CHAPTER 4 RESULTS AND DISCUSSIONshodhganga.inflibnet.ac.in/bitstream/10603/9157/9/09... ·...

CHAPTER 4.

RESULTS AND DISCUSSION

Chapter 4. Results and Discussion

Ph.D. Thesis of Shah Kunal Nareshkumar [1091] Page 67

4.1. SCREENING, ISOLATION, PURIFICATION AND

IDENTIFICATION OF OSTB

4.1.1. Site selection and isolation based on solvent tolerance screening

The sites under study include Alang-Sosiya ship breaking yard, where wide

range of wastes including oil, asbestos, paint chips, heavy metals, plastic, glass and

ceramics are generated. Other sites include hydrocarbon contaminated places, like

petrol pump where constant pressure of organic solvent drives the bacterial diversity.

Garden soil harbours a bacterial diversity that is equipped to compete interspecies and

intraspecies. Salt farm has different salinity evaporation ponds, where initially the

bacterial diversity of sub soil sea water is gradually replaced by halophilic bacteria.

The soil/sediment and seawater samples collected from above sites were subjected for

isolation of OSTB.

Samples collected were inoculated in modified Luria-Bertani (MLB) medium

containing toluene (log P 2.5) for acclimatization of microorganisms. After

acclimatization, the samples were transferred to agar plates to have isolated colonies

of various OSTB. The number of isolates obtained from each site is depicted in Table

4. Twenty five morphologically different OSTB were obtained which were selected

for further study. For species level bacterial identification, a systematic polyphasic

approach, based on morphological and biochemical characteristics, fatty acid profiling

and 16S rDNA sequencing, was adopted.

4.1.2. Morphological and biochemical characterization

Out of 25 OSTB, 22 were rods (showing arrangement as single or in pairs) and

3 were cocci (showing arrangement as tetrad or sarcinae). Out of 25 OSTB, 20 were

motile, while 5 were non motile. The colony characteristics ranged from round shape

(AK1871) to irregular shape (AK2641), from entire (AK1874) to undulate margin

(AK1871) and from flat elevation (AK2641) to convex elevation (AK39532).

Variation in colony pigmentation was also observed like orange (AK1882), yellow

(AK39423, AK39532, AK39766, and AK39881) and white. AK1872 was an

exopolymer producer, evident from mucous colony characteristics. AK39762

exhibited unique property of adhering to agar surface very firmly.



Table 4. Details of sample collection area.

SN Location GPS Coordinates Date of collection Sample Type No. of

isolates

Code No. of OSTB

isolated

1 Alang, Gujarat N 21° 23.561’,

E 072° 10.475’.

Jan 05, 2007 Contaminated beach

sand

05 AK1871, AK1872,

AK1874, AK1882,

AK2641.

2 Veraval, Gujarat N 20° 55.062’,

E 070° 21.037’.

Jan 05, 2007 Contaminated soil 01 VK1901.

3 Experimental Salt Farms,

CSMCRI, Gujarat

N 21° 47.652’,

E 072° 07.519’.

Dec 26, 2008 Mud and subsoil

water

08 AK39313, AK39315,

AK39422, AK39423,

AK39427, AK39531,

AK39532, AK39651.

4 Bharat Petroleum Pump,

Bhavnagar, Gujarat

N 21° 46.329’,

E 072° 08.786’

Dec 26, 2008 Contaminated soil 04 AK39762, AK39763,

AK39765, AK39766.

5 Hindustan Petroleum

Pump, Bhavnagar, Gujarat

N 21° 44.701’,

E 072° 08.940’

Dec 26, 2008 Contaminated soil 03 AK39673, AK39674,

AK39675.

6 CSMCRI Garden, Gujarat N 21° 45.520’,

E 072° 08.679’

Dec 26, 2008 Soil 04 AK39881, AK39883,

AK39885, AK39887.

The phenotypic characteristics of 25 OSTB are as follows [Table 5]:



Table 5. Phenotypic characteristics of 25 OSTB.

SN OSTB Shape &

Arrangement

Colony characteristics Motility

1 AK1871 Rod – single Round, wavy, dry, opaque, off-white,

granular,

Motile

2 AK1872 Rod – single Round, entire, moist, opaque, eps

producer

Motile

3 AK1874 Rod – single,

double

Round, entire, moist, opaque, off-white Motile

4 AK1882 Rod Round, entire, moist, opaque, orange Motile

5 VK1901 Rod – single,

double

Round, entire, moist, opaque, off-white Motile

6 AK2641 Rod – single Irregular, entire, moist, opaque, cream Motile

7 AK39313 Rod Round, wavy, moist, translucent, light

brown, granular

Motile

8 AK39315 Rod Round, entire, moist, translucent, off-

white, micro CFU

Motile

9 AK39422 Rod Round, wavy, moist, translucent, off-

white

Motile

10 AK39423 Rod Round, wavy, moist, translucent, yellow

ochre, granular

Motile

11 AK39427 Rod – pair Irregular, wavy, dry, translucent, off-

white, granular (crystal type)

Non

motile

12 AK39531 Rod- pair Round, wavy, moist, translucent, dull

pink, granular

Motile

13 AK39532 Cocci – tetrads,

sarcinae

Round, entire, dry, yellow, convex Non

motile

14 AK39651 Rod – pair Round, entire, moist, translucent, yellow

tinge

Motile

15 AK39762 Rod –single, pair Round, entire, dry, opaque, dull pink,

adheres to agar

Motile



16 AK39763 Rod – single, pair Round, entire, moist, translucent, off-

white, raised

Motile

17 AK39765 Rod – single, pair Round, entire, dry, opaque, off-white,

butyrous

Motile

18 AK39766 Cocci Round, entire, dry, yellow, convex Non

motile

19 AK39673 Rod – single, pair Round, entire, dry, translucent, off-white Motile

20 AK39674 Rod – single, pair Round, entire, dry, opaque, off-white,

micro CFU

Motile

21 AK39675 Cocci Round, entire, dry, opaque, off-white,

micro CFU

Non

motile

22 AK39881 Rod – single, pair Round, entire, moist, translucent, yellow

ochre, granular

Non

motile

23 AK39883 Rod Round, entire, moist, opaque, cream, high

convex, butyrous

Motile

24 AK39885 Rod – single Round, entire, moist, opaque, off-white Motile

25 AK39887 Rod – single, pair Round, wavy, moist, translucent, brown Motile

The biochemical characteristics of OSTB showed that only one isolate was

catalase negative (AK1882). Ten isolates showed MR positive indicating vigorous

acid producers. While four were VP positive indicating their ability to produce acetyl

methyl carbinol (acetoin). None of the OSTB showed indole production, citrate

utilization, urease production, maolnate utilization and phenyl alanine deamination.

Starch hydrolysis was observed in 18 OSTB, while 17 showed tributyrin hydrolysis.

Bile esculin hydrolysis was observed in seven OSTB. Arginine decarboxylation was

observed by only two isolates. Lysine decarboxylation yielding cadaverine was

observed for six OSTB, while only three OSTB showed ornithine decarboxylation

yielding putrescine. Among various sugars tested, α-methyl – D – mannoside, sorbose

and xylitol were not hydrolyzed by any of the isolates, while seven isolates showed

acid production from lactose, while 14 OSTB showed acid production from dextrose.

The biochemical characteristics of 25 OSTB are as follows [Table 6 & 7; Fig. 4]:



Table 6. Biochemical tests of 25 OSTB.

SN 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

OS

TB

AK

1871

AK

1872

AK

1874

AK

1882

VK

1901

AK

2641

AK

39313

AK

39315

AK

39422

AK

39423

AK

39427

AK

39531

AK

39532

AK

39651

AK

39762

AK

39763

AK

39765

AK

39766

AK

39673

AK

39674

AK

39675

AK

39881

AK

39883

AK

39885

AK

39887

Catalase + ++ + - ++ +++ +++ +++ + +++ + + +++ + + + + ++ ++ + + + + +++ ++

Oxidase + + + - + + + + + - + + - + + + + + + + - - - - -

MR + + + - - - - + - + - + - + + - + - - + - - - - -

VP - - - - - - - - - - - - - + + - + - - + - - - - -

Indole - - - - - - - - - - - - - - - - - - - - - - - - -

Nitrate + + - - - - - - - + + + - - + - + - + - - + - - -

Simmon

Citrate

- - - - - - - - - - - - - - - - - - - - - - - - -

Urease - - - - - - - - - - - - - - - - - - - - - - - - -

Malonate - - - - - - - - - - - - - - - - - - - - - - - - -

Phenyl-

Alanine

- - - - - - - - - - - - - - - - - - - - - - - - -

Starch + + + + + + + - + + - + - - ++ +++ ++ + ++ - - + + - +

Tributyrin + + + + + + - + - + - + - ++ ++ - ++ - - ++ + - + + +

Bile

Esculin

- - - - - - - + - - + - - + - - + - - + + - - + -

Dec

arb

ox

yl

ase

Arg - - - - - - - - - - - - - - - - + - - - - - - + -

Lys - - - - - - - + - - - - - - - - + - + + - + - + -

Orn - - - - - - - + - - - - - - - - - - - + - - - + -



Table 7. Sugar utilization pattern of 25 OSTB.

SN 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

OS

TB

AK

18

71

AK

18

72

AK

18

74

AK

18

82

VK

19

01

AK

26

41

AK

39

31

3

AK

39

31

5

AK

39

42

2

AK

39

42

3

AK

39

42

7

AK

39

53

1

AK

39

53

2

AK

39

65

1

AK

39

76

2

AK

39

76

3

AK

39

76

5

AK

39

76

6

AK

39

67

3

AK

39

67

4

AK

39

67

5

AK

39

88

1

AK

39

88

3

AK

39

88

5

AK

39

88

7

1 Lactose -a - ± - + + ± ± + - - - - - - + - - + - + - ± - +

2 Xylose - - ± - + + - - + + ± ± - ± - - ± ± + ± + - + - +

3 Maltose + ± ± + + + ± - + + ± + - - ± + ± ± + ± + + + - +

4 Fructose + + ± + ± + ± + ± + + + - + ± + ± - + + + + + + +

5 Dextrose + ± + + + + ± + ± ± ± ± ± + ± + ± ± + + + + + ± +

6 Galactose - - ± ± + + - ± + - - - - ± - + - - + ± + - ± - +

7 Raffinose - - + - + + ± ± + - - + - ± - + ± - + ± + - + - +

8 Trehalose + ± ± + + + ± ± + + ± + ± + ± ± ± - + + + + + ± +

9 Melibiose - - + ± + + - ± + - - - - ± - + ± - + ± + - ± - +

10 Sucrose - ± + ± + + ± + + + ± + ± + ± + ± ± + + + + + ± +

11 L-Arabinose - ± - ± - - ± ± + - ± - - + ± - ± - + ± + - ± ± +

12 Mannose - + - + - - - + - - + ± - + ± - ± - + + ± + - ± +



13 Inulin + + + - + ± - ± + - ± + - - ± + ± - + - - ± + - +

14 Sodium

Gluconate

± - - - - - - - - - - ± - - - ± ± - - - ± - - - -

15 Glycerol ± + ± + + + ± + ± + ± ± ± + + ± ± - + + + + + - +

16 Salicin ± + ± - - - ± + + - + - - + + - ± - + + - - + ± +

17 Glucosamine ± - ± ± ± - + ± ± ± ± ± ± ± ± ± ± ± ± + ± ± ± ± ±

18 Dulcitol - - - - - - - - - - ± - - - - - - - - - - - - - -

19 Inositol - - - - - - ± - + - - - - - ± ± ± - + - - - - - +

20 Sorbitol - - - - - - ± - - - ± - - - ± - ± - ± - - - + - -

21 Mannitol - ± ± + - + ± + ± + + + - + ± ± ± - ± + + + + ± +

22 Adonitol - - - - - - - - - - - - - - - - - - - - ± - - - -

23 α-Methyl

-D-glucoside

- - ± - ± + ± - ± - ± - - - ± ± ± - + - + - ± - +

24 Ribose ± - ± ± ± + - - - - ± ± - + ± ± ± - - + + ± + + -

25 Rhamnose - - - - - - - ± + - ± - - - - - - - + - - - - - ±

26 Cellobiose - - - - - ± ± ± ± - ± - - + - - ± - + + - - ± ± ±



27 Melezitose - - - - - - - - - - - - - - - - - - + - + - - - +

28 α-Methyl

-D-Mannoside

- - - - - - - - - - - - - - - - - - - - - - - - -

29 Xylitol - - - - - - - - - - - - - - - - - - - - - - - - -

30 ONPG - + + - + + + + + - + + - - + + - - + - - - + - -

31 Esculin + + - + + + + + - - + - - + + - + - + + + - + + +

32 D-Arabinose - - - - - - - - + - - - - ± - - - - + ± + - - - +

33 Citrate + + + - + + + + - + + - + - + + + + - + - - + + +

34 Malonate + - + - + + - - - + + - - - - + + + - - - - + + -

35 Sorbose - - - - - - - - - - - - - - - - - - - - - - - - -

36 Control - - - - - - - - - - - - - - - - - - - - - - - - -

a (-) negative, (+) positive, (±) weakly positive.



Non utilized sugars are observed in pink

colour.

Utilized sugars are observed in yellow

colour.

Fig. 4. Biochemical identification through biochemical kit.

The morphological, cultural and physiological characteristics of the isolates were

compared with data from the Bergey’s Manual of Determinative Bacteriology [Holt, 1994].

Although these tests provided rough idea about the probable genera, the identification

was incomplete. Besides, this biochemical identification is time consuming and

frequently generates false positive results and may lead to erroneous identification of

species. Hence, FAME analysis was performed to identify organisms.

4.1.3. Fatty Acid Methyl Ester

Fatty acid profile of twenty five OSTB was studied. RTSBA6 library of

Sherlock sample processor was used. The MIDI calibration mix showed 0.997-0.998

similarity index during each calibration. Good peak matching was observed for

standard. While for each OSTB, the total response was more than 50000, reference

ECL shift was less than 0.015 and percent peak named were more than 85%. The

similarity index above 0.500 is a good match with difference of 0.100 between next

match. The library showed good similarity index for certain bacteria (Bacillus cereus,

B. pumilus, B. megaterium, B. licheniformis and Staphylococcus sp.). Whereas for

others, the similarity index was below 0.500, but the total response, reference ECL

shift, and % peak named was in acceptable range indicating that the probable match

was not present in the RTSBA library. Values lower than 0.300 suggested that the



MIS database do not have the species in the database, but indicated most closely

related species.

The technique used by the Sherlock Microbial Identification System (MIS) is

based on Similarity Index, a numerical value, which expresses how closely the fatty

acid composition of an unknown compares with the mean fatty acid compositions of

the strains used to create the library entries listed as its match. Thus, it is an

expression of relative distance from the population mean.

Based on fatty acid profiling, all the OSTB were identified at least up to genus

level, while some of them were identified even up to species level. The following

observations were obtained for each OSTB [Table 8]:

Table 8. Similarity index of 25 OSTB obtained by fatty acid methyl ester analysis using the

Sherlock Microbial Identification System (MIS).

SN OSTB Sim

Index

Entry Name Total

Response

%

Named

Ref

ECL

Shift

1 AK1871 0.741 Bacillus cereus 85765 100 0.007

2 AK1872 0.625

0.468

Staphylococcus schleiferi

Bacillus licheniformis

51213 100 0.014

3 AK1874 0.518 Bacillus viscosus 91303 100 0.004

4 AK1882 0.686

0.683

Bacillus filicolonicus

Virgibacillus pantothenticus

74252 100 0.007

5 VK1901 0.427 Bacillus viscosus 90025 100 0.002

6 AK2641 0.362 Bacillus flexus 64056 100 0.002

7 AK39313 No matches found 69729 100 0.012

8 AK39315 0.572 Bacillus coagulans 190944 100 0.010



9 AK39422 0.246 Bacillus sp. 126662 100 0.010

10 AK39423 0.546 Bacillus sp. 116220 95.07 0.006

11 AK39427 0.150 Geobacillus

stearothermophilus

211226 100 0.008

12 AK39531 0.362 Bacillus macroides 269496 98.15 0.010

13 AK39532 0.620

0.524

Brevibacillus choshinensis

Micrococcus luteus

494349 99.93 0.004

14 AK39651 0.641 Bacillus pumilus 239769 100 0.003

15 AK39762 0.710 Bacillus licheniformis 90918 100 0.007

16 AK39763 0.656

0.439

Bacillus megaterium

Bacillus flexus

154204 100 0.006

17 AK39765 0.750 Bacillus subtilis 78249 98.92 0.005

18 AK39766 0.769 Micrococcus lylae 424855 99.67 0.003

19 AK39673 0.361 Bacillus lentus 151984 100 0.004

20 AK39674 0.530 Bacillus pumilus 153370 86.84 0.011

21 AK39675 0.742

0.523

Staphylococcus cohnii

Staphylococcus arlettae

493184 98.95 0.003

22 AK39881 0.207 Bacillus megaterium 64360 100 0.010

23 AK39883 0.958 Bacillus megaterium 113059 98.10 0.006

24 AK39885 0.578 Bacillus pumilus 85189 100 0.010

25 AK39887 0.418 Bacillus lentus 100114 100 0.010



Phenotypic characteristics as well as FAME analysis based identification

provided species level identification for many OSTB, but failed to identify remaining

OSTB. Hence, 16S rRNA gene sequencing technique was used to identify remaining

and confirm the species level identification for identified ones.

4.1.4. Identification based on 16S rRNA gene sequencing

A total of 25 strains were used for genomic DNA extraction followed by PCR

amplification using 16S rRNA specific primers. All the PCR products were gel-

purified and were partially sequenced to analyze their 16S rRNA genes. DNA

sequencing and phylogenetic analysis revealed that most of the 16S rDNA sequences

from all 25 isolates were between 93 to 99% identical (25 isolates) to the sequences

within GenBank. The E value for closest match for each isolate was 0.0.

The sequences were submitted to GenBank and following accession numbers

were assigned, indicated in brackets.

AK1871 (FJ573187), AK1872 (FJ573188), AK1874 (FJ573189), AK1882

(FJ573190), VK1901 (FJ573191), AK2641 (FJ573193), AK39313 (HQ234336),

AK39315 (HQ234337), AK39422 (HQ234338), AK39423 (HQ234339), AK39427

(HQ234340), AK39531 (HQ234341), AK39532 (HQ234342), AK39651 (HQ234343),

AK39762 (HQ234344), AK39763 (HQ234345), AK39765 (HQ234346), AK39766

(HQ234347), AK39673 (HQ234348), AK39674 (HQ234349), AK39675 (HQ234350),

AK39881 (HQ234351), AK39883 (HQ234352), AK39885 (HQ234353), AK39887

(HQ234354).

The possible identification of twenty five isolates using reported sequence

from NCBI GenBank was done [Table 9].



Table 9. 16S rRNA gene based identification of OSTB with Accession number and its closest

match.

SN OSTB

(Assigned

Accession

No.)

Closest match

(Accession No.)

Quer

ry L

ength

Max

Sco

re

Tota

l S

core

Quer

ry C

over

age

Max

. Id

enti

ty

E V

alue

1 AK1871

(FJ573187)

Bacillus cereus

(GU391507)

1373 1551 2284 98 99 0.0

2 AK1872

(FJ573188)

Bacillus

licheniformis

(FJ266313)

1443 2531 2531 97 98 0.0

3 AK1874

(FJ573189)

Geobacillus

stearothermophilus

(FJ581462)

1426 2067 2067 97 93 0.0

4 AK1882

(FJ573190)

Bacillus aquimaris

(AB376670)

1450 2519 2519 96 99 0.0

5 VK1901

(FJ573191)

Bacillus sp.

(GQ280041)

1444 1411 1411 96 85 0.0

6 AK2641

(FJ573193)

Bacillus marisflavi

(GU332612)

1451 2540 2540 98 98 0.0

7 AK39313

(HQ234336)

Bacillus

oceanisediminis

(GQ292772)

1388 2514 2514 99 99 0.0

8 AK39315

(HG234337)

Terribacillus

halophilus

(AB243849)

1407 2532 2532 100 99 0.0

9 AK39422 Bacillus

licheniformis

1400 2545 2545 99 99 0.0



(HG234338) (FJ607346)

10 AK39423

(HG234339)

Bacillus firmus

(GU397391)

1394 2575 2575 100 100 0.0

11 AK39427

(HQ234340)

Bacillus sp.

(AB575949)

1337 2052 2052 99 94 0.0

12 AK39531

(HQ234341)

Bacillus firmus

(GQ903397)

1367 2366 2366 100 97 0.0

13 AK39532

(HQ234342)

Micrococcus

luteus (AJ717369)

1353 2495 2495 100 99 0.0

14 AK39651

(HQ234343)

Bacillus pumilus

(GU726861)

1385 2558 2558 100 100 0.0

15 AK39762

(HQ234344)

Bacillus

licheniformis

(HM006898)

1354 2329 2329 99 97 0.0

16 AK39763

(HQ234345)

Bacillus flexus

(GU397394)

1384 2556 2556 100 100 0.0

17 AK39765

(HQ234346)

Bacillus subtilis

(HM802140)

1384 2553 2553 100 99 0.0

18 AK39766

(HQ234347)

Micrococcus

indicus

(EU169174)

1375 2523 2523 100 99 0.0

19 AK39673

(HQ234348)

Bacillus

licheniformis

(EU221362)

1395 2483 2483 100 98 0.0

20 AK39674

(HQ234349)

Bacillus pumilus

(HM480271)

1385 2514 2514 98 99 0.0



21 AK39675

(HQ234350)

Staphylococcus

arlettae

(EU660331)

1385 2558 2558 100 100 0.0

22 AK39881

(HQ234351)

Bacillus aquimaris

(HM044219)

1381 2374 2374 100 97 0.0

23 AK39883

(HQ234352)

Bacillus

megaterium

(HM357354)

1385 2558 2558 100 100 0.0

24 AK39885

(HQ234353)

Bacillus pumilus

(HM371418)

1337 2459 2459 100 99 0.0

25 AK39887

(HQ234354)

Bacillus sp.

(GQ199770)

1361 2012 2012 99 93 0.0

Interestingly, 16S rRNA sequence based identification showed good amount

of congruence with FAME analysis data. Thus, outcome of identification based on

fatty acid methyl ester analysis as well as 16S rRNA gene sequencing data is

presented in the form of a combined table to give a holistic view on identification of

all OSTB under study [Table 10].

As observed from Table 10, fatty acid profiling of some isolates have

suggested two different species of bacteria matching with the database. Here, a

polyphasic approach was applied to draw the conclusion where results of phenotypic

characteristics and 16S rRNA sequencing were used. For example, according to

FAME analysis, AK1872 was identified as Staphylococcus schleiferi with Similarity

Index (SI) of 0.625 and Bacillus licheniformis with SI of 0.468, but phenotypic

characteristics suggested it to be rod, and 16S rRNA sequencing data also suggested it

to be B. licheniformis; hence the isolate was identified as Bacillus licheniformis.

Similarly, FAME data of AK1882 showed SI of 0.686 for Bacillus filicolonicus and

0.683 for Virgibacillus pantothenticus, while 16S rRNA sequencing data suggested

Bacillus aquimaris, hence the isolate was concluded to be Bacillus sp. For AK39532,

FAME analysis suggested Brevibacillus choshinensis with SI of 0.620 and



Micrococcus luteus with SI of 0.524 while phenotypic characteristics suggested it to

be cocci, and 16S rRNA sequencing also suggested Micrococcus luteus, thus finally

the isolate was identified to be Micrococcus luteus. Similarly, a consensus decision

was reached for isolates AK39763 and AK39675 and they were identified as Bacillus

flexus and Staphylococcus arlettae, respectively.

Table 10. Combined data of fatty acid methyl ester analysis and 16S rRNA gene sequencing

for identification of OSTB.

SN OSTB

(Assigned

Accession

No.)

MIDI identification 16S rRNA

sequencing based

closest match

Concluded

identification of

OSTB Sim

Index

Entry Name

1 AK1871

(FJ573187)

0.741 Bacillus cereus Bacillus cereus Bacillus cereus

2 AK1872

(FJ573188)

0.625

0.468

Staphylococcus

schleiferi

Bacillus

licheniformis

Bacillus

licheniformis

Bacillus

licheniformis

3 AK1874

(FJ573189)

0.518 Bacillus viscosus Geobacillus

stearothermophilus

Bacillus sp.

4 AK1882

(FJ573190)

0.686

0.683

Bacillus

filicolonicus

Virgibacillus

pantothenticus

Bacillus aquimaris Bacillus sp.

5 VK1901

(FJ573191)

0.427 Bacillus viscosus Bacillus sp. Bacillus sp.

6 AK2641

(FJ573193)

0.362 Bacillus flexus Bacillus marisflavi Bacillus sp.

7 AK39313

(HQ234336)

No matches found Bacillus

oceanisediminis

Bacillus

oceanisediminis



8 AK39315

(HG234337)

0.572 Bacillus coagulans Terribacillus

halophilus

Terribacillus

halophilus

9 AK39422

(HG234338)

0.246 Bacillus sp. Bacillus

licheniformis

Bacillus

licheniformis

10 AK39423

(HG234339)

0.546 Bacillus sp. Bacillus firmus Bacillus firmus

11 AK39427

(HQ234340)

0.150 Geobacillus

stearothermophilus

Bacillus sp. Bacillus sp.

12 AK39531

(HQ234341)

0.362 Bacillus macroides Bacillus firmus Bacillus firmus

13 AK39532

(HQ234342)

0.620

0.524

Brevibacillus

choshinensis

Micrococcus luteus

Micrococcus luteus Micrococcus

luteus

14 AK39651

(HQ234343)

0.641 Bacillus pumilus Bacillus pumilus Bacillus pumilus

15 AK39762

(HQ234344)

0.710 Bacillus

licheniformis

Bacillus

licheniformis

Bacillus

licheniformis

16 AK39763

(HQ234345)

0.656

0.439

Bacillus

megaterium

Bacillus flexus

Bacillus flexus Bacillus flexus

17 AK39765

(HQ234346)

0.750 Bacillus subtilis Bacillus subtilis Bacillus subtilis

18 AK39766

(HQ234347)

0.769 Micrococcus lylae Micrococcus indicus Micrococcus

indicus

19 AK39673

(HQ234348)

0.361 Bacillus lentus Bacillus

licheniformis

Bacillus

licheniformis

20 AK39674 0.530 Bacillus pumilus Bacillus pumilus Bacillus pumilus



(HQ234349)

21 AK39675

(HQ234350)

0.742

0.523

Staphylococcus

cohnii

Staphylococcus

arlettae

Staphylococcus

arlettae

Staphylococcus

arlettae

22 AK39881

(HQ234351)

0.207 Bacillus

megaterium

Bacillus aquimaris Bacillus

aquimaris

23 AK39883

(HQ234352)

0.958 Bacillus

megaterium

Bacillus megaterium Bacillus

megaterium

24 AK39885

(HQ234353)

0.578 Bacillus pumilus Bacillus pumilus Bacillus pumilus

25 AK39887

(HQ234354)

0.418 Bacillus lentus Bacillus sp. Bacillus sp.

Furthermore, when phylogenetic tree was constructed using published

sequences, each OSTB under study showed homology with different reported species

[Fig. 5].



Fig. 5. Construction of phylogenetic tree using Neighbour Joining (NJ) program of MEGA

version 4.0. Published 16S rRNA gene sequences of various bacteria were used as reference

strains for the construction of tree.



Fig. 6. Construction of phylogenetic tree using Neighbour Joining (NJ) program of MEGA

version 4.0 of identified 25 OSTB.

The phylogenetic relationship of 25 OSTB among themselves was studied by

constructing a Neighbour Joining tree by MEGA version 4.0 [Fig. 6]. Out of twenty

five OSTB, twenty belonged to Bacillus sp., two to Micrococcus sp., and one each

from Geobacillus sp., Terribacillus sp., and Staphylococcus sp. Alternatively, 80%

isolates belonged to genus Bacillus, while 8% to Micrococcus, 4% each to

Staphylococcus, Geobacillus and Terribacillus sp. The phylogenetic tree was

prepared by six different methods, and it formed same clustering for all methods as

observed in Fig. 7.



Neighbour Joining (NJ)

Minimum Evolution

Boostrap NJ

Interior branch NJ

Bootsrap Minimum Evolution

Interior Branch Minimum Evolution

Fig.7. Phylogenetic tree constructed using different computing methods in MEGA version 4.0.

A similar pattern was observed in each method.



4.1.5. Cluster analysis by MIDI

Cluster analysis uses mathematical techniques to display similarities among

objects in a set. Using MIDI’s cluster analysis tools, Dendrogram and 2-D Plot,

samples with common fatty acid compositions can be identified and grouped. Based

on the defined groups, a sample can be identified as a member of a strain if the sample

is included in a cluster. The results are displayed graphically to depict the relatedness

between organisms.

4.1.5.1. Dendrogram:

Dendrogram uses cluster analysis techniques to produce unweighted pair

matching based on fatty acid compositions. The results are displayed graphically to

depict the relatedness between organisms. Linkages among samples at a level of 2

Euclidian distances or lower can be considered as same organism. Euclidian Distance

is the distance in n-dimensional space between two strains when their fatty acid

compositions are compared. The Euclidian distance scale permits quick determination

of the relatedness of entries at the species and subspecies levels (approximately 10

and 6 Euclidian distances respectively).

Fig. 8. Dendrogram prepared by MIDI Sherlock analysis.

Using MIDI’s Sherlock analysis, a Dendrogram is prepared [Fig. 8] that shows

different cluster formation: Bacillus licheniformis – megaterium group, Bacillus

viscosus – flexus group and Bacillus lentus – subtilis group. Micrococcus sp. forms a

different clade indicating it being distantly associated with the remaining bacteria. As



mentioned earlier, closely related species have formed a cluster by being associated in

branch clades, while distant isolates form a second cluster.

Fig. 9. Neighbour Joining tree prepared by MIDI Sherlock analysis.

Based on the fatty acid profiling, a Neighbour Joining (NJ) tree [Fig. 9] was

prepared using MIDI’s Sherlock analysis. Different groups comprising Bacillus

licheniformis – megaterium group, Bacillus flexus – viscosus group, Bacillus lentus

group, Bacillus spp. group, Bacillus pumilus – megaterium group and Staphylococcus

– Micrococcus group were formed. Similar group formation was observed in MIDI

Dendrogram analysis as mentioned earlier.

4.1.5.2. 2-D plot

In addition to Dendrogram, 2-D Plot is another cluster analysis tool that can be

used to track a strain. In its normal operating mode, 2-D Plot uses a principal

components analysis of FAME profiles to group entries in a two-dimensional space.

The x-axis represents principal component 1, and the y-axis represents principal

component 2. (These may be changed to plot 1 vs. 3, or 2 vs. 3 to gain additional

perspective.) The 2-D Plot is most useful for finding relationships among large



numbers of organisms or for visualizing the relationships of distantly related

organisms. Thus, large numbers of organisms can be analyzed, the data called into the

2-D Plot, and the resulting diagram(s) used to define groups of closely related

organisms, even when the organisms are not members of species currently nameable

by Sherlock.

Table 11. Description of OSTB sequence in 2D plot

The OSTB were analysed in the order as mentioned in Table 11 by Sherlock analysis.



Fig. 10. 2D plot prepared by MIDI Sherlock analysis.

As observed from the Fig. 10, various clusters are observed, like B. lentus

group, B. viscosus – flexus group, Bacillus spp. group, B. megaterium group, B.

pumilus group, B. licheniformis group. B. cereus and Micrococcus sp. didn’t form any

cluster, they were independently oriented in 2D plots signifying them to be distantly

related to various species.

4.1.6. Sequence diversity among OSTB

Complete 16S rRNA gene sequences of all twenty five OSTB were analysed

by the Maximum Composite Likelihood method in MEGA4 [Tamura et al., 2004;

Tamura et al., 2007].

The number of base substitutions per site from analysis between sequences is

shown. All results are based on the pair wise analysis of 25 sequences. All positions

containing gaps and missing data were eliminated from the dataset (Complete deletion

option of the software). There were a total of 1207 positions in the final dataset.



Table 12. 16S rRNA gene sequence diversity among OSTB.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

1

2 0.101

3 0.146 0.145

4 0.091 0.054 0.125

5 0.270 0.286 0.251 0.258

6 0.082 0.063 0.114 0.034 0.246

7 0.093 0.057 0.111 0.046 0.240 0.048

8 0.103 0.081 0.133 0.082 0.253 0.079 0.057

9 0.085 0.066 0.122 0.070 0.251 0.060 0.052 0.064

10 0.089 0.054 0.106 0.047 0.242 0.045 0.006 0.057 0.051

11 0.170 0.132 0.209 0.132 0.355 0.135 0.118 0.126 0.132 0.117

12 0.110 0.072 0.131 0.071 0.256 0.067 0.030 0.076 0.072 0.024 0.140

13 0.233 0.217 0.298 0.222 0.432 0.211 0.210 0.209 0.207 0.204 0.262 0.228

14 0.091 0.036 0.131 0.057 0.268 0.053 0.052 0.068 0.050 0.048 0.130 0.068 0.197

15 0.105 0.016 0.146 0.064 0.281 0.069 0.063 0.087 0.071 0.058 0.137 0.078 0.222 0.041

16 0.079 0.069 0.076 0.051 0.202 0.045 0.035 0.058 0.044 0.034 0.131 0.057 0.211 0.058 0.073

17 0.097 0.021 0.136 0.056 0.273 0.060 0.055 0.073 0.057 0.049 0.130 0.069 0.203 0.021 0.025 0.062

18 0.235 0.219 0.299 0.223 0.433 0.212 0.209 0.211 0.209 0.204 0.262 0.228 0.008 0.198 0.224 0.212 0.205

19 0.091 0.065 0.119 0.068 0.250 0.063 0.049 0.068 0.007 0.050 0.135 0.073 0.210 0.058 0.070 0.043 0.058 0.212

20 0.091 0.036 0.131 0.057 0.268 0.053 0.052 0.068 0.050 0.048 0.130 0.068 0.197 0.000 0.041 0.058 0.021 0.198 0.058

21 0.105 0.097 0.163 0.093 0.293 0.089 0.095 0.109 0.086 0.092 0.163 0.117 0.211 0.085 0.101 0.080 0.085 0.209 0.088 0.085

22 0.103 0.061 0.140 0.031 0.274 0.043 0.055 0.088 0.077 0.054 0.136 0.078 0.233 0.067 0.065 0.061 0.066 0.234 0.076 0.067 0.107

23 0.082 0.070 0.086 0.057 0.215 0.045 0.039 0.064 0.048 0.040 0.131 0.063 0.204 0.056 0.073 0.009 0.063 0.204 0.047 0.056 0.083 0.065

24 0.091 0.039 0.132 0.059 0.269 0.053 0.054 0.069 0.050 0.050 0.132 0.070 0.197 0.004 0.044 0.058 0.024 0.198 0.058 0.004 0.083 0.069 0.055

25 0.137 0.110 0.188 0.124 0.302 0.115 0.104 0.120 0.075 0.099 0.195 0.117 0.252 0.083 0.116 0.108 0.098 0.253 0.084 0.083 0.142 0.132 0.105 0.078



Description of OSTB as analysed by MEGA4.

1 Bacillus cereus (AK1871) 2 Bacillus licheniformis (AK1872) 3 Bacillus sp. (AK1874)

4 Bacillus sp. (AK1882) 5 Bacillus sp. (VK1901) 6 Bacillus sp. (AK2641)

7 Bacillus oceanisediminis (AK39313) 8 Terribacillus halophilus (AK39315) 9 Bacillus licheniformis (AK39422)

10 Bacillus firmus (AK39423) 11 Bacillus sp. (AK39427) 12 Bacillus firmus (AK39531)

13 Micrococcus luteus (AK39532) 14 Bacillus pumilus (AK39651) 15 Bacillus licheniformis (AK39762)

16 Bacillus flexus (AK39763) 17 Bacillus subtilis (AK39765) 18 Micrococcus indicus (AK39766)

19 Bacillus licheniformis (AK39673) 20 Bacillus pumilus (AK39674) 21 Staphylococcus arlettae (AK39675)

22 Bacillus aquimaris (AK39881) 23 Bacillus megaterium (AK39883) 24 Bacillus pumilus (AK39885)

25 Bacillus sp. (AK39887)

The estimates of evolutionary divergence between 16S rRNA gene sequences among 25 OSTB revealed that except isolate AK39651 and

AK39674 (which showed 100% homology), all other isolates differ from each other. Divergence among 16S rRNA gene sequences in all the

other isolates were in the range of 0.016 to 0.433 [Table 12].



Thus, in each site, the large diversity of the OSTB community constitutes a

bacterial reservoir that allowed them to adopt the changing conditions in the

environment. The presence of diversified bacterial species generally signified the

healthy nature of the ecosystem, since, in the marine or other aquatic systems,

imbalance in the bacterial diversity and abrupt change of particular bacterial species

concentration is the result of stress and frequent diseases.

The present report indicated isolation of following OSTB: B. aquimaris, B.

cereus, B. firmus, B. flexus, B. licheniformis, B. megaterium, B. oceanisediminis, B.

pumilus, B. subtilis, Bacillus sp., M. luteus, M. indicus, S. arlettae, and T. halophilus.

Based on the various reports, it can be concluded that Bacillus group of

species are dominating as OSTB from various ecological niches, e.g. B. cepacia [Shu

et al., 2009], B. cereus [Ghorbel et al., 2003; Joshi et al., 2007; Shah et al., 2010; Xu

et al., 2010], B. licheniformis [Shimogaki et al., 1991; Sareen and Mishra, 2008; Li et

al., 2009], Bacillus pumilus [Rahman et al., 2007], B. sphaericus [Hun et al., 2003;

Sulong et al., 2006; Fang et al., 2009; Liu et al., 2010], B. subtilis [Abusham et al.,

2009; Rai and Mukherjee, 2009; Ahmed et al., 2010b], Bacillus spp. [Matsumoto et

al., 2002; Sardesai and Bhosle, 2003; Gupta et al., 2005b; Reddy et al., 2008; Shah et

al., 2010]. In the present study also, known Bacillus spp. dominated the total number

of OSTB isolates. However, to the best of our knowledge, B. oceanisediminis and T.

halophilus are reported to be novel species as OSTB which are described for the first

time through this work.

Different Staphylococcus spp. are reported as OSTB by various groups such

as Staphylococcus haemolyticus [Nielsen et al., 2005] and Staphylococcus

saprophyticus [Fang et al., 2006]. In this work, Staphylococcus arlettae is reported as

OSTB.

Enormous bacterial diversity in OSTB is reported by various researchers,

which includes: Acinetobacter sp. [Chen et al., 2009; Ahmed et al., 2010a; Uttatree et

al., 2010], Aeromonas veronii [Divakar et al., 2010], Aromatoleum aromaticum

[Trautwein et al., 2008], Brevibacillus sp. [Kongpol et al., 2009; Moreno et al., 2009],

Burkholderia sp. [Zahir et al., 2006; Dandavate et al., 2009], Enterobacter sp.

[Neumann et al., 2005; Gupta et al., 2006], Escherichia coli [Kobayashi et al., 1998;

Asako et al., 1999], Geomicrobium sp. [Karan et al., 2011], Halobacterium sp.



[Akolkar et al., 2008], Marinobacter [Sana et al., 2006], Moraxella sp. [Devi et al.,

2006], Natrialba magadii [Ruiz et al., 2007], Providencia sp. [Kadavy et al., 2000],

Pseudomonas aeruginosa [Ogino et al., 1994; Ogino et al., 2000; Ito et al., 2001;

Gaur et al., 2008a & 2008b; Mahanta et al., 2008; Ji et al., 2010; Kawata et al., 2010],

Pseudomonas fluorescens [Zhang et al., 2009; Cadirci and Yasa, 2010], Pseudomonas

pseudoalcaligenes [Lin et al., 1996], Pseudomonas putida [Inoue and Horikoshi,

1989; Aono et al., 1992; Heipieper et al., 1995; Ramos et al., 1997; Kobayashi et al.,

2000; Chen et al., 2009; Gaur and Khare, 2009], Pseudomonas spp. [Ramos et al.,

1995; Ogino et al., 1995; Kim et al., 1998; Ogino et al., 1999a; Geok et al., 2003;

Gupta et al., 2005a; Rahman et al., 2005 & 2006; Gupta and Khare, 2006; Tang et al.,

2008; Gaur et al., 2010], Rhodococcus spp. [Na et al., 2005; Kita et al., 2009],

Salinivibrio sp. [Karbalaei-Heidari et al., 2007], Serratia marcescens [Zhao et al.,

2008], Streptomyces rimosus [Leščić et al., 2001].

4.2. SOLVENT TOLERANCE AND ANTIBIOTIC RESISTANCE

OF OSTB

4.2.1. Solvent tolerance of OSTB

The ability of bacterial cells to tolerate different organic solvents is an

important cell characteristic that determines their use as a biocatalyst in a biphasic

biotransformation system. Interaction of cells with organic solvents results in cell

toxicity and loss of biomass. Previous reports stated that the solvent toxicity of

solvent toward cells is related not only to the solvent hydrophobicity, expressed by its

log Pow value [Laane et al., 1987], but also to the solvent molecular structure [Vermue

et al., 1993] and the characteristic of the cell membranes [Bruce & Daugulis, 1991].

The solvent tolerance ability of OSTB under the study was investigated. The

cell viability was checked after exposing them to nine different solvents, having a

wide range of the log P value, comprised of aliphatic, alicyclic, aromatic, ether,

alcohol, ketone, and chlorinated class of hydrocarbons at 50% (v/v) concentration.

The solvent tested were hexadecane (8.8), cyclooctane (4.5), n–hexane (3.9), xylene

(3.1), carbon tetrachloride (2.7), benzene (2.1), methyl-tert-butyl ether (0.9), n–

butanol (0.8), and acetone (-0.23).



All the twenty five OSTB isolates thrived in presence of 50 % (v/v) of each

solvent for seven days. Majority of OSTB grew luxuriantly in hexadecane, while they

were mostly inhibited by xylene. Comparatively, good growth was observed in

remaining solvents (cyclooctane, n-hexane, methyl tert butyl ether, benzene, n-

butanol, carbon tetrachloride and acetone) with isolate specific variations. Looking at

the effect of each solvent on particular organism, following observations were noted:

Among 25 OSTB, solvent tolerance pattern of eight Bacillus species,

identified only up to genus level, is described in Fig 11. These isolates include

Bacillus sp. AK1874, Bacillus sp. AK1882, Bacillus sp. VK1901, Bacillus sp.

AK2641, Bacillus sp. AK39427 and Bacillus sp. AK39887. AK1882 and AK39887

showed number of survivors below 50 against all solvents except hexadecane [Fig.

11]. For AK1874, VK1901, AK2641, and AK39427 the numbers of survivors were

below 150 for cyclooctane, hexane and xylene, whereas for solvents carbon tetra

chloride, benzene, MTBE, butanol and acetone, the numbers of survivors were above

150. Sardesai and Bhosle [2003] reported Bacillus sp. that showed growth in presence

of 20% (v/v) chloroform.



Fig 11. Effect of different solvents on the growth of Bacillus spp.

In the present study, five OSTB belonged to B. subtilis – licheniformis group:

B. licheniformis AK1872, B. licheniformis AK39422, B. licheniformis AK39762, B.

licheniformis AK39673 and B. subtilis AK39765. Almost similar trend of solvent

tolerance was observed for four OSTB: B. licheniformis AK39422, B. licheniformis

AK39762, B. licheniformis AK39673 and B. subtilis AK39765 [Fig. 12], where

number of survivors were less than 200 in presence of cyclooctane, ca. 100 in hexane,

less than 50 in xylene, 100-250 in carbon tetra chloride and benzene, ca 300 in

MTBE, 50-200 in butanol and 50-150 in acetone.

AK1872 showed relatively more tolerance to solvents as number of survivors

were slightly higher for each solvent as compared to other four OSTB. Production of

exopolysaccharide by the isolate might be the plausible reason which rendered it

tolerance to organic solvents. Sareen and Mishra [2008] reported tolerance of B.

licheniformis strain RSP-09 in presence of 50% (v/v) DMSO. Solvent tolerance of B.

licheniformis against polar and nonpolar solvents has been reported by Li et al.,

[2009] where 40% growth of the bacterium was observed in presence of 1% (v/v) and

2% (v/v) benzene and acetone respectively, whereas 27% growth in presence of 2%

(v/v) butanol was observed as compared to control.



Fig 12. Effect of different solvents on the growth of B. licheniformis – subtilis group and B.

cereus.

Among 25 OSTB, only one isolate, identified as B. cereus AK1871, exhibited

relatively higher tolerance to organic solvents as compared to other isolates which

was evident from higher number of survivors [Fig. 12]. The number of survivors

ranged from 300 to 450 in cyclooctane, hexane, xylene, carbon tetra chloride,

benzene, MTBE, butanol and acetone. Ghorbel et al., [2003] reported screening based

on exposure of organisms to 25% (v/v) hexane, where they isolated solvent tolerant B.



cereus. As per report of Zahir et al., [2006], B. cereus tolerated 1.3% (v/v) hexane and

1% (v/v) benzene, while it failed to grow in 1.2% (v/v) xylene.

B. cereus AK1871 was grown in presence and absence of toluene at 50% (v/v)

concentration. The scanning electron micrographs of cells clearly showed presence of

some sheath like structure around the cells grown in presence of toluene as a part of

the adaptation towards solvent [Fig. 13].

Cells grown in ZMB without toluene.

Magnification X12,000.

Cells grown in ZMB with 50% (v/v)

toluene. Magnification X10,000.

Fig. 13. Scanning electron micrographs of B. cereus AK1871 was grown in presence and

absence of toluene at 50% (v/v) concentration.

Ramos et al., reported P. putida DOT-T1, grown in the presence of high

concentrations of toluene, exhibited a wider periplasmic space than cells grown in the

absence of toluene. They also reported that in some cases ribosomes appeared in the

periplasmic space, suggesting that damage occurred at the level of the cytoplasmic

membrane. They also observed cell membrane evaginations in cells growing on 10%

(vol/vol) toluene. Perhaps, transmission electron micrographs of B. cereus AK1871

could reveal some more details regarding its ultrastructure.

Gupta et al., [2006] reported transmission electron micrographs of the

Enterobacter cells growing in the presence of cyclohexane are showed convoluted

and disorganized membrane structure leading to electron transparent regions and

accumulation of solvent was clearly observed. Similar changes have been observed in

case of Pseudomonas sp. cells grown in p-xylene [Cruden et al., 1992]. Solvents are

reported to damage the integrity of cell membrane structure. This causes loss of



permeability regulations. In extreme cases leakage of cell RNA, phospholipid and

protein also takes place [Sikkema et al., 1995]. Cytoplasmic membrane of solvent

tolerant cells adopt by making changes in fatty acid composition and protein/lipid

ratio in cell membrane to restore the fluidity [Isken and de Bont, 1998].

Among 25 OSTB, three OSTB belonged to B. firmus – flexus group: B. firmus

AK39423, B. firmus AK39531 and B. flexus AK39763. B. firmus AK39531 and B.

flexus AK39763 showed almost similar solvent tolerance, while B. firmus AK39423

showed slightly higher number of survivors with respect to other two isolates [Fig.

14]. B. firmus AK39531 and B. flexus AK39763 showed 150-250 survivors in

presence of cyclooctane and carbon tetra chloride, 100-150 in hexane, less than 100 in

xylene, 200-250 in benzene, ca 300 in MTBE and ca 150 in butanol and acetone.

Fig. 14. Effect of different solvents on the growth of B. firmus – flexus group and B.

megaterium.

Among 25 OSTB, only one isolate was identified as B. megaterium AK39883

which showed extremely high sensitivity to all the solvents studied as number of



survivors were much below 50 in the presence of cyclooctane, hexane, xylene, carbon

tetra chloride, benzene, MTBE, butanol and acetone [Fig. 14].

Among 25 OSTB, three different species of B. pumilus were found: AK39651

and AK39674 showed similar pattern of solvent tolerance, while AK39885 showed

solvent tolerance pattern that varied from the other two [Fig. 15]. AK39651 and

AK39674 showed 100-300 survivors in cyclooctane, hexane, xylene, carbon tetra

chloride, benzene, MTBE, butanol and acetone while AK39885 showed 100 survivors

in presence of benzene, 200 in MTBE, 300 in cyclooctane, 500 in hexane and below

50 in carbon tetra chloride, butanol and acetone, while no survivors were detected

when grown in the presence of xylene.

Fig. 15. Effect of different solvents on the growth of B. pumilus and B. aquimaris.

Only one species of B. aquimaris AK39883 was found among 25 OSTB [Fig.

15]. It showed ca 200 survivors in presence of cyclooctane, benzene and MTBE. It



showed 300 survivors in hexane and carbon tetra chloride, less than 50 in butanol and

acetone, while no survivors were observed in xylene.

Among 25 OSTB, three isolates were cocci belonging to M. luteus AK39532,

M. indicus AK39766 and S. arlettae AK39675. M. indicus AK39766 and S. arlettae

AK39675 showed similar solvent tolerance pattern, whereas M. luteus AK39532

showed quite high sensitivity against solvents except cyclooctane [Fig. 16]. AK39766

and AK39675 showed 150-200 survivors for cyclooctane, 100-200 for hexane, less

than 100 for xylene, 150-250 for carbon tetra chloride and acetone, ca 250 for

benzene, 250-350 for MTBE and 100-200 for butanol. AK39532 showed 300 and 50

survivors in presence of cyclooctane and hexane, respectively, while xylene, carbon

tetra chloride, benzene, MTBE, butanol and acetone were found to be highly toxic as

no survivor was found in the presence of these solvents. Zahir et al., [2006] reported

Staphylococcus sp. tolerated 1.3% (v/v) hexane, 1.2% (v/v) xylene and 1% (v/v)

benzene.

Fig. 16. Effect of different solvents on the growth of Staphylococcus sp., Micrococcus spp.

and Teribacillus sp.



Among 25 OSTB, only one T. halophilus AK39315 was found [Fig. 16]. It

showed 200-250 survivors in presence of cyclooctane, carbon tetra chloride and

MTBE, 50-100 for hexane and acetone, 250-300 for benzene and butanol and less

than 50 for xylene.

The above observations were made by classifying organisms according to

different groups. Additionally, the effect of each solvent on 25 OSTB was examined

individually as follows:

4.2.1.1. Effect of hexadecane

Theoretically, hexadecane with log P value 8.8 is comparatively less toxic

than other solvents used in the study. The results obtained in the study are in

congruence with this fact, as the numbers of survivors of each isolate are in the range

of few thousands, being highest among all solvents used in the study, with exception

for OSTB AK1882, AK39883, and AK39887, which were inhibited in the presence of

hexadecane [Fig. 17].

Fig. 17. Effect of hexadecane (8.8) at 50% (v/v) on growth of different OSTBs.



Iwabuchi et al., [2000] reported a mucoidal strain of Rhodococcus

rhodochrous resistant to 10% (v/v) n-hexadecane. However, in this study, 50% (v/v)

concentration of hexadecane was used, which was much higher than the reported one

indicating remarkable tolerance of isolated bacteria to hexadecane.

4.2.1.2. Effect of cyclooctane

Overall the number of survivors in presence of cyclooctane (log P value 4.5)

was in the range of few hundred at the end of seven days. All OSTB showed survivors

in the range of 150 to 300, with exception of AK1882, VK1901, AK2641, AK39313,

AK39883, and AK39887 which exhibited inhibitory effect of cyclooctane [Fig. 18].

Fig. 18. Effect of Cyclooctane (4.5) at 50% (v/v) on growth of different OSTBs.

According to the report of Inoue and Horikoshi [1989], Agrobacterium

tumefaciens IFO 3507, B. subtilis AHU 1219, and Corynebacterium glutamicum JCM

1318 strains were completely inhibited in the presence of cyclooctane.

4.2.1.3. Effect of hexane

Though the log P value of hexane is 3.9, number of survivors is just few

hundreds. OSTB AK1871, AK1872, AK39423, AK39881, and AK39885 showed



comparatively good growth with survivors above three hundred. On the other end,

OSTB AK1882, VK1901, AK2641, AK39313, AK39315, AK39532, AK39762,

AK39883, and AK39887 showed higher inhibition towards hexane with survivors

below hundred. OSTB AK1874, AK39422, AK39427, AK39531, AK39651,

AK39763, AK39765, AK39766, AK39673, AK39674 and AK39675 were moderately

inhibited by hexane [Fig. 19].

Fig. 19. Effect of Hexane (3.9) at 50% (v/v) on growth of different OSTBs.

Various reports on sensitivity and tolerance of bacteria to hexane are

identified. Inoue and Horikoshi [1989] reported inhibitory effect of hexane for

Agrobacterium tumefaciens IFO 3507, Alcaligenes faecalis JCM 1474, Aeromonas

hydrophila JCM 1027, B. subtilis AHU 1219, and Corynebacterium glutamicum JCM

1318, while, Ferrante et al., [1995] reported E. coli strain CAG18492 and KLE400

showing growth in presence of hexane by plate overlay method. Gupta et al., [2006]

also reported growth of Enterobacter aerogenes in presence of 20% (v/v) hexane.

Zahir et al., [2006] reported growth of Pseudomonas sp., Pseudomonas citronellolis,



Stenotrophomonas maltophilia, Burkholderia cepacia, Staphylococcus sp., Bacillus

cereus, and Bacillus sp. in presence of hexane at 1.3% (v/v) only. However, OSTB

studied in the present report exhibited excellent tolerance to hexane at 50% (v/v).

4.2.1.4. Effect of xylene

Xylene with log P value 3.1, was extremely toxic to the growth of OSTB.

Except strains AK1871 and AK1872, all other OSTB under study showed poor

number of survivors <50, while for some of the isolates, it was extremely toxic [Fig.

20].

Fig. 20. Effect of Xylene (3.1) at 50% (v/v) on growth of different OSTBs.

Inoue and Horikoshi [1989] reported strains, Pseudomonas putida IH-

2124TX, Pseudomonas putida IH-2124TXC, E. coli IFO 3806, P. fluorescens IFO

3507, Achromobacter delicatulus IAM 1433, Agrobacterium tumefaciens IFO 3507,

Alcaligenes faecalis JCM 1474, Aeromonas hydrophila JCM 1027, B. subtilis AHU

1219, and Corynebacterium glutamicum JCM 1318 showed no growth in presence of

xylene. Gupta et al., [2006] also reported that growth of Enterobacter aerogenes was

inhibited in presence of xylene at 20% (v/v) concentration.



In contradiction to the above mentioned results, Kadavy et al., [2000] reported

three out of nine strains of Providencia rettgeri tolerated overlayer of 1:1 ratio of

xylene:cyclohexane. Perhaps the tolerance of these strains can be attributed to its

source, gut of Helaeomyia petrolei (oil fly) larvae that inhabit the asphalt seeps of

Rancho La Brea in Los Angeles, California. Nielsen et al., [2005] reported

Staphylococcus haemolyticus isolated from oil fly larval gut that tolerated 100% plate

overlay and saturating levels of xylene.

Zahir et al., [2006] reported growth of Staphylococcus sp. and Pseudomonas

putida strain S12 in presence of xylene [1.2% (v/v)]. While growth of Pseudomonas

sp., Stenotrophomonas maltophilia, Burkholderia cepacia, Bacillus cereus was

inhibited in presence of xylene at 1.2% (v/v).

4.2.1.5. Effect of carbon tetrachloride

Carbon tetrachloride completely inhibited AK39313 and AK39532 and highly

inhibited AK1882, AK39883, AK39885 and AK39887 [Fig. 21].

Fig. 21. Effect of Carbon tetra chloride (2.7) at 50% (v/v) on growth of different OSTBs.



Remaining OSTB showed number of survivors in the range of 100 to 500 in

the presence of 50% (v/v) carbon tetrachloride. Ferrante et al., [1995] reported E. coli

strain CAG18492 and KLE400 showed no growth in presence of carbon tetra chloride

by plate overlay method.

4.2.1.6. Effect of benzene

AK39532 was completely inhibited by benzene, while AK1882, AK39313,

AK39883 and AK39887 were highly inhibited with a few survivors. Other OSTB

showed relatively good growth with number of survivors in the range of 200 to 450

[Fig. 22]. Inoue and Horikoshi [1989] reported inhibitory effect of benzene on the

growth of Pseudomonas putida IH-2000, Pseudomonas putida IH-2124T,

Pseudomonas putida IH-2124TX, Pseudomonas putida IH-2124TXC, E. coli IFO

3806, Pseudomonas putida IFO 3738, P. fluorescens IFO 3507, Achromobacter

delicatulus IAM 1433, Agrobacterium tumefaciens IFO 3507, Alcaligenes faecalis

JCM 1474, Aeromonas hydrophila JCM 1027, B. subtilis AHU 1219, and

Corynebacterium glutamicum JCM 1318. Gupta et al., [2006] reported inhibition of

growth of Enterobacter aerogenes in presence of benzene at 20% (v/v) concentration.

Fig. 22. Effect of Benzene (2.1) at 50% (v/v) on growth of different OSTBs.



Nielsen et al., [2005] reported that Staphylococcus haemolyticus, isolated from

oil fly larval gut, tolerated 100% plate overlay and saturating levels of xylene. Na et

al., [2005] reported three benzene utilizing bacteria that grew when liquid benzene

was added to the basal salt medium at 10-90% (v/v). Zahir et al., [2006] reported

growth of Staphylococcus sp. and Bacillus cereus in presence of benzene [1% (v/v)],

while it inhibited growth of Pseudomonas sp., Stenotrophomonas maltophilia, and

Burkholderia cepacia.

4.2.1.7. Effect of MTBE

OSTB AK39532 was completely inhibited while AK1882, AK39883 and

AK39887 showed number of survivors below 50. Remaining OSTB showed number

of survivors in the range of 200 to 500 [Fig 23].

Fig. 23. Effect of MTBE at 50% (v/v) on growth of different OSTBs.

4.2.1.8. Effect of butanol

OSTB AK1871 and AK1874 showed highest number of survivors in presence

of butanol as compared to other OSTB under study. OSTB VK1901, AK39315,



AK39423, AK39427, AK39531, AK39651, AK39762, AK39763, AK39765,

AK39766, AK39673, AK39674, AK39675 were moderately inhibited while AK1872,

AK1882, AK2641, AK39313, AK39422, AK39532, AK39881, AK39883, AK39885

and AK39887 were highly inhibited [Fig. 24].

Fig. 24. Effect of Butanol (0.8) at 50% (v/v) on growth of different OSTBs.

Gupta et al., [2006] also reported inhibition of growth of Enterobacter

aerogenes in presence of butanol at 20% (v/v) concentration.

4.2.1.9. Effect of acetone

Though acetone has the lowest log P value, AK1871 and AK1874 showed

higher tolerance with number of survivors around 400. VK1901, AK2641, AK39423,

AK39427, AK39531, AK39651, AK39763, AK39765, AK39766, AK39673,

AK39674 and AK39675 were moderately inhibited with number of survivors in the

range of 150 to 300. Isolates, AK1872, AK1882, AK39313, AK39315, AK39422,

AK39532, AK39762, AK39881, AK39883, AK39885 and AK39887 were highly

inhibited [Fig. 25].



Fig. 25. Effect of Acetone (-0.23) at 50% (v/v) on growth of different OSTBs.

In conclusion, present study indicated that most of the OSTB isolated in the

present study exhibited wide range of solvent tolerance at 50% (v/v) solvent

concentration. The study also revealed the fact that xylene was found to be the most

toxic solvent where as hexadecane showed the least toxicity followed by MTBE.

Similarly, amongst all the OSTB studied, Bacillus cereus AK1871 was identified as

the most organic solvent tolerant isolate followed by Bacillus sp. AK1874 and

Bacillus firmus AK39423. The most organic solvent sensitive isolates were Bacillus

sp. AK 1882, Bacillus megaterium AK39883 and Bacillus sp. AK39887. Thus,

Bacillus cereus AK1871 can be identified as a potential candidate for biocatalysis

reactions.

Biocatalysis using whole cells has emerged as an important tool in the

industrial synthesis of bulk chemicals, pharmaceuticals, and agrochemical

intermediates. However, the number of applications so far is rather restricted because

some factors such as strain stability, reduced production rates or yields, and narrow

substrate scope limit the number of applications [Shoemaker et al., 2003]. One



important limitation of biocatalysis is that many interesting reactions involve organic

components (substrates or products) that are poorly water soluble. Furthermore, in

some cases the productivity of the biocatalyst was decreased because of end product

inhibition [Van Sonsbeek et al., 1993]. The use of a second organic phase in

biotransformations has several advantages: if the product is continuously removed by

a solvent phase, its toxic effects will decrease and the biocatalyst will remain active; if

the concentration of the product increases in the organic phase, product recovery will

be easier and less costly [Bruce and Daugulis, 1991; Leon et al., 1998].

The isolation and identification of solvent-tolerant bacteria able to grow in the

presence of organic solvents may help to overcome some limitations in industrial

biotransformations and to expand the applications of biocatalysts. The use of solvent-

tolerant bacteria as whole-cell biocatalysts in double-phase systems is an interesting

new option for the production of toxic compounds with a low log Pow value because

these chemicals can be removed from the aqueous phase with the appropriate

solvents.

4.2.2. Antibiotic resistance pattern of OSTB

The role of environment in the emergence and spread of antibiotic resistant

bacteria and their possible pathways in which the environmental bacteria contribute to

the spread of resistance genes are not yet clear. The OSTB under study were

investigated for the incidence of multiple antibiotic resistance to different antibiotics

commonly used [Fig. 26].

B. firmus AK39531

B. licheniformis AK39762



B. cereus AK1871


B. pumilus AK39885

HiMedia Antibiotic Kit

Fig. 26. Antibiotic resistance pattern of few OSTBs.

4.2.2.1. Resistance pattern of individual isolate

Resistance pattern of individual OSTB against number of antibiotics is

depicted graphically in Fig. 27. B. licheniformis AK39762 showed resistance to 13

antibiotics, highest among all OSTB studied, followed by Bacillus sp. AK39427 and

Micrococcus indicus AK39766 showing resistance to 9 antibiotics. B. licheniformis

AK39422 and B. aquimaris AK39881 showed resistance to 7 antibiotics, while B.

cereus AK1871, B. licheniformis AK39763 and Staphylococcus arlettae AK39765

showed resistance to 6 antibiotics.



Fig. 27. Resistance pattern of individual isolate against number of antibiotics.

As evident from Fig. 28, 20 OSTB were resistant to ampicillin, 23 OSTB were

resistant to ceftazidime, and 24 OSTB were resistant to cloxacillin. Highest incidence

of antibiotic resistance was observed against ceftazidime, ampicillin, cloxacillin and

penicillin, followed by cefadroxil and ceftriaxone. Interestingly, these antibiotics

belong to Penicillins and Cephalosporins group of antibiotics. Thus, resistance to

Penicillin and Cephalosporin was widely observed among all the OSTB under study,

whereas lowest incidence of resistance was observed against amikacin, amoxycillin,

cefoperazone, chloramphenicol, ciprofloxacin, co-trimaxozole, erythromycin,

gentamicin, netilmycin, nitrofurantoin, norfloxacin and vancomycin. These antibiotics

belonged to Aminoglycosides, Glycopeptides, Macrolides, Nitrofurans, Quinolones

and Sulfonamides class of antibiotics. Thus, the OSTB under study were sensitive to

these classes of antibiotics.



Fig. 28. Numbers of resistant isolates against each antibiotics.

The resistance pattern of 25 OSTB against different class of antibiotics was

Penicillins > Cephalosporins > Quinolones > Aminoglycosides > Sulphonamides >

Macrolides, Nitrofurans, Others > Glycopeptides [Table 13].

On examination of the antibiotic susceptibility and resistance patterns of 25

bacteria obtained from six different sites by using 20 commonly used antibiotics,

following conclusions can be drawn from antibiotic resistance and susceptibility

patterns: (i) all OSTB are sensitive to antibiotics which inhibit protein synthesis,

inhibit DNA gyrase and mediate metabolic antagonism, (ii) they are resistant to

antibiotics that inhibit cell wall synthesis [Table 13].

The above results partly match with those reported by Sarita et al., [2005],

where highest incidence of antibiotic resistance was shown against ampicillin, while

lowest against chloramphenicol, gentamicin and amikacin.

Table 13. Resistance pattern of OSTB among different class of antibiotics.

Class Antibiotics Resistant OSTB

Aminoglycosides Amikacin

Gentamicin

Netilmycin

1

0

0



Tobramycin 4

Cephalosporins Cefadroxil

Cefoperazone

Ceftazidime

Ceftriaxone

5

2

23

10

Glycopeptides Vancomycin 0

Macrolides Erythromycin 1

Nitrofurans Nitrofurantoin 1

Penicillins Ampicillin

Amoxicillin

Cloxacillin

Penicillin

20

1

24

18

Quinolones Ciprofloxacin

Nalidixic acid

Norfloxacin

0

5

2

Sulphonamides Co-trimaxozole 3

Others Chloramphenicol 1

Antibiotic Resistance Index (ARI)

Antibacterial resistance index (ARI) of each sampling site was determined

using the formula ARI = y/nx, where y was the actual number of resistance

determinants recorded in a population of size n and x was the total number of

antibacterial agents tested for, in the sensitivity test.



Antibiotic resistance index (ARI) was lowest for Alang site (0.160). For other

sites (Veraval, Salt farm, Hindustan PP, Garden) it was in the range of 0.225 to 0.250.

However, ARI was found slightly high for Bharat PP (0.375) [Table 14].

Table 14. Multiple antibiotic resistance and Antibiotic resistance index

Site

No.

Location Total

isolates

Det

erm

inan

ts

Susc

epti

ble

Resistance

MA

R i

sola

tes

ARI

Clu

ster

I

Clu

ster

II

Clu

ster

III

1 Alang 5 16 1 2 2 0 2 0.160

2 Veraval 1 5 0 0 1 0 1 0.250

3 Salt farm 8 37 0 3 5 0 5 0.231

4 Bharat PP 4 30 0 0 3 1 4 0.375

5 Hindustan

PP

3 15 0 1 2 0 2 0.250

6 Garden 4 18 0 2 2 0 2 0.225

Cluster I – Contains isolates resistant to < 3 antibiotics, Cluster II – Contains isolates resistant

to 4-10 antibiotics, Cluster III – Contains isolates resistant to >10 antibiotics, MAR Group-

Contains isolates resistant to more than three antibiotics.

The OSTB obtained from hydrocarbon contaminated sites like Alang, Veraval

and two petrol pump are under stress of adaptation that is inherent in a solvent-rich

environment. Isken et al., [1999] reported P. putida S12 showed reduction of the

growth yield by 33% in the presence of solvents. This suggests energy-consuming

adaptation processes leading to reduction in the yield of the tolerant cells.

During adaptation, part of the energy burden was derived from a membrane-

associated organic solvent efflux system. The importance of this solvent efflux system

was evident from its ability to impart a solvent-resistant phenotype from solvent-

sensitive strains of P. putida [Kieboom et al., 1998b]. Such efflux systems are

generally involved in extrusion of hydrophobic molecules. Apart from this, they are

rather nonspecific in their substrate requirements [Nikaido, 1996], leading to the



expectation that a single efflux system may pump out both organic solvents and

antibiotics [Zgurskaya and Nikaido, 2000]. This expectation is fulfilled in the case of

P. putida where preculturing this bacterium in presence of toluene made it more

resistant to hydrophobic antibiotics [Isken et al., 1997]. In the present study, all the

OSTB were screened in presence of 10% (v/v) solvent, and later tested for resistance

against different antibiotics. The selection of solvent tolerant isolates and their gradual

acclimatization to solvent might have induced their solvent tolerance mechanism to

work continuously, resulting in better antibiotic resistance.

Based on the above observations, it was interesting to speculate that the

survival of various OSTB in their hydrocarbon contaminated environment depends on

the ability of the cells to pump out a wide variety of aromatic and polyaromatic

hydrocarbons. In a significant investigation, Li et al., [1998] reported that the

common efflux system for organic solvents as well as antibiotics in P. aeruginosa is

responsible for multidrug resistance. A similar correlation has been reported for E.

coli [Aono et al., 1995]. The present study also indicated that possibly, the same

mechanism might be functional in OSTB under study. This rationale is strengthened

when one considers that the enrichment process at various hydrocarbon contaminated

sites has maintained a constant selective pressure for organisms adapted to organic

solvents for long time [UNESCO, 2004]. The isolates from one of the petrol pump

have shown highest ARI indicating the constant pressure experienced by it. Whereas

isolates from Alang showed lowest ARI, the plausible reason might be the sample

being sea water, the toxicity of solvents in the prevailing environment gets diluted due

to dynamic condition of the sea. Additionally, in recent years the state pollution

control board is exercising strict environmental regulations to make ship breaking

activities a sustainable industry.

Regardless of the origins of multidrug resistance (MDR) strains, it is important

to understand the impact that solvent contamination of natural environments may

have on the development of these strains. In industrialized nations like India,

contamination of soils, groundwater, and surface water bodies by petroleum fuel spills

is very common. Additionally, limited resource availability and inadequate

enforcement of environmental laws increase the possibility of contamination by such

multi drug resistant microbes. [Brodkorb and Legge, 1992].



4.3. STUDIES ON SOLVENT TOLERANT PROTEASE

4.3.1. Screening of organic solvent tolerant protease producer

Six isolates, out of 25 organic solvent tolerant bacteria, exhibited high

protease activity on skim milk agar. The bacterial isolates showing high ratios of clear

zone diameter to colony diameter were selected as potential protease producers for the

subsequent experiments. The most promising isolate, Bacillus cereus AK1871 was

studied in detail.

4.3.2. Production of protease

The isolate B. cereus AK1871 cultured in Zobell Marine broth for 48 h at 35

°C and 120 rpm was centrifuged at 4 °C for 10000 rpm and 10 min. The supernatant

was used as crude protease for further study. Zobell marine broth was used as basal

media for studying effect of nutritional and physical factors on protease production.

4.3.3. Nutritional factors affecting protease production

4.3.3.1. Effect of carbon source on protease production

The ability of B. cereus AK1871 to utilize various carbon sources {1.0%

(w/v)} for protease production is as shown in Fig. 29. Maximum protease production

was obtained after 48 h incubation. The relative activity of media containing starch

was at par with basal media, followed by media containing arabinose and mannose

with relative activity in the range of 0.5 to 0.7. The media containing dextrose,

fructose, glycerol, lactose, sucrose showed relative activity as low as 0.2 as compared

to control, while almost no activity was observed in the presence of maltose and

sorbitol.

Low level of protease activity was observed in media containing carbon

sources like dextrose, fructose, glycerol, lactose, maltose, sorbitol and sucrose, which

indicate them, unsuitable for protease production by AK1871.

Presence of starch into the medium as a carbon source showed maximum

protease activity. Similar findings have been reported for B. licheniformis [Sinha and

Satyanarayana, 1991], Bacillus sp. JB-99 [Johnvesly and Naik, 2001] and B. cereus

BG1 [Ghorbel-Frikha et al., 2005]. Ghorbel-Frikha et al., [2005] reported highest



protease activity in presence of starch followed by maltose. Enzyme production was

significantly low when B. cereus strain was grown on lactose and saccharose,

respectively, and was the same as that of the control without carbon source. Rahman

et al., [2005] reported 3 times higher relative activity in media containing starch.

Naidu and Devi [2005] reported high protease activity in presence of wheat bran

followed by starch and sucrose.

B. cereus AK1871 protease is further shown to possess good solvent tolerance,

making it potential candidate for biocatalysis. Starch is considered to be a good

alternative for industrial protease production [Sonnleitner, 1983]. Since AK1871

showed good protease production in presence of starch, it appeared to favour

commercial production economical.

Fig. 29. The effect of carbon sources on protease production. Relative activity was calculated

on the basis of activity of protease in basal media as 1.00. Each value represents the mean of

three independent determinations. Error bars indicate the standard deviation.

Readily metabolized or utilized carbon sources in the media decreased or

inhibited protease synthesis due to catabolite repression. In the present study,

repression of protease of B. cereus AK1871 by glucose was observed which was also

supported by other researchers. For example, a similar observation was recorded in

the regulation of extracellular protease production [Sinha and Satyanarayana, 1991;

Johnvesly and Naik, 2001; Rahman et al., 2003]. On the contrary, there were reports,

where glucose stimulated protease production by Clostridium bifermentans

[Macfarlane and Macfarlane, 1992] and Bacillus sp. [Mehrotra et al., 1999]. Joshi et



al., [2007] reported that in the presence of fructose as a carbon source highest

protease activity was observed, while media containing starch exhibited the lowest

activity. Liu et al., [2010] reported maximum protease production in the presence of

glycerol followed by glucose through response surface methodology. Gupta and

Khare [2007] also reported glycerol (0.7%) as the best carbon source.

4.3.3.2. Effect of organic nitrogen source on protease production

The ability of B. cereus AK1871 to produce protease in liquid media was

examined in the presence of various organic nitrogen sources. Protease production

varied significantly from one organic nitrogen source to another. High protease

activity was detected after 48 h in the medium containing yeast extract which was at

par with basal medium [Fig. 30]. A similar trend was reported by Joshi et al., [2007]

and Rachadech et al., [2010] where media containing yeast extract showed high

protease activity, followed by peptone and tryptone. In addition to that, they reported

that a combination of yeast extract and peptone as source of organic nitrogen showed

highest activity. Takii et al., [1990] also reported enhanced protease production in

presence of yeast extract by Bacillus acidophilus subsp. halodurans. Gupta and Khare

[2007] also reported casein (0.4%) and yeast extract (0.6%) as the best nitrogen

sources.

Fig. 30. The effect of organic nitrogen sources on protease production. Relative activity was

calculated on the basis of activity of protease in basal media as 1.00. Each value represents

the mean of three independent determinations. Error bars indicate the standard deviation.



Naidu and Devi [2005] reported the presence of beef extract in production

media showed highest protease production followed by yeast extract, peptone and

tryptone. Whereas Rahman et al., [2005] reported that media containing casamino

acids, yeast extract and tryptone increased protease yield by 4.25-, 3.13- and 3.04 –

fold respectively, to that of the basal medium. Rai and Mukherjee [2010] and Liu et

al., [2010] also reported beef extract and casein as the best organic nitrogen source

through response surface methodology (RSM).

In majority of the microorganisms, both inorganic and organic nitrogen

sources are metabolized to produce amino acids, nucleic acids, proteins and cell wall

components. Although complex nitrogen sources were usually needed for protease

production, the requirement for a specific organic nitrogen supplement differs from

organism to organism. In this context, the nature of organic nitrogen sources greatly

influenced the production of the extracellular organic solvent-tolerant protease.

4.3.3.3. Effect of inorganic nitrogen source on protease production

Protease production was detected in medium containing an inorganic nitrogen

source [Fig. 31]. Among the inorganic nitrogen sources tested, ammonium nitrate

gave maximum protease production by B. cereus AK1871, 1.3 times, as compared to

basal medium after 48 h incubation whereas ammonium chloride and ammonium

sulfate yielded 0.3 to 0.4 times activity to that of the basal medium. This observation

suggested that complex nitrogen sources were not essential for protease production by

this bacterium. The present results are supported by the report of Hommu et al.,

[1993] where production of protease by Candida albicans was detected in the absence

of organic nitrogen sources. Similarly, production of alkaline protease from

thermophilic B. licheniformis was reported to be higher with inorganic nitrogen

sources such as ammonium sulfate and ammonium nitrate [Sinha and Satyanarayana,

1991].

Contradictory to this, Pansare et al., [1985] and Rahman et al., [2005] reported

inhibition of protease production in the presence of ammonium nitrate in Aeromonas

hydrophilia and P. aeruginosa strain K, respectively. Few other reports also indicated

low level of protease production in presence of inorganic nitrogen sources when used

as sole nitrogen sources [Rahman et al., 2003; Chaphalkar and Dey, 1994] and

indicated the requirement of organic nitrogen sources for better enzyme production by



Bacillus sp. [Keay and Wildi, 1970; Sen and Satyanarayana, 1993; Joo et al., 2002;

Rahman et al., 2003]. Thus, different reports are available on the effects of organic

and inorganic nitrogen sources on alkaline protease production by Bacillus spp.

Fig. 31. The effect of inorganic nitrogen sources on protease production. Relative activity

was calculated on the basis of activity of protease in basal media as 1.00. Each value

represents the mean of three independent determinations. Error bars indicate the standard

deviation.

4.3.3.4. Effect of amino acids on protease production

This experiment was carried out by supplementing the minimal medium with

amino acids and eliminating inorganic nitrogen source (ammonium sulphate). The

results indicated that protease activity was increased significantly when amino acids

were used as the sole nitrogen sources. Protease activity increased approximately 1.5

times in media containing arginine, glutamic acid and ornithine after 48 h incubation

while in the presence of glycine and lysine, the activity was at par with the basal

medium [Fig. 32].

Ikura and Horikoshi [1987] had observed that addition of certain amino

compounds were effective in enhancing the production of extracellular enzyme by

alkaliphilic Bacillus sp. Similarly, supplementation of basal medium with amino acids

was reported to increase the proteolytic activity of Serratia marcescens significantly

[Bromke and Venuti, 1999] and protease production by P. aeruginosa [Jensen et al.,



1980]. In contradiction to this, Rahman et al., [2005] reported that enzyme activity

was decreased dramatically when amino acids were used as the sole nitrogen sources.

Fig. 32. The effect of amino acids as nitrogen sources on protease production. Relative

activity was calculated on the basis of activity of protease in basal media as 1.00. Each value

represents the mean of three independent determinations. Error bars indicate the standard

deviation.

4.3.3.5. Effect of metal ion on protease production

Metal ions are required in the fermentation media for optimum production of

proteases. However, the requirement for specific metal ions depends on the sources as

well as property of enzymes. In the present study, it was observed that presence of

metal ions did not support protease production. On the contrary, metal ions such as

Co2+

, Fe2+

, Mg2+

, Mn2+

, K+, and Sr

2+ completely inhibited enzyme production [Fig.

33]. Jasvir et al., [1999] reported decrease in proteolytic activity in presence of both

Cu2+

and Zn2+

, while Mg2+

increased it marginally. Mabrouk et al., [1999] reported

adverse effect of Zn2+

on protease productivity by B. licheniformis ATCC 21415.

Rahman et al., [2005] reported that among the cations studied, Cs+, Ba

2+ and Sr

2+

completely inhibited enzyme production, while the presence of Fe3+

, Mn2+

and Li+

decreased proteolytic activity by more than 86% after 48 h incubation.



Fig. 33. The effect of metal ions on protease production. Relative activity was calculated on

the basis of activity of protease in basal media as 1.00. Each value represents the mean of


In similar lines, synthesis of extracellular protease by P. aeruginosa [Bjorn et

al., 1979] and P. fluorescens [McKellar et al., 1987] were enhanced at lower iron

concentration than that required for growth. Joshi et al., [2007] reported that enzyme

activity was stimulated in presence of Co2+

and Fe2+

.

4.3.4. Physical factors affecting protease production

4.3.4.1. Effect of inoculum size on protease production

The amount of inoculum used to culture the bacteria can affect the protease

production. The present study in this direction indicated that, protease production

gradually increased with an increase in inoculum size with optimum at 8.0% (v/v)

(A600 = c.a. 1.1) inoculum size [Fig. 34]. However, at 10% (v/v) inoculum size, there

was a decrease in the protease production by 9%. Therefore, high inoculum size might

not necessarily offer higher protease production. On the contrary, higher inoculum

size could result in decrease in oxygen level and nutrition depletion in media resulting

in lower enzyme production.



Fig. 34. The effect of inoculum sizes on protease production. Each value represents the mean

of three independent determinations. Error bars indicate the standard deviation.

Variations in optimum inoculum size have been reported by different workers

for different bacteria: 1.0% (v/v) for Bacillus sp. [Mehrotra et al., 1999], 4.0% (v/v)

for P. aeruginosa [Rahman et al., 2005], 5.0% (v/v) for B. licheniformis ATCC 21415

[Mabrouk et al., 1999] and 10.0% (v/v) for Bacillus sp. [Jasvir et al., 1999].

Therefore, different microorganisms required different cell mass in the form of

inoculum size for maximum protease yield.

4.3.4.2. Effect of pH on protease production

The effect of pH of the medium was studied on the protease production by B.

cereus AK1871. The results indicated that, protease production was optimum when

culture medium having pH 10 was used.

Previously, Moon and Parulekar [1991] reported that pH of the medium

strongly affects many enzymatic processes and transportation of various components

across the cell membrane. When ammonium ions were used in the media, the media

turned acidic, while it turned alkaline when organic nitrogen, such as amino acids or

peptides were consumed. The decline in the pH might be due to the production of

acidic products. In view of a close relationship between protease synthesis and the

utilization of nitrogenous compounds, pH variations during fermentation might

indicate kinetic information about protease production, such as the start and end of the

protease production period.



Maximum production of alkaline protease by another strain of B.

stearothermophilus was reported at pH 10.0 and 60 °C [Rahman et al., 2003]. In

contradiction, other researchers reported neutral pH to be optimum for protease

production in case of B. stearothermophilus [Kubo et al., 1988], P. aeruginosa

[Rahman et al., 2005], B. cereus [Joshi et al., 2007] and B. licheniformis [Rachadech

et al., 2010].

4.3.5. Enzyme purification and molecular weight

The profile of protease purification from B. cereus AK1871 is summarized in

Table 15. Approximately 58-fold purification of the crude enzyme was achieved with

a recovery of approximately 10.76% and specific activity of 406 U mg-1

. The elution

profile of ammonium sulphate precipitated protease through DEAE-cellulose column

is shown in Fig. 35. The elution profile of pooled ion exchange chromatographic

fraction of protease on Sephadex G-200 column is shown in Fig. 36. Purified protease

migrated as a single band on SDS-PAGE under reducing conditions, suggesting its

homogeneity with apparent molecular mass of the purified protease as 38 kDa [Fig.

37A]. Zymogram activity staining showed a band of clear zone of proteolytic activity

against the background [Fig. 37B].

Fig. 35. Elution profile of ammonium sulphate precipitated protease through DEAE-cellulose

column. The black line indicates protein concentration, whereas the dotted line indicates

enzyme activity.



Fig. 36. Elution profile of ion exchange chromatographic fractions of protease on Sephadex

G-200 column. The black line indicates protein concentration, whereas the dotted line

indicates enzyme activity.

Fig. 37. (A) SDS-PAGE of purified protease. Lane 1, molecular weight markers; Lane 2,

purified protease. (B) Substrate–PAGE of purified protease. Lane 1, purified protease (See

text for details).



Table 15. Purification profile of B. cereus AK1871 protease.

Purification step Total

activity

(U)

Total

protein

(mg)

Specific

activity

(U mg-1

)

Purification

fold

Recovery

(%)

Crude enzyme 6805.6 977.6 6.96 1.00 100

Ammonium

sulphate

precipitation

2620.8 23.0 113.94 16.37 38.51

DEAE ion

exchange

2052.4 7.6 271.48 39.00 30.16

Sephadex gel

filtration

732.6 1.8 406.09 58.34 10.76

Different researchers reported varying fold purification and recovery of

different molecular mass protease as follows: Gupta et al., [2005b] reported

purification of a solvent tolerant P. aeruginosa strain PseA protease by combination

of ion exchange and hydrophobic interaction chromatography using Q-Sepharose and

Phenyl Sepharose 6 Fast Flow matrix, respectively to achieve 11.6-fold purification

with 60% recovery. The apparent molecular mass based on SDS-PAGE was estimated

to be 35 kDa. Sana et al., [2006] reported purification by acetone precipitation, DEAE

ion exchange and Sephadex gel filtration chromatography which yielded 68-fold

purification with 11% recovery and specific activity of 791.7 U mg-1

. Rahman et al.,

[2006] purified an organic solvent-tolerant strain K protease to homogeneity by

ammonium sulphate precipitation and anion exchange chromatography which yielded

124-fold purification with 40% recovery and specific activity of 16460.67 U mg-1

.

The molecular mass of the purified enzyme as revealed by SDS-PAGE

electrophoresis was 51 kDa.

Karbalaei-Heidari et al., [2007] reported a metalloprotease secreted by the

moderately halophilic bacterium Salinivibrio sp. strain AF-2004 which was purified



to homogeneity by acetone precipitation followed by Q-Sepharose anion exchange

and Sephacryl S-200 gel filtration chromatography and yielded 12-fold purification

with 6% recovery and 116.8 U mg-1

specific activity. The apparent molecular mass of

the protease was 31 kDa by SDS-PAGE. Sareen and Mishra [2008] purified protease

by using affinity chromatography with α-casein agarose resin that resulted in 55%

yield and 85-fold purification with specific activity of 2983 U mg−1

. An apparent

molecular weight of protease was 55 kDa. Rai and Mukherjee [2009] reported 12.6-

fold purification of protease with 25% recovery and 2650 U mg-1

specific activity. It

showed molecular mass of 33.1 kDa.

Divakar et al., [2010] purified protease by ammonium sulphate precipitation,

ion exchange chromatography and gel permeation chromatography yielded 53.4-fold

purification with 32% recovery and 1004 U mg-1

specific activity having 67 kDa

molecular weight. Gaur et al., [2010] purified aminopeptidase with 11.9-fold

purification and 38% recovery from a solvent tolerant strain, P. aeruginosa PseA, by

ion-exchange chromatography resulting in a protease having molecular weight of

56 kDa. Rai and Mukherjee, [2010] purified protease by CM-cellulose, DEAE-

Sephadex A50, acetone precipitation and RP-HPLC to yield 23.5-fold purification

with 29% recovery and 5000 U mg-1

specific activity.

4.3.6. Characterization of protease

4.3.6.1. Effect of pH on activity of purified enzyme

Fig. 38 illustrates the relative protease activity at different pH values ranging

from 5.0 to 11.0. The purified protease exhibited activity over a broad range of pH,

6.0–9.0, with optimum activity at pH 8.0 and about 80% activity at pH 7.0 and 9.0.

At pH 10.0, the activity was drastically reduced to only 20% which was ca. 30% at

pH 5.0.



Fig. 38. Effect of pH on protease activity. The buffers used were 0.1 M citrate buffer (pH 5.0–

6.0), 0.2 M Tris–HCl buffer (pH 7.0–9.0) and 0.2 M Glycine–NaOH buffer (pH 10.0–11.0).

The activity at pH 8.0 is taken as 100%. Each value represents the mean of three independent

determinations. Error bars indicate the standard deviation.

Organic solvent-stable proteases from P. aeruginosa PST-01 [Ogino et al.,

1999], P. aeruginosa PseA [Gupta et al., 2005] and B. cereus BG1 [Ghorbel et al.,

2003; Xu et al., 2010] were reported to have optimal pH between 8.0 and 9.0 while

activity was completely lost at pH values over 10.0. Organic solvent-stable alkaline

proteases producing B. licheniformis [Li et al., 2009] and P. putida [Singh et al.,

2011] exhibited activity over a wide range of pH i.e. from 8.0 to 12.0 with optimum at

pH 9.5.

4.3.6.2. Effect of temperature on activity of purified enzyme

The purified protease exhibited activity over a wide temperature range of 40

°C to 70 °C, optimum being at 60 °C as observed in Fig. 39. It retained almost 70%

and 60% activity at 50 °C and 70 °C, respectively. The observation here is in

agreement with the report of Reddy et al., [2008], where organic solvent and

detergent tolerant protease from Bacillus sp. RKY3 having same temperature optima

is described.



Fig. 39. Effect of temperature on protease activity. The purified enzyme was incubated with

the substrate at different temperatures. The activity at 60 °C has been taken as 100%. Each

value represents the mean of three independent determinations. Error bars indicate the

standard deviation.

Ghorbel et al., [2003] also have reported protease from B. cereus having

temperature optima of 60 °C in the presence of Ca2+

which otherwise was 50 °C. Li et

al., [2009] and Divakar et al., [2010] reported optimum temperature of 60 °C. Higher

temperature optima of 70 °C for protease of Pseudomonas sp. is reported by Rahman

et al., [2006] and Gupta et al., [2010] whereas lower temperature optima of 45 °C

[Rahman et al., 2007; Rai and Mukherjee 2010] and 50 °C [Sareen and Mishra 2008;

Xu et al., 2010] are also reported.

4.3.6.3. Effect of sodium chloride on activity of purified enzyme

The enzyme showed optimum activity in the absence of sodium chloride but it

could tolerate 0.5 M NaCl with 65% relative activity. Higher concentration of NaCl

inhibited protease activity [Fig. 40]. Karbalaei-Heidari et al., [2007] reported a

metalloprotease secreted by the moderately halophilic bacterium Salinivibrio sp.

strain AF-2004 which showed optimum activity in presence of salinity ranging from

0-0.5 M NaCl. While Ruiz et al., [2007] reported an extracellular protease producing

haloalkaliphilic archaeon, Natrialba magadii, which is active in presence of 1.5 M



NaCl. Joshi et al., [2007] reported solvent tolerant protease that retained 100%

relative activity at 5% salt concentration.

Fig. 40. Effect of NaCl on activity of protease. Percentage relative activity has been

calculated on the basis of activity of protease without NaCl (100%). Each value represents

the mean of three independent determinations. Error bars indicate the standard deviation.

4.3.6.4. Effect of metal ions on activity of purified enzyme

The effect of various metal ions (final concentration 5 mM) on activity of

enzyme was studied and the results are shown in Table 16. Ca2+

increased the activity

of enzyme by 50%, while Ba2+

, K+, Mg

2+, Li

+ and Mn

2+ ions did not show either

positive or negative effect on the enzyme activity. Cr3+

, Cd2+

, Zn2+

, Cu2+

, Hg2+

and

Pb2+

suppressed the enzyme activity considerably.

Various reports on effect of metal ions on protease activity suggested

enhancement in activity in presence of Ca2+

and Mg2+

, while drop in activity in

presence of Co2+

, Ni2+

, Cu2+

, Zn2+

and Hg2+

[Ghorbel et al., 2003, Gupta et al., 2005;

Sana et al., 2006; Sareen and Mishra, 2008; Reddy et al., 2008; Xu et al., 2010;

Divakar et al., 2010; Rachadech et al., 2010]. Similar trend was observed in the

present study where increase in the B. cereus AK1871 protease activity in the

presence of Li+, Ca

2+ and Mg

2+ (s-block metals) and reduction in presence of Cr

3+,

Mn2+

, Co2+

, Ni2+

, Cu2+

, Zn2+

, Cd2+

and Hg2+

(d-block element) was noted. Generally,

s-block metals bind poorly to ligands and form mainly ionically bound complexes



with donor ligands. As the bonding is mainly ionic, the metal ions are easily

displaced. Usually d-block elements preferentially bind to ligands to give stable

complexes through covalent bonds [Duffus, 2002] and hence the enzyme gets

irreversibly bound leading to poor activity.

Table 16. Effect of metal ions on the enzyme activity.

Metal ions

(5 mM)

Relative enzyme

activity (%)

Metal ions

(5 mM)

Relative enzyme

activity (%)

None 100 Mixturea 21.2 ± 0.9

Ba2+

(BaCl2) 97.3 ± 4.8 Ca2+

(CaCl2) 147.8 ± 6.6

Cd2+

(CdCl2) 17.7 ± 0.7 Co2+

(CoCl2) 78.8 ± 2.7

Cr2+

(CrCl3) 8 ± 0.3 Cu2+

(CuCl2) 6.2 ± 0.18

K+ (KCl) 92.9 ± 5.6 Hg

2+ (HgCl2) 1.8 ± 0.08

Mg2+

(MgCl2) 108 ± 3.4 Li+ (LiCl) 101.8 ± 4.8

Ni2+

(NiCl2) 61.9 ± 2.8 Mn2+

(MnCl2) 91.1 ± 3.8

Zn2+

(ZnCl2) 20.3 ± 1.1 Pb2+

(PbCl2) 37.2 ± 1.5

Each value represents the mean of three independent determinations. (±) Standard deviation.

a Mixture of Ba

2+, Ca

2+, Cd

2+, Co

2+, Cr

2+, Cu

2+, Fe

2+, Hg

2+, K

+, Li

+, Mg

2+, Mn

2+, Ni

2+, Pb

2+,

Zn2+

.

Similar effects have earlier been demonstrated wherein the activation was

increased with an increase in the ionic radii of the cation [Huheey, 1992]. Ca2+

has the

largest ionic radii (0.099 nm) among the divalent metal ions studied, whereas ionic

radii for other ions like Mn2+

, Zn2+

, Cu2+

, and Mg2+

are 0.082 nm, 0.075 nm, 0.073

nm and 0.072 nm, respectively. In spite of small ionic radii of Mg2+

, its activation

effect on the enzyme activity is in agreement with the results of Towatana et al.,

[1999]. Another reason for an increase in activity in the presence of Ca2+

might be due

to stabilization of enzyme in its active conformation by acting as an ion bridge via a

cluster of carboxylic groups and thereby maintaining the rigid conformation of the

enzyme molecule [Sareen and Mishra, 2008; Strongin et al., 1978].



A novel serine protease with respect to metal ion requirement was reported by

Rai and Mukherjee [2009], where it had a special requirement for Fe2+

ion.

Additionally the enzyme activity increased 4- and 1.5-fold of its original activity in

presence of Fe2+

and Zn2+

ions.

4.3.6.5. Effect of inhibitors on activity of purified enzyme

As observed in Table 17, effect of specific protease inhibitors on enzyme

activity is evident. The activity of protease was marginally affected in the presence of

alkylating agent like iodoacetamide and a ligand like o-phe. Its activity was

unaffected in the presence of metal chelator like EDTA which indicated that the

enzyme is metal independent. Moreover, the enzyme activity was unaffected by the

cocktail of Bestatin hydrochloride (an aminopeptidase and metalloprotease inhibitor),

pepstatin A (reversible acid protease inhibitor) and E-64 (a non-competitive

irreversible cysteine protease inhibitor), whereas it showed considerable inhibition in

presence of PMSF, which is an irreversible serine protease inhibitor. This indicated

that protease of the present study is a serine protease.

Table 17. Effect of various protease inhibitors on protease activity

Inhibitors Concentration (mM) Relative enzyme activity (%)

None - 100

EDTA 5 107.2 ± 4.8

1, 10 Phenanthroline 5 77.5 ± 3.9

Urea 5 57.7 ± 2.65

Iodoacetamide 5 82 ± 2.9

PMSF 5 16.2 ± 0.6

Cocktaila 1% (v/v) 103.6 ± 4.3


a Cocktail components: AEBSF, Bestatin hydrochloride, Leupeptin, Pepstatin A, o-Phe.



Among various Bacillus spp. studied, two types of solvent tolerant protease

have been reported, metalloproteases [Gupta et al., 2005b; Xu et al., 2010] and serine

proteases [Reddy et al., 2008; Sareen and Mishra, 2008, Rai and Mukherjee, 2010].

4.3.6.6. Effect of detergents, oxidizing, reducing and bleaching agents on

activity of purified enzyme

In the presence of non-ionic detergents like Tween 80, protease activity was

increased by 25%, whereas reverse trend with 15% decrease was observed with Triton

X-100 [Table 18]. Additionally, cationic and anionic detergents like CTAB and SDS

significantly reduced the protease activity by 80% and 55%, respectively. The

presence of commercial detergents, Surf excel, Ariel and Tide reduced the protease

activity drastically by 98%, 75% and 45%, respectively. The stability of any enzyme

is influenced by the ingredients of the detergents, such as surfactants particularly the

anionic surfactants, sequestrates, bleaching agents and stabilizers [Stoner et al., 2004;

Mukherjee et al., 2009]. Therefore, loss of protease activity of B. cereus AK1871 in

some of the detergents may be attributed to inhibitory effect(s) of component(s) of

these detergents. In spite of such inhibitory effects, Rai and Mukherjee, [2009]

reported that Alzwiprase demonstrated significant stability and compatibility with all

the tested commercial laundry detergents making it an ideal candidate for use in

laundry detergent.

The protease of the present study was marginally affected by the presence of

1% non-ionic detergents like Triton X-100 and Tween 80, whereas, SDS (anionic)

exhibited inhibitory effect. These results are in agreement with the reported proteases

from Pseudomonas as well as Bacillus spp. [Gupta et al., 2005; Sareen and Mishra,

2008; Reddy et al., 2008; Rai and Mukherjee, 2009; Divakar et al., 2010; Rai and

Mukherjee, 2010]. This effect of detergent on the enzyme can be correlated to their

hydrophilic/lipophilic balance (HLB), which is defined as the way a detergent

distributes between polar and non polar phases [Furth, 1980]. Triton X-100 with HLB

of 13.5 is less detrimental as compared to SDS with a HLB of 40. Besides, the

protease of the present study was stable in the presence of oxidizing and bleaching

agent like hydrogen peroxide which is in agreement with the reports of Sana et al.,

[2006] and Reddy et al., [2008].



Table 18. Effect of detergents, oxidizing, reducing and bleaching agents on protease activity.

Additives Concentration Relative enzyme activity (%)

None - 100

Triton X-100 1% (v/v) 84.7 ± 3.3

Tween 80 1% (v/v) 125.2 ± 4.5

CTAB 5 mM 18 ± 0.6

SDS 5 mM 46.8 ± 1.9

Tide 1% (w/v) 55 ± 2.4

Surf excel 1% (w/v) 1.8 ± 0.06

Ariel 1% (w/v) 26.1 ± 1.0

Hydrogen peroxide 1% (v/v) 103.6 ± 4.2

Sodium tetraborate 5 mM 49.6 ± 2.0

Ammonia 1% (v/v) 40.7 ± 1.7

Glutathione 5 mM 84.68 ± 3.2


Protease activity was reduced marginally by 15% with reducing agent,

glutathione, while the enzyme retained its original activity in presence of oxidizing

and bleaching agent, hydrogen peroxide. Enzyme activity dropped to almost half in

presence of a weak disinfectant, sodium tetra borate and an antimicrobial agent,

ammonia solution.

4.3.6.7. Effect of organic solvents on activity and stability of purified

enzyme

In the presence of water immiscible solvents except butanol, the protease

activity increased as compared to water miscible solvents. Here, in the presence of

decane, hexadecane and hexane, the protease activity was higher as compared to



control, throughout the period of incubation (144 h). In case of cyclooctane and

toluene, the activity was higher than the control, until 1 h of incubation, which was at

par with control on further incubation whereas in case of benzene, enhanced activity

was observed after 1 h and then marginal decrease was observed on further

incubation. On the contrary, the protease activity was decreased in the presence of

water miscible solvents like ethanol and DMSO with about 70% and 80% activity,

respectively, after 1 h incubation [Fig. 41].

The present study indicated that the purified protease was stable in many non

polar (water immiscible) solvents, throughout the period of incubation as compared to

polar (water miscible) solvents. Reddy et al., [2008] reported marginal increase in the

activity in presence of benzene, hexane and toluene which is in concurrence with the

present report. Similarly, report of Xu et al., [2010] also supported the present data by

indicating retention of more than 90% of activity of protease after 24 h as compared

to the control in the presence of hydrophobic and most hydrophilic solvents.

Fig. 41. Effect of organic solvents on activity and stability of purified protease. Purified

protease was incubated at 30 ◦C with constant shaking in the absence or presence of various

solvents at 33% (v/v) for 144 h. Relative activity was calculated on the basis of activity of

protease without solvent as 100. Each value represents the mean of three independent

determinations. Error bars indicate the standard deviation.



On the contrary, Geok et al., [2003], Rahman et al., [2006] and Ogino et al.,

[1999] reported inactivation of protease in the presence of benzene, toluene, xylene

and hexane and enhancement in activity of protease in the presence of hexadecane

and decane [Geok et al., 2003; Rahman et al., 2006]. Protease stability in the presence

of water miscible solvents like ethanol, acetone and DMSO is reported by Sana et al.,

[2006], while inactivation is reported by Tang et al., [2008] and Li et al., [2009],

except DMSO which did not show any adverse effect on protease activity. In the

present study also, protease activity was reduced significantly (40%) in the presence

of ethanol and by 20% in the presence of DMSO after 1 h of incubation. Usually,

presence of organic solvent reduces the structural flexibility of enzyme which is

required for optimal catalysis. Here, the activation of protease in the presence of

organic solvents indicates the ability of enzyme to resist denaturation by formation of

multiple hydrogen bonds with water for structural flexibility and conformation

mobility [Klibanov, 2001]. DMSO serves as a highly solvating organic media for

homogenous organic-aqueous mixtures to catalyze kinetic and equilibrium-controlled

synthesis [Bordusa, 2002]. Thus, the stability of this protease in organic solvents of

log P values ranging from 2.0 to 8.8 and having 80% activity in DMSO (-1.35) up to

1 h, suggest its probable application in peptide synthesis. The crude protease from B.

sphaericus exhibited remarkable solvent stability and retained most of the activity at

least up to 14 days at 37 °C in the presence of various organic solvents at 25% (v/v)

concentration [Fang et al., 2009]. According to them, more than 80% activity was

recovered when the log P value of organic solvents were from 1.8 to 3.5, whereas in

methanol, ethanol, and 1-butanol the residual activity was 35%, 36%, and 42%,

respectively. However, when n-decane, octane, isooctane, and heptane, having log P

values around 4.0 were added, the activities of the protease were enhanced.

Li et al., [2009] reported a protease able to retain more than 80% stability in

presence of various solvents (decane, heptanes, cyclohexane, octanol, toluene,

benzene, butanol, acetone, DMF and DMSO) after 1 h of incubation. Rai and

Mukherjee [2009] also reported protease that retained more than 90% of original

activity even after pre-incubation for 10 days at 25 °C in presence of 20% (v/v) of

different solvents like hexane, xylene, methanol, propanol, acetonitrile and ethanol.

When protease is used in kinetic- and equilibrium-controlled synthesis, the use

of homogeneous aqueous-organic mixtures with highly solvating organic media such



as DMF, DMSO, acetonitrile, or MeOH is a preferred approach [Bordusa, 2002]. The

solvent-stable protease produced by Pseudomonas aeruginosa PST-01 has been

reported to catalyze peptide synthesis in monophonic aqueous-organic solvent

systems; the equilibrium yield of Cbz–Arg–Leu–NH2 increased with an increase in

the concentration of DMF or DMSO [Ogino et al., 2000].

From the results obtained in present study where the activity of B. cereus

AK1871 protease was exceptionally high even after it was subjected to various

solvents at 50% (v/v) concentration. With such stability in a wide range of solvents,

including DMSO, the given protease makes it an ideal catalyst for kinetic- and

equilibrium-controlled synthesis.

4.3.6.8. Substrate specificity of enzyme

Protease showed specificity towards casein, as compared to bovine serum

albumin and wheat gluten where the activity was only 20% as compared to casein.

Divakar et al., [2010] reported protease from Aeromonas veronii that exhibited the

highest activity towards casein; however it exhibited 44 and 82% relative activities,

when gelatin and BSA were used as substrates, respectively. Similarly, alkaline serine

proteases from B. stearothermophilus strain F1 [Rahman et al., 1994] and

metallokeratinase from B. subtilis strain PE1 [Adinarayana et al., 2003] were reported

to exhibit their highest activity towards casein. Sana et al., [2006] reported wheat

gluten showed meagre activity, while BSA showed half the activity with respect to

casein.

4.4. STUDIES ON SOLVENT TOLERANT LIPASE

4.4.1. Screening of organic solvent tolerant lipase producer

The bacterial isolates showing high ratios of clear zone diameter to colony

diameter were selected as potential lipase producers for the subsequent experiments.

Eight OSTB (T. halophilus AK39315, B. pumilus AK39651, B. licheniformis

AK39762, B. flexus AK39763, B. subtilis AK39765, M. indicus AK39766, B.

megaterium AK39883, B. pumilus AK39885) produced lipase out of twenty five

OSTB which were isolated from various sites.



4.4.2. Optimum lipase production

As observed in Fig. 42, among the eight OSTB studied, B. licheniformis

AK39762, B. flexus AK39763, B. subtilis AK39765, M. indicus AK39766 showed

comparatively high lipase activity (ranging from 0.8 U mg-1

to 1.3 U mg-1

). The lipase

activity peaked at 72 h of incubation and longer incubation showed drop in the

activity.

Fig. 42. Optimum lipase production among eight OSTB was observed every 24 h during the

period of incubation.

Ahmed et al., [2010] reported maximum lipase activity of 2.35 U mg-1

on the

third day of production. The increase in lipase activity was negligible on the fourth

day, and after the fourth day, decline in lipase activity was observed. The decrease of

lipase production at the later stage could be possibly due to pH inactivation,

proteolysis, or both. A similar report of maximum lipase activity on the third day of

fermentation has also been reported from Bacillus licheniformis B 42 [Bayoumi et al.,

2007] and P. aeruginosa [Mahanta et al., 2008]. While Dandavate et al., [2009]

reported the maximum lipase activity (1.76 U mg-1

) was found in liquid culture of

Burkholderia multivorans BMV2 on 6th day of incubation. The lipase activity

decreased significantly to about 0.23 U mg-1

which might be attributed to proteolytic

degradation.



4.4.3. Effect of different oils on lipase production

Four OSTB, B. licheniformis AK39762, B. flexus AK39763, B. subtilis

AK39765 and M. indicus AK39766, out of eight showing high lipase activity were

further studied for effect of different oils in the medium on lipase production [Fig.

43]. The lipase activity for B. licheniformis AK39762 was comparatively higher when

cultivated in the presence of castor oil, coconut oil, cotton seed oil and groundnut oil

at 48 h of incubation where as the lipase production in presence of Jatropha oil, Jojoba

oil and olive oil along with control (without any oil) peaked at 72 h, but was lower

than the remaining four oils mentioned earlier.

Fig. 43. Effect of different oils on B. licheniformis AK39762, B. flexus AK39763, B. subtilis

AK39765 and M. indicus AK39766 lipase production.

The lipase activity for B. flexus AK39763 was comparatively higher when

grown in the presence of castor oil, cotton seed oil, groundnut oil, Jojoba oil and olive



oil at 48 h of incubation. The lipase activity for B. subtilis AK39765 was highest in

presence of Jatropha oil at 72 h of incubation. M. indicus AK39766 showed highest

lipase production in presence of Jojoba oil at 72 h of incubation. In conclusion, for

each of the four selected OSTB, lipase production was induced either by coconut oil,

groundnut oil, Jatropha oil, or Jojoba oil in the production medium.

Dandavate et al., [2009] reported olive oil as the best substrate for lipase

production by Burkholderia multivorans strain BMV2 in comparison to groundnut oil,

castor oil and corn oil. This suggests that lipase produced by BMV2 had specificity

towards longer chain fatty acid as compared to short chain fatty acids. Uttatree et al.,

[2010] reported meagre variation in lipase production in the media containing olive

oil, corn oil, sesame oil, camellia tea oil, safflower oil, canola oil, sunflower oil,

coconut oil, soybean oil, refined rice bran oil, palm oil and tributyrin, interpreting that

the strain Acinetobacter baylyi produced constitutive lipase. Kanjanavas et al., [2010]

reported 7 times higher relative activity in presence of coconut oil as compared to

olive oil.

4.4.4. Effect of organic solvent on lipase activity and stability

OSTB (B. licheniformis AK39762, B. flexus AK39763, B. subtilis AK39765

and M. indicus AK39766) showing high lipase activities were studied for solvent

tolerance in highly toxic solvent, DMSO (log P value -1.35) at 50 % (v/v)

concentration [Fig. 44]. Relative activity was measured by the standard assay method

at regular intervals.

Fig. 44. Effect of DMSO on lipase activity and stability. Each value represents the mean of




As observed in Fig. 44 B. flexus AK39763 lipase could tolerate presence of

solvent for a longer period with gradual decrease in the activity from 90% to 65%

from 0 h to 96 h respectively. Further reduction in activity was observed with time,

retaining about 35% relative activity after 144h. B. subtilis AK39765 and B.

licheniformis AK39762 lipase lost their activity in presence of DMSO at 0 h,

immediately after addition of solvent, and after 24 h, respectively. M. indicus

AK39766 lipase showed 70% relative activity at 0 h, while it showed constant 40%

relative activity during the entire period of incubation. As AK39763 showed higher

solvent stability for prolonged period, it was chosen for further studies on solvent

tolerance against different solvents.

Fig. 45. Effect of different organic solvents on AK39763 lipase activity and stability. Each

value represents the mean of three independent determinations. Error bars indicate the

standard deviation.

Based on the maximum tolerance of lipase towards organic solvent, lipase of

B. flexus AK39763 was extensively studied for solvent tolerance across the log P

range comprising aliphatic, alicyclic, aromatic, ether, alcohol, ketone, and chlorinated

class of hydrocarbons [Fig. 45]. Each solvent was used at 50 % (v/v) concentration.

Activity was measured at regular intervals by the standard assay procedure and

relative activity was calculated with respect to control at zero hour as 100.



Interestingly, lipase of B. flexus AK39763 remained stable in presence of polar

solvents [butanol (0.8), MTBE (0.9), acetone (-0.23) and DMSO (-1.35)], while in

presence of non-polar solvents [hexane (3.9), xylene (3.1), carbon tetrachloride (2.7)

and benzene (2.1)] the activity was lost immediately. In the presence of hexadecane

(8.8) and cyclooctane (4.5), the stability was lost with prolonged incubation time. .

Lipases are diverse in their sensitivity to solvents, but there is general

agreement that polar (water miscible) solvents are more destabilizing than non-polar

solvents [Cardenas et al., 2001; Castro-Ochoa et al., 2005; Dandavate et al., 2009]. It

is reported that polar solvents strip off the essential water molecules from the active

site of enzymes. For this reason, use of polar solvents is avoided and non polar

solvents are more often employed in non-aqueous enzymology. Thereby, suitable

performance of enzymes in non-polar solvents has been established in different

biocatalytic processes [Zaks and Klibanov, 1985; Smallwood, 1996]. However, the

availability of lipases that are active and stable in polar solvents would open up new

opportunities in biocatalysis with polar substrates. The polar solvent therefore appears

promising for catalysis in low water medium.

Instability of lipases in aprotic polar solvents is frequently associated with the

stripping of water from the protein surface [Azevedo et al., 2001], along with solvent

penetration into the enzyme, leading to protein unfolding and subsequent denaturation

[Wangikar et al., 1997]. There are only few reports showing the stability of lipases in

aprotic polar solvents.

Ji et al., [2010] reported the lipase activity to be more than 90% in presence of

DMSO at 25% (v/v) concentration after 48 h of incubation. In the present study,

AK39763 lipase showed increased lipase activity of 107% at 0 h in presence of

DMSO at 50% (v/v) concentration. With increase in incubation time to 408 h, the

activity was reduced to 45%.

Uttatree et al., [2010] reported 60% relative lipase activity after 12 h

incubation in 50% butanol. Better results were obtained in the present study where

the AK39763 exhibited 56% relative lipase activity with 50% (v/v) butanol even after

24 h of incubation. It has been reported use of butanol as co-solvent for biodiesel

production could improve the ester yield [Royon et al., 2007]. Thus, the stability in

alcohol makes lipase from AK39763 an attractive contender for further application in



biodiesel production. Leščić et al., [2001] also reported stability of lipase of

Streptomyces rimosus in 50% (v/v) of acetone.

Gaur et al., [2008b] reported solvent tolerant lipase stable in polar (DMSO,

methanol, ethanol and isoporpanol) and non polar (benzene, toluene, xylene,

cyclohexane, hexane, n-heptane, isooctane, decane and tetradecane) solvents at 25%

(v/v) concentration for 24 h.

Different reports on stability of lipase in non polar solvents are known. Hun et

al., [2003] reported lipase activity was enhanced by n-hexane and p-xylene by 3.5 and

2.9-folds, respectively, while it lowered with DMSO and got inactivated with

hexadecane after incubating at 25% (v/v) solvent concentration for 30 min. Fang et

al., [2006] reported solvent tolerant lipase stable in presence of 25% (v/v) p-xylene,

benzene, toluene, and hexane, while the activity dropped considerably in presence of

methanol and ethanol at the end of 30 min incubation.

Dandavate et al., [2009] reported BMV2 lipase which was stable in n-hexane

up to 24 h with about 97.8% activity which was further reduced to about 53.19% after

48 h of incubation. Whereas, the lipase of the present study showed 35% activity at

the end of 24 h which further dropped to 30% at the end of 48 h.

The 50% stability of AK39763 lipase in hexadecane throughout the period of

incubation can be explained as interaction of organic solvent molecules with

hydrophobic amino acid residues present in the lid of enzyme that covers the catalytic

site of the enzyme, thereby maintaining the lipase in its open conformation for

catalysis [Doukyu and Ogino, 2010]. Cadirci and Yasa [2010] reported stability of

lipase in non-polar solvents such as benzene, styrene, toluene, hexane and heptanes at

the end of 2 h incubation.

The stability of lipase in non polar solvent is also explained by the fact, that

the solvent may modify the oil–water interface to make enzymatic action easier

without causing protein denaturation. In addition to that, enhancement in enzyme

activity could be due to disaggregation of lipase and solvents may induce some

structural changes in the enzyme.

In entirety, the stability of enzymes was suggested to be influenced by the

solvent polarity; however, correlations between a simple parameter such as log P and



an even more complicated factor such as denaturation capacity, can never exactly

predict the effects of solvents on enzymes in general. There are large individual

variations among enzymes and no particular trend of the inactivating effect of the

organic solvents towards enzymes [Aldercreutz, 1996; Ghatorae et al., 1994; Geok et

al., 2003] was observed.

4.4.5. Effect of pH on lipase activity

The effect of pH on lipase activity of four OSTB (B. licheniformis AK39762,

B. flexus AK39763, B. subtilis AK39765 a nd M. indicus AK39766) is described

below:

Fig. 46. Effect of pH on B. licheniformis AK39762, B. flexus AK39763, B. subtilis AK39765

and M. indicus AK39766 lipase. Error bars indicate the standard deviation.

As observed in Fig. 46, the optimum pH of B. licheniformis AK39762, B.

flexus AK39763 and B. subtilis AK39765 is 9.0 and the optimum pH of M. indicus

AK39766 is 8.0. The lipase activity are highly pH dependent, and any alteration in the

pH of the reaction mixture is likely to affect the catalytic potential. The pH influences

the structure of proteins and hence governs their catalytic activity [Shah et al., 2007].

The optimum pH for lipase activity of B. subtilis EH 37 was reported to be 8.0, and it

retained 90% of its maximum activity at pH 9.0 [Ahmed et al., 2010b]. The data is in

agreement with literature information suggesting that Bacillus lipases generally have

pH optima in the range of 7.0–9.0 [Nawani and Kaur, 2007].



Rahman et al., [2005] purified an organic solvent-tolerant S5 lipase from

Pseudomonas sp. which had a pH optimum of 9.0. Zhang et al., [2009] cloned,

sequenced, and over expressed a novel lipase gene from an organic solvent degrading

strain Pseudomonas fluorescens JCM5963 as an N-terminus His-tag fusion protein in

E. coli. The recombinant lipase (rPFL) had optimum pH of 9.0.

Sulong et al., [2006], Gaur et al., [2008b] and Zhao et al., [2008] reported the

pH optima of purified lipase from Bacillus sphaericus, Pseudomonas aeruginosa,

Serratia marcescens to be 8.0, respectively.

The major limitation of p-nitrophenyl ester-based assay is that the lipase

activity could be quantified colorimetrically at neutral or at moderately alkaline

pH. Lipase- catalyzed reactions cannot be performed at acidic (4.5-6.0) or

highly alkaline pH (10-12), due to little absorbance of p-nitrophenol at acidic

pH [Gupta et al., 2003; Kademi et al., 2000] or auto- degradation/strong non-specific

color formation in the presence of strong alkalis such as NaOH or KOH

[Kademi et al., 2000]. Heating of the reaction mixture also tends to completely

decompose pNPP.

4.5. STUDIES ON POTENTIAL OF OSTB FOR

BIOREMEDIATION

For bioremediation studies of benzene and toluene, four distinctly different

bacteria viz. B. licheniformis AK1872, B. oceanisediminis AK39313, M. luteus

AK39532, and S. arlettae AK39675, isolated from samples collected from different

sites, were selected. For the study, initial concentration of benzene (B) and toluene

(T) used was 1740 mg liter-1

. After incubation for 48 h analysis was conducted using

GC-MS and the degradation of benzene and toluene was expressed as % loss as

compared to control.



Fig. 47. GC-MS analysis of residual BT (%) at the end of 48h incubation.

As observed above in Fig. 47, B. oceanisediminis AK39313 was identified as

the most potential culture as it could degrade around 35-36% benzene and toluene

which is higher as compared to other strains under study. B. licheniformis AK1872

and Staphylococcus arlettae AK39675 showed almost similar degradation ability,

around 15-16% of benzene and 19-20% of toluene while Micrococcus luteus

AK39532 showed least degradation. Based on the encouraging preliminary results,

biodegradation efficiency of total 21 OSTB was evaluated for prolonged period where

HPLC was used as an analytical tool.

The HPLC method was standardized for quantitative assay of benzene and

toluene by plotting calibration curves for both the solvents [Fig. 48 and 49]. This

method was used to calculate biodegradation capability of each isolate by comparing

concentration of solvents in control and experimental samples.

Fig. 48. Standard graph of Benzene.



Fig. 49. Standard graph of Toluene.

A few representative chromatograms of HPLC profile of biodegradation of

benzene and toluene by a few OSTB is shown below in Fig 50.

Standard



Control

Bacillus sp. AK39427



B. aquimais AK39881

Bacillus sp. AK39887



B. oceanisediminis AK39313

M. luteus AK39532





Fig. 50. HPLC chromatograms of biodegradation study.



As observed from Fig. 51, B. oceanisediminis AK39313 showed highest

degradation benzene ca. 50% among all the isolates where as Bacillus sp. AK39427,

Micrococcus luteus AK39532, B. licheniformis AK39762, Bacillus aquimaris

AK39881 and Bacillus sp. AK39887 showed degradation of benzene in the range of

35-40%. B. cereus AK1871, Bacillus sp. VK1901, Bacillus sp. AK2641, Terribacillus

halophilus AK39315, B. firmus AK39423, B. flexus AK39763, B. subtilis AK39765

and Micrococcus indicus AK39766 showed negligible degradation of benzene, in the

range of 0-6%.

Fig. 51. HPLC analysis of residual B (%) at the end of 72h incubation.

As observed from Fig. 52, B. oceanisediminis AK39313 showed highest

degradation of 58% toluene among all the isolates where as Bacillus sp. AK39427,

Micrococcus luteus AK39532, B. licheniformis AK39762, Bacillus aquimaris

AK39881 and Bacillus sp. AK39887 showed degradation of toluene in the range of

35-40%. B. cereus AK1871, Bacillus sp. VK1901, Bacillus sp. AK2641, Terribacillus

halophilus AK39315, B. firmus AK39423, B. flexus AK39763, B. subtilis AK39765

and Micrococcus indicus AK39766 showed marginal biodegradation of toluene in the

range of 9-14%.



Fig. 52. HPLC analysis of residual T (%) at the end of 72h incubation.

Here, various OSTB belonging to Bacillus sp., Terribacillus sp., Micrococcus

sp. and Staphylococcus sp. have been shown to degrade benzene and toluene. Yeast

extract (100 mg l-1

) was added to the medium that served as nitrogen and carbon

source which allowed the cells to proliferate in order to initiate the benzene and

toluene degradation. Various reports on yeast extract containing inducers for

expression of benzene and toluene degradation genes are known [Venkateswarlu and

Sethunathan, 1985, Paul et al., 2001; Ronen et al., 2005]. In environment, some form

of organic matter is generally present, due to metabolism or growth of different life

forms, which supports some initial growth of microbial community before the

degradation of hydrocarbon commences. For instance, reports on use of soil slurry

supporting degradation of benzene and toluene compounds are known. Soil and

sediment systems are very complicated; they may contain many inorganic or organic

components and essential trace elements to support the growth of their microbial

community. Combusted soil did not improve benzene and toluene biodegradation by

strain B113, indicating that organic matters might be a factor for the improvement of

benzene and toluene biodegradation [Kim and Jeon, 2009].

The pollution of soils by petroleum compounds is of great concern mainly

because of the solubility of the different molecules in water, which can endanger



aquifers in contact with polluted zones. Petroleum storage facilities are frequently the

source of pollution due to leaks and spills during fuel transfer and storage. Various

sites where old leaks have not yet been cleaned up are reported by US EPA

[http://www.epa.gov/OUST/pubs/OUST_FY07_Annual_Report-_Final_4-08.pdf]. As

mentioned in previous paragraph, the OSTB showing prominent degradation in the

study may have the potential in field applications for bioremediation of contaminated

sites.

Wang et al., [2008] reported a deep sea isolate, EJB1, showing a broad

degradation range. It was initially isolated from xylene enrichment, but grew on

benzene and toluene as well. Another isolate, JB5 obtained from toluene enrichment

grew with benzene as well. This suggested that most of them showed a wide range of

degradation. Undoubtedly, they play a role in attenuation of these toxic compounds in

marine environments. Their adaptability to saline conditions and high-concentration

of organic solvent make them unique in bioremediation. Based on the data presented

in this thesis, the OSTB isolated from marine and terrestrial environment are the

prospective candidates for bioremediation of range of aromatic compounds.

http://www.epa.gov/OUST/pubs/OUST_FY07_Annual_Report-_Final_4-08.pdf

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