spent wash which is

rich in colored organic compounds and becomes extremely toxic when it _comes in

contact with high temperature. Thus, waste water from distilleries and fermentation

industries, cause great soil and water pollution due to the presence of dark brown

recalcitrant pigments such as melanoidin, polyphenolic compounds and caramels that are

produced by thermal degradation and condensation reactions of sugar (Evershed et al.,

1997; Dhaiya et al., 2001). Because of lack of efficient treatment and improper mode of

disposal of effluents generated by industries, the untreated waste water find their to the

nearby water bodies which results in loss. of productivity of natural waters and

deterioration of water quality to such an extent that the water becomes unusable. Thus, it

is quite necessary to take proper remedial measures before final disposal of effluent.

Various physicochemical methods have been applied but these methods only

change the form of contaminants rather than degrading them and are resource intensive in

nature. Microbial degradation and decolourization of industrial wastes is an environment­

friendly and cost competitive alternative of waste minimization (Mohana et al., 2007;

Pant and Adholeya, 2007). Microorganisms like bacteria, fungi, yeast, and algae have

been utilized widely since long back for biodegradation of complex, toxic and recalcitrant

compounds present in various industrial wastes including distillery spent wash for

environmental clean up (Benito et al., 1997; Sirianuntapiboon et al., 2004; Kumar and

Chandra, 2006; Mohana et al., 2007). Nevertheless, a number of studies have

demonstrated the presence of genotoxic compounds in various wastewaters from

industrial sources (Mahimraja and Bolan, 2004; Chandra et al., 2007).

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New guidelines for disposal of sludge and industrial effluents have generated

interest in applying wider ways of biological treatment. Sequencing batch reactor (SBR)

technology has recently become an attractive alternative option for the removal of various

xenobiotic compounds from wastewaters (Tomei et al., 2004; Mohan et al., 2005).

Preliminary studies, both anaerobic and aerobic systems are commonly used to treat the

wastewaters from agro-industrial plants including distilleries as well. Increasing attention

is being directed towards utilizing microbial activity (pure bacteria, fungi and microalgal

cultures) for the decolourization of distillery-spent wash. Sometimes mixed communities

can overcome the problems faced by pure cultures in the environment because of

nutritional limitations and toxic substances (Thakur, 1995).

Hence, in this study strategies have been adopted to use microbes isolated (fungi

and bacteria) from the effluent sites, in a sequential way in which two fungi were used at

first two steps in order to adsorb the effective shock load of effluent by bacteria which

was used at the third step in the continuous process. Another advantage of using fungi

and bacteria in a sequential manner is that fungi helps to remove the colored components

of the distillery spent wash whereas bacteria was effective in removing most of

recalcitrant organic compounds and drastically reducing the COD levels of the treated

effluent. This way microorganism were isolated from indigenous sources and applied for

decolourization and detoxification of distillery spent wash so that they can associate with

the· microorganism of native place. Advances in molecular ecology has led to the

application of both qualitative and quantitative molecular methods such as denaturing

gradient gel electrophoresis (DGGE) in order to characterize dynamics of archae

assemblages (Muyzer, 1999). The DGGE technique provides valuable information about

the dominant phylotypes with in the complex microbial systems such as bioreactors

(Akarsubasi et al., 2006).

In chapter 3 and 4, decolourization of distillery spent wash, using fungi

(Emericella nidulans var. lata, Neurospora intennedia) and bacteria (Bacillus sp.)

isolated from distillery mill site was reported. In this study, an improvement of this

process by using all these three strains in a sequential manner and also simultaneous

detoxification of the effluent in the three-step bioreactor was carried out. In addition, the

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study of evaluation of performance and community dynamics in the bioreactor with the

help of DGGE techniques was done.

5.2. Materials and methods

5.2.1. Effluent treatment in sequential mode in batch reactor

After optimization of culture conditions, the treatment of the·· distillery effluent

was carried out in sequential manner using first fungus (Neurospora intermedia) treated

effluent further treated with second fungus (Emericella nidulans var. lata) and vice-versa.

To determine the best sequence, treatments were carried out at flask scale having 10%

MSM-effluent. The color and COD reduction was measured (as given in chapter 4) after

each treatment. The sequence, which led to maximum reduction in color and COD of the

effluent, was used for scale-up studies in three stage sequential bioreactor where fungi

were used for treatment of distillery effluent which was subsequently treated by bacteria

at the final stage of treatment.

5.2.2. Treatment of effluent in a three stage sequential bioreactor

The effluent treatment process optimized at the flask level was scaled up to glass

made 15L bioreactor fabricated in the lab with effective working volume of lOL. Process

parameters like pH, temperature, rpm, inoculum size and growth factors i.e. %carbon and

% nitrogen were maintained for all the three strains as per the results obtained from

optimization studies in chapter three & four. The treatment was carried out in sequential

manner with 10% effluent-MSM treated by fungus type I (Neurospora intennedia)

further by fungus type II (Emericella nidulans) and finally by bacteria (Bacillus sp.). A

schematic diagram of three step sequential bioreactor is shown in Figure5.1. All the

stages of the bioreactor were fitted with an aerator for continuous air supply during the

aerobic treatment. The effluent was let in the first stage of bioreactor from the effluent

reservoir to start the bioreactor operation with the first fungus (Neurospora intennedia).

For first stage the retention time was 6 h, while it was kept 12h for the rest of the stages.

The bioreactor was in continuous mode of operation for 30h. Samples were withdrawn

for color and COD analysis after every four hours.

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Effluent ReseiVior . f-Regulato1~

Stage II

Screening fungi I .,.41Jt--- -J------,--'

Sampling otrtlet

stage Ill

Sampling 0~1« ...... ------ ~-----'

~I Alkali

1 1 Online

pH m«er

Figure 5.1. Schematic diagram of three stage bioreactor for treatment of distillery spent

wash.

5.2.3. Preparation of inoculum for sequential batch reactor

For the preparation of fungal inoculum in the form of pellets, the purified fungal

isolates were grown on potato dextrose broth with streptopenicillin (100 ppm). The flasks

were incubated at 30 oc for 4 days in orbital shaker. The pellets of approximately 1.5-2

nun size were used for the treatment of distillery spent wash in bioreactor (Thakur, 2004).

However, in case of bacteria the inoculum was used along with the growth media, as it

was practically not feasible to produce weight percent of the bacterial inoculum. Thus,

86

the 12h broth culture was used as inoculum for the third stage of sequential bioreactor

(Sirianuntapiboon and Prasertsong, 2008).

5.2.4. Analytical methods

During the continuous mode distillery effluent treatment in the sequential

bioreactor the influent, reactor content and effluent samples from each stage were .

monitored for temperature and pH at regular time intervals. However, pH was adjusted

with the acid-alkali control valve fitted with all the three stages, as the pH requirement

was different for fungal and bacterial strains. Treated samples after each stage were taken

and centrifuged at 8,000 rpm for 15 minutes for analysis on the following parameters.

Ceil free supernatants of the treated bioreactor samples at each stage were taken

to determine the color and COD, anions by Ion chromatography, cations by Flame

photometry and metal analysis by AAS and toxicity analysis (as given in chapter 3) '

Degradation analysis by Gas Chromatography-Mass Spectroscopy

The untreated and treated effluent samples from each stage of bioreactor were

processed prior to GC-MS analysis according to Raj et al. (2007). Effluent samples

(50ml) were centrifuged (8,000 rpm for 15 min) to remove suspended solids and biomass.

Supernatants were acidified to pH 1-2 with cone. HCl and then thoroughly extracted with

three volumes of ethyl acetate. The organic layer was collected, dewatered over

anhydrous Na2S04 and filtered through Whatman no. 54 filter paper. The residues were

dried under a stream of nitrogen gas. The ethyl acetate extracts residues were analyzed as

trimethylsilyl (TMS) derivatives (Lundquist and Kirk, 1971). In this method, 100~1

dioxane and 30~1 pyridine were added in the samples followed by silylation with 50~1

trimethyl silyl [BSTFA (N, O-bis (trimetylsilyl) trifluoroacetarnide) and TMCS

(trimethylchlorosilane)]. The mixture was heated at 60 oc for 15 min with periodic

shaking to dissolve the residues.

The analysis was done using Gas Chromatography mass Spectroscopy (GC-MS)

(GC- Agilant 6890N and MS 5973N) equipped with .a capillary column (DB5 MS;

30mX0.25um film thickness X 0.25mm I.D. X 30 meter long). One microliter of each

extract was injected to analyze by GC-MS at condition (Split less mode; initial

temperature 80°C for 1.5 min; temperature increased 80 oc to 230 oc at a rate of 20°C

min -J and 230 oc to 250 oc and kept it at 25 oc for 4.5 min.). The head pressure of the

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helium carrier gas was 80 kPa, helium flow rate 1.1 ml/min., and data was compared with

the inbuilt standard chemical library system (National Institute of Standards and

Technology (NIST) library, NBS75K, 2003) of GC-MS.

Community dynamics studies using DGGE techniques.

The untreated and treated effluent samples from each reactor were collected in

duplicate and stored at :...20 oc until DNA extraction. One ml aliquots of each stored

sample was used for inoculation in 100 ml potato dextrose broth at 30 oc for 7 days for

fungal inoculants and one ml in LB for l2h for bacterial inoculants, to enhance the

microbial population.

Extraction of fungal DNA and amplification by polymerase chain reaction

DNA was isolated and amplified as described earlier by Doyle and Doyle (1987).

The ITS 1 region of 18S rDNA gene was amplified for DGGE analysis (Hortal et al.,

2006) (chapter 3). Further nested PCR was performed using the template amplified by

ITS 1 and ITS 4 primers that included ITS 1 region.

L.._ ___ 1_8s ___ ____.l ITSI 15.8S I ITS2 ._l ___ 2_8_s ___ ______.

~ ITS2

Figure 5.2. ITS 1 region of the fungal rDNA gene amplified by ITS 1 * (GC clamp) and

ITS2 primers

For amplification of ITS 1 region, forward primer ITS 1 had the sequence 5 '­

TCCGTAGGTGAACCTGCGG-3' and reverse primer ITS2 5'­

GCTGCGTTCTTCATCGATGC-3' (Ren et al., 2004). A 40 bp GC clamp was attached

to ITS! primer (Muyzer et al., 1993). After addition of GC clamp it is symbolized as

ITSl *.The reaction mix (25J.ll) consisted of buffer with MgCb-2.5 111 (2.5mM), dNTP-

2.0 111 (lmM each), ITS1 * (forward)-0.7J1l (lOmM), ITS2 (reverse)- 0.7 111 (lOmM), Taq

polymerase-0.5 111 (5UIJ1l), DNA-the PCR product (region between ITSl and ITS4) was

diluted 100 times and volume was made up by water. The programme for amplification is

initial denaturation step of 95 oc for 3min, followed by 25 cycles of amplification at 95

oc for 30 s, 59 oc for 1 min and 72 oc for 30 sec and a final extension of 5 min at 72 oc.

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Amplified products were resolved on 0.7 % agarose gels containing ethidium bromide (1

flg/ml).

Extraction of bacterial DNA and PCR

Genomic DNA of bacteria from all the stages was extracted and the V3 region of

the -16S rRNA gene corresponding to positions 341 to 561 of Escherichia coli was

partially amplified as described earlier in chapter four.

DGGE Technique

DGGE was performed with the Bio-Rad DCode ™ system as described earlier in

chapter four. The gel images were captured using a CCD camera and were analyzed by

using Alpha Ease~C (V4.1.0) software.

Analysis of toxicity by Comet assay

Alkaline comet assay using Saccharomyces cerevisiae MTCC 36 (model

organism) was performed as described earlier in chapter three and four.

Analysis of comets

The slides were stained with 4,6 diarnidino-2-phenylindole, DAPI (2 flg/ml, 100

fll per slide) just before analysis. Comets were analyzed using the fluorescence

microscope with an excitation filter of 355 nm and a barrier filter of 450 nm. Fifty comets

were analyzed per sample. The fluorescence microscope was fitted with 1000X oil

immersion lens. Cells with damaged DNA appeared like comets. The percentage of DNA

in tail was calculated using the software TriTek Comet Score™ Freeware vl.5.2.6

(Miyamae et al., 1998).

5.3. Results

5.3.1. Determination of sequence for effluent treatment in batch reactor

To evaluate the most effective sequence at flask level, effluent treatment was

given individually by Emericella nidulans var. lata (I) and N. intermedia (II), and then

sequential treatments were carried out. The effluent treated by Emericella nidulans var.

lata was further treated by N. intennedia (III) and vice-versa i.e. the effluent treated by N.

intermedia was further treated by Emericella nidulans var. lata (IV) (Figure 5.3). Initially

color concentration was 6218 CU. Maximum reduction in color was obtained by

treatment IV i.e. 77% reduction (1431 CU).

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t:: 0 ;:: 80 :s ·;: 0 060 u Cll

"C

&40 CIS -t:: Cll

~20 Cll 0...

II Ill IV Treatment types

Figure 5.3. Percent reduction in color for 10% effluent-MSMtreatment by both fungi

individually and then sequentially

5.3.2. Treatment of distillery spent wash in Sequential Bioreactor

The most efficient sequential treatment (IV) i.e. effluent treated by N. intennedia

further treated by E. nidulans var. lata conducted at the flask level was scaled up (15L) to

the bioreactor level. It had the working volume of 1 OL. Process parameters such as pH 3

for fungi and pH 7 for bacteria and. temperature 30°C were maintained throughout the

experiment. The duration of effluent treatment was 6h by N. intennedia (stage I), 12h by

E. nidulans var. lata (stage II) and finally 12h by Bacillus sp. (stage III). Thus, the total

duration of treatment was 30h. Initial color and COD values of the untreated effluent

were 6780 CU and 30,576 mg/1, respectively, which were finally reduced to 1220 CU and

2140.40 mg/1 (COD), indicating 82% reduction in color and 93% reduction in COD

levels after sequential treatment (Figure 5.4).

90

c: 100 0 ;:; nJ

80 N

- Color - coo

·~: 0 0 60 (J Cl)

c Cl) 40 C) nJ -c: Cl) 20 (J ... Cl)

c.. 0 - '---- T

II Ill Stages of Treatment

Figure 5.4. Reduction in color and COD content of distillery spent wash after sequential

treatment in 15L bioreactor

5.3.3. Analysis

The ions (phosphate, nitrate and sulphate) present in the effluent were analyzed in

detail and the data revealed that phosphate was below detection limits. Nitrate was very

high in the effluent and reduced with each successive treatment. The initial nitrate

concentration was 6071 ppm, which reduced to 398lppm after sequential treatment

showing a decrease of 34%. There was no significant change in sulphate concentration.

Heavy metals like copper, zinc and nickel were detected, and it was found below

detection limits. Sodium and potassium was estimated using flame photometer.

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Table 5.1. Concentrations of ions at different stages of 15L bioreactor

S.No. Ions Control Stage I Stage II. Stage III

Anions (ppm)

1 Nitrate (N03) 6071 5459.4 5002.2 3981.7

2 Sulphate (SO/) 363.4 351.8 353.7 323.8

3 Phosphate (P04 5) B.D.L. B.D.L. B.D.L. B.D.L.

Cations (ppm)

1 Copper ions (CuL+t.H) B.D.L. B.D.L. B.D.L. B.D.L.

2 Zinc ions (Zn.l+) B.D.L. B.D.L. B.D.L. B.D.L.

3 Nickel ions (Ni2+) B.D.L. B.D.L. B.D.L. B.D.L.

4 Sodium ions (Na+) 1180 1100 1028 1020

5 Potassium ions (K+) 870 840 860 780

GC-MS Analysis

The influent and effluent from each stage of the bioreactor was analyzed by GC­

MS to find degradation pattern of the compounds present in the effluent. Data generated

by the study showed increase in the number of peaks of metabolism at every successive

stage. The chromatograph corresponding to the compounds extracted with ethyl acetate

from the acidified supernatants obtained from untreated (Control) and treated samples

from each stage with Neurospora intennedia (Stage I), Emericella nidulans var. lata

(Stage II) and Bacillus sp. (Stage III) are shown in Figure 5.5a-d and their peak identity

is shown in Table 5.2.

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5

i i

i

(a)

t .. £ :1 . .

. I·~~· -l~ . , -

-~ J ~ . . . Jl . j -. W_.,_._..~JiJ,L v-..Jt~ ~ lk .~

(b)

10 15 20 25 30 minutes

Figure 5.5. GC-MS chromatograph of (a) untreated distillery spent wash, (b) treated effluent in stage I of bioreactor

93

MCounts

(c)

c: ·e c: (")

0 ·e l{)

co cO m l{) c: ,...: .E

5.0 7.5 10.0 12.5 15.0 17.5 20.0 minutes 22.5

Figure 5.5. GC-MS chromatograph of (c) treated effluent in stage II of bioreactor (d) effluent treated in stage III of bioreactor

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The result of the study indicated disappearance pattern of major peaks after RT at

30.475 toRT at 41.946 and emergence of varied and increased number of peaks even

before RT at 12.084, which was the first major peak detected in the control (untreated)

sample (Figure 5.5a). Some of the degradation products were identified (Table 5.2) from

the standards available of the authentic compounds and documented data from National

Institute of Standards and Technology (NIST) library.

Table 5.2. Identification of metabolites and degradation products formed at different

stages in 15L bioreactor by NIST library as given in Figure 5.5

S. No. R. T. Control Stage I Stage II Stage Ill lndentified compounds N-Methyi-N-(2,4,6-

1 7.721 - + + + trimethylpheny)formamide 2 8.132 - - + + Formic acid 3 8.51 - - + + Acetic acid 4 9.458 - - + + Furan Carboxylic acid 5 10.379 - - + + 2- Propanone, 1- hydroxy 6 11.307 - - + + Cinnamic acid

1 ,4 benzenedicarboxylic acid, 7 12.005 - + + + bis(trimethylsilyl)ester

(Z)-4-Nitrophenylazo tert-butyl 8 12.4 - + - + sulfide 9 12.596 - - + + Phthalic acid 10 12.949 - - + + Pyrrolecarboxylic acid 11 13.067 - - + trimethyl-pyrazine 12 13.112 - + + + 2H-Pyran-2-one 13 13.177 - - + dimethyl-pyrazinone 14 13.248 - - + - Ethaneperoxoic acid

Bis(5-tert-butyl-2 methoxy 15 13.452 + + + - phenyl)dimethyl silane 16 13.555 - - - + Propanedioic acid 17 13.702 - + + + Hexadecanoic acid 18 14.498 - - - + Cyclononasiloxane 19 14.578 - + + + Hydroxyethoxypropyl- dioxolane

Dimethylcyclohexane-20 14.908 - + + + dicarbaldehyde 21 15.317 - - + + Ethylene acetal 22 15.904 - - + + 9-octadeanamide 23 16.46 - - - + Isopropyl-Phthalate

1 hydoxy-16-nitro-bicyclo[ 1 0.4. O]hexadecane-13-

24 16.973 + - - - one 25 17.598 - + + + Tetradecanoic acid 26 18.081 - - + + Octadecanoic acid

Cis-9, 1 0-epoxyl n-27 19.291 - - + + propyloctadecanamide 28 21.583 - - + + Octadecatrienoic acid 29 30.483 + - - - T etradecyldioxolane 30 39.831 + - - - Hexadecatetran

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Various acid and aromatic type of compounds were identified in extract from

successive stages of bioreactor treatment revealing degradation of complex polymers

(melanoidin) present in distillery effluent. Very few number of compounds were

degraded and detected in the first stage of treatment as the process of adsorption was

dominant by Neurospora intermedia (Stage I), however, number of low molecular weight

acid type compounds such as formic acid, acetic acid, cinnamic acid were extracted from

the effluent treated by Emericella nidulans var. lata (Stage II) and Bacillus sp. (Stage Ill).

This suggests that complex and high molecular weight compounds present in the

effluent when partially digested by fungal strains are finally degraded to simpler fractions

by bacteria with the help of intracellular enzymatic system and the role of these enzyme

which are responsible for degradation of melanoidin like compounds was studied further.

Microbial community dynamics during treatment of distillery effluent

Fungal and bacterial community structures at each stage including untreated

effluent (control) were screened by DGGE analysis of PCR amplified products of ITS

region of 18S rDNA in case of fungi and 16S :rDNA gene fragments in case of bacteria

(Figure 5.6). In case of fungal DGGE band profile, the taxa has changed and increased in

number over the successive stages of bioreactor. Many equally and intense bands

indicating the presence of other ribotypes was observed. The bacterial DGGE profile

shows a higher change in the community profile along with the change in the band

intensities with time. Light band intensity patterns with many weak bands were still

present in the first and second stage of sequential bioreactor where fungal population was

introduced and dominant.

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(a) (b)

Figure 5.6. DGGE band pattern of (a) Bacterial and (b) Fungal community in different

stages of bioreactor

The bacterial DGGE band pattern revealed that however there were other

bacterial communities in Control, I and II stages of bioreactor, yet there was dominance

of the introduced Bacillus sp. in the III stage of bioreactor as revealed by the intensity of

the band while in case of fungal DGGE pattern revealed a shift in the community

composition throughout all the stages with the dominance of introduced stains at

particular stages. However, in the III stage where bacterium was introduced, fungal

DGGE bands were also observed, suggested their role in the biodegradation of distillery

effluent along with Bacillus sp. Statistical analysis was not possible with bacterial and

fungal communities in our study because dominant populations were not readily

observed. Therefore, the technique has limitations to exactly quantifying the extent of the

dominance of particular species in different stages ofbioreactor.

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Comet assay analysis for detoxification of distillery effluent in sequential bioreactor

The effluent treated in 15L bioreactor was subjected to toxicity analysis using

comet assay. The comets were analyzed by Comet score software to quantify the toxicity

effect. Percent DNA in tail was evaluated. Higher the amount of DNA in tail, more

damaged is nucleus and thus higher is the toxicity. Comets were divided into five

classes: Class I less than 1% DNA in tail, Class II had 1-20% DNA in tail, Class III had

21-50% DNA in tail, Class IV it was 51-75% DNA in tail and finally Class V having

comets with more than 75% DNA in tail (Figure 5.7a). The sample size was 50 for each

sample. Figure 5.7b shows the distribution of comets in five classes for different samples

taken from different stages of bioreactor. (%) Incidence shows the percent of comets

present in that class. From the graph it is clear that treatments were efficient in reducing

toxicity as there was a clear shift of comets to lower classes. In untreated effluent

(control) class IV was dominant. The bulk of the comets have shifted to class II after

sequential treatments. There was significant reduction in the percent DNA in tail and it

reduces by 80% after three step treatments (Figure 5.7c). The result showed that the

treatment of effluent in three step sequential bioreactor at the optimized conditions is

effective not only in reducing color and COD content but also toxicity.

Classes I Ill IV v

(a)

98

(I) 50 u c: 40 (I)

"C '(j 30 c: - 20 c: (I) u 10 ... (I) c..

0

"% Ill ~~

i$1 o II :;.c'

~· o..., ~

Q)('l 0 iO ...

(b)

60 ~------------------------------~

50 C1l

~ 40

<t z 30 0 -c: ~ 20 ..... Cl)

0.. 10

Control II Ill

(c) Stages of Bioreactor

Figure 5.7. Comet assay analysis of treated distillery spent wash in the bioreactors where

(a) is nuclei of Saccharomyces cerevisiae MTCC 36 in different stages of comet

formation, (b) distribution of comets in class I-V at different stages of bioreactor and (c)

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Percentage of DNA in tail of comets in presence of distillery mill effluent (control) and

after treatments in different stages of bioreactor.

5.4. Discussion

Spentwash generated from distillery industries is one of the most complex and

cumbersome colored wastewater with very higli.BOD, COD, organic and inorganic toxic­

constituents. Its disposal into the environment is hazardous and has a considerable

pollution potential. With government policies on pollution control becoming more

stringent, distillery industries have been forced to look for more effective treatment

technologies. In the recent past, increasing attention has been directed towards utilizing

mixed microbial community for decolourization of spentwash. A number of clean up

technologies have been put into practice and novel bioremediation approaches for

treatment of distillery spent wash. Advances in biotechnology, has led to the development

of aerobic sequential bioreactors for the treatment of high strength distillery effluent.

Concept of sequential treatment is important because in this case organisms can

be applied for efficient treatment of effluent in different stages. In this study, the

treatment of effluent was done using two fungal strains and one bacterial strain at the

optimized conditions (Chapter 3 and 4). Firstly, treatment was carried out by fungi

fol1owed by bacteria. Bacteria produce intracel1ular enzymes and need to ingest the

chemicals for their degradation. This is difficult as the chemicals present in the effluent

are complex polymers (melanoidin). Apart from that fungi have chitin in their cell walls

and can tolerate high concentration of pollutants than bacteria. Fungi has better capability

to remove color from the effluent, however, bacteria is more potent for degradation of

aromatic compounds (Thakur, 2004). Thus, it was decided that first and second treatment

will be given by the two fungal strains and finally by bacteria. Similar studies have been

carried out earlier for mineralization of bicyclic aromatics such as chlorinated biphenyls,

chlorinated dibenzofurans and naphthalene sulfonates, in which two or more .

microorganisms were tried sequentially, one member of which carried out the initial

catabolic reactions and the other completed the rest of the metabolic pathway to

mineralize the organic compounds completely (Pokhrel and Viraraghavan, 2004; Singh

and Thakur, 2006).

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The sequence of treatment by the fungi was determined. The maximum percent

reduction in color by individual strains was 60% and 55%, respectively (Figure 5.3). This

increased to 77% decolourization when treatment IV was followed, i.e. effluent treated

by Neurospora intermedia was further treated by Emericella nidulans var. lata. This

sequence was then used in scale up studies in 15L bioreactor in which final treatmerttwas

given by bacteria. The sequential treatment using fungi and bacteria yielded faster and

better results in comparison to individual strain treatments. The treated effluent of

bioreactor was analyzed in detail. There was 34% reduction in concentration of nitrate

ions. Level of sodium and potassium ion was also very high and treatment of the effluent

had no significant effect on it.

Besides being various studies carried on chemical and microbial degradation of

natural and synthetic melanoidins present in distillery effluent, yet now no clear

mechanism of its degradation is present due to the complexity of Maillard reactions and

reaction conditions like pH, temperature, heating time, water content and lack of pure

standards (lkan et al., 1990). However, GC-MS study conducted on control and effluent

treated in various stages of bioreactor postulates degradation mechanism of melanoidin

present in distillery effluent in which complex products are seen in initial stages of

treatment and more simpler and acid types of products are seen in later stages of

bioreactor. Complex polymers such as melanoidins (a bio-polymer formed by amino­

carbolyl reaction) are very recalcitrant in nature and exist extensively in molasses and

other agri-based industrial wastewaters (Chandra et al., 2008). Microorganisms have been

known to serve as useful tools for the conversion of complex organic compounds to

valuable intermediate products (Masai et al., 1999). After microbial degradation its

chemical structure has been postulated many times by various methods to reduce its

pollution load so that better strategies could be made for its degradation and

decolourization. Methods like pyrolytic degradation of nitrogenous and non-nitrogenous

polymers produced at different stages of MaiJJard reaction (Yaylayan and Kaminsky,

1998), oxidative degradation using alkaline H20 2 (Hayase et al., 1984) and Ozone

treatment (Kim et al., 1985) were used to study and identify various fractions of

Melanoidin as 2-methyl-2, 4-pentanediol, N,N-dimethylacetamide, phenol, acetic acid,

oxalic acid, 2-furancarboxylic acid, furandicarboxylic acid and 5-(hydroxymethyl)-2-

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furancarboxylic acid. However, it is noteworthy here that furan and acid type of fractions

have also been identified in our GC-MS study involving microbial degradation of

distillery spent wash. Similar studies have also been reported stating that fungi and

bacteria and their enzymatic systems could metabolize complex compounds to low

molecular-weight products (~okela et al., 1987; Kumar et al., 2001). These degradation

studies were carried out in the present investigation, however the degradation pathway of

complex melanoidin like compounds could not be extrapolated.

Contrary to the belief that effluents' indigenous population might affect the

persistence and efficiency of the introduced organisms, DGGE analysis was done and it

was found that the introduced organisms were competent enough to produce desired

results yielding significant decolourization and COD reduction with the native population

of the effluent. DGGE bands were scored on the basis of presence or absence and

intensity of band patterns (Lyautey et al., 2005). Presence of single strain band in the

control (untreated effluent) confirms the isolation of microbes from the effluent and

sludge itself. Analysis of DGGE data from the three stage sequential bioreactor treating

distiller,y effluent indicated that the composition of bacterial and fungal communities

changed during treatment in the bioreactor. This could be beneficial from the point of

view of process engineering and the development of processes as the introduced

organisms at different stages were competent enough with the native population of the

effluent and produced desired results.

Toxicity analysis of the treated effluent showed that the sequential treatment was

more efficient in detoxification of the effluent as compared to individual treatments and

led to 80% reduction in the toxicity levels of the treated effluent. There was a clear shift

in class of the comets with more comets falling in class II instead of class IV in later

stages of bioreactor. Thus, a significant reduction in color (82%) and COD (93%) was

achieved along with significant detoxification levels when these organisms were applied

in a sequential manner for effluent treatment.

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