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DEDICATION

I DEDICATE THIS HUMBLE EFFORT

TO

HAZRAT MUHAMMAD (PBUH)

And

MY PARENTS

Who taught me

The first word to speak

The first alphabet to write

The first step to take

And

Under whose feet my heaven lies

TABLE OF CONTENTS

Chapter No. Title Page No.

Acknowledgments I

List of Abbreviations III

List of Tables IV

List of Figures VII

Abstract IX

1. Introduction 1

2. Review of Literature 6

3. Materials and Methods 24

3.1 Study Area 24

3.1.1 Sample collection 24

3.2. Determination of heavy metals in the effluent 26

3.2.1. Preparations of standards for AAS analysis 26

3.3. Measurement of Physico-chemical parameters 28

3.3.1. Biological Oxygen Demand (BOD) 28

3.3.2. Chemical Oxygen Demand (COD) 31

3.4. Selection of heavy metals for the study 34

3.4.1. Preparation of Stock Solutions for Nickel 34

3.4.1.a. Calculation in mM: For 100 mM concentration 34

3.4.1.b. Calculation in ppm: For 1000 ppm concentration 35

3.4.2. Preparation of Stock Solutions for Cobalt 36

3.4.2.a. Calculation in mM: For 100 mM concentration 36

3.4.2. b. Calculation in ppm: For 1000 ppm concentration 37

3.5 Isolation and identification of HMT bacteria 37

3.5.1. Bacterial Count 38

3.5.2. Determination of Maximum Tolerable Concentration (MTC) 38

3.5.3. Multi Metal Resistance (MMR) 39

3.6. Identification of Bacteria 40

3.6.1. Gram’s staining 40

3.6.2. Motility Test 40

3.6.3. Growth on selective and differential culture media 40

3.6.4. Biochemical characterization 41

3.7. Optimization of growth conditions 43

3.8. Effect of Ni and Co on bacterial growth 46

3.9. Antibiotic Susceptibility testing 46

3.9.1. Disc diffusion method 46

3.10. Molecular Characterization 47

3.10.1. Extraction of genomic DNA 47

3.10.2. PCR amplification 48

3.10.3. Agarose gel electrophoresis 48

3.10.4. Phylogenetic analysis 50

3.11. Determination of biosorption potential of indigenous HMT bacterial

strains

50

3.11.1. Determination of heavy metals in supernatant 50

3.11.2. Preparation of standards for ICP-OES analysis 52

3.11.3. Estimation of metal Reduction 52

3.12. Preparation of samples for FTIR and SEM 52

3.12.1. Lyophilization of samples 52

3.12.1. a. Preparation & filling of vials 53

3.12.1. b. Lyophilization 53

3.13. Fourier transform infrared spectroscopy (FTIR) 55

3.14. Scanning electron microscopy (SEM) 55

3.15. Statistical analysis 55

4. RESULTS & DISCUSSION 56

4.1. Determination of heavy metals in effluent 56

4.2. Measurement of Physico-Chemical parameters 60

4.3. Isolation and identification of HMT bacteria 64

4.3.1. Bacterial count 64

4.3.2. Determination of MTC of Nickel (Ni) 67

4.3.3. Determination of MTC of Cobalt (Co) 74

4.3.4. Determination of MTC of Chromium (Cr) 74

4.3.5. Determination of Multi Metal Resistance (MMR) 75

4.3.6. Identification of bacterial isolates 77

4.3.6.a. Gram’s staining 77

4.3.6.b. Motility test 77

4.3.6.c. Growth on selective and differential culture media 77

4.3.6.d. Biochemical characterization 81

4.3.6.e. Carbohydrate fermentation 81

4.4. Optimization of growth conditions 81

4.5. Effect of Nickel (Ni) on bacterial growth 96

4.6. Effect of Cobalt (Co) on bacterial growth 96

4.7. Antibiotic susceptibility testing 106

4.8. Molecular characterization 110


strains

114

4.9.1. Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-

OES)

114

4.10. Fourier transform infrared spectroscopy (FTIR) 118

4.11. Scanning Electron Microscopy (SEM) 124

DISCUSSION 128

5. SUMMARY 137

REFRENCES 141

I

ACKNOWLEDGEMENTS

Up and above everything else, I offer my humblest and sincerest thanks to ALLAH

ALMIGHTY and bow my head in gratitude to Him to whom all praises and hymns are due, the

Omnipotent, the most Beneficent and Compassionate, the most Gracious and Merciful, the

Creator and Sustainer of the whole universe, Who bestowed upon us the Holy Quran, a doubtless

sacred book, an entire mode of life and mortality, a true cure for the diseases and a source of

emancipation for the believers; and conferred upon me good health, zeal of doing work, talented

teachers, the sense of enquiry and requisite potential and diligence for successful completion of

research work and preparation of this manuscript which is nothing but adding a tiny drop into the

already existing unfathomable ocean of knowledge.

The humblest and deepest obligations are also paid, with great honor and esteem to the

Holy Prophet HAZRAT MUHAMMAD (PBUH), the cause of this universe, the greatest social

reformer and benefactor of mankind, the most perfect and the best among and ever born on the

surface of earth, who is forever, a beacon of perfect guidance and knowledge for humanity as a

whole.

The work in this humble presentation was accomplished under the inspiring guidance and

enlightened supervision of my great and worthy supervisor, Dr. Muhammad Hidayat Rasool,

Chairman, Department of Microbiology, Government College University Faisalabad. I feel

highly privileged in taking the opportunity to thank him from the depth of my heart, for

suggesting the project, the dynamic supervision, marvelous guidance, encouraging behavior,

invaluable suggestions, corrections and indefatigable assistance at all time during the entire study

program and preparation of this manuscript.

I do not have enough words in my command to thank the members of my supervisory

committee, Dr. Muhammad Waseem, Assistant Professor and Dr. Bilal Aslam, Assistant

Professor, Department of Microbiology for their kind behavior, valuable suggestions, technical

guidance and moral support due to which this research work has found its way to successful

completion.

I fervently extend my zealous thanks to Dr. Muhammad Sajjad Mirza, Head of

Environmental Biotechnology Division, National Institute for Biotechnology and Genetic

II

Engineering, Faisalabad for their support and valuable suggestions in performing molecular

studies during my research work. I also want to thank Central High-Tech Laboratory, University

of Agricultural Faisalabad for helping me in metal analyses. I also highly appreciate and pay

thanks to my friend Mr. Shahid Hussain, Vaccine Production Manager at Intervac Pharama (Pvt)

Ltd. for helping me in the preparation of my samples and providing the facility of Freeze-drying.

My appreciations and thanks extend to Intertek Laboratories, Pakistan (Pvt) Ltd. for also

facilitating me in my research work. Finally I would like to thanks Dr. Yasir Nawab, Assistant

Professor, National Textile University Faisalabad for helping me in conducting SEM in National

Textile Research Center (NTRC) Faisalabad.

My special heartfelt appreciation and thanks are due to my affectionate mother, father,

brothers and sister for their love, best wishes, sincere prayers, moral support and

encouragement during the whole span of studies. I wish this endeavor justifies their faith in me.

Abuzar Muhammad Afzal

III

LIST OF ABBREVIATION

Sr. No. Word Abbreviation

1. Atomic Absorption Spectrometer AAS

2. Biological Oxygen Demand

BOD

3. Chemical Oxygen Demand COD

4. Dissolved Oxygen DO

5. Electric Conductivity EC

6. Eosin Methylene Blue agar EMB agar

7. Fourier transform infrared spectroscopy FT-IR

8. Heavy Metal Tolerant bacteria HMT bacteria

9. Inductively Coupled Plasma-Optical Emission Spectroscopy ICP-OES

10. Maximum Tolerable Concentration MTC

11. Multi Metal Resistance MMR

12. Nutrient Agar N.A

13. Total Dissolved Solids

TDS

14. Total Suspended Solids

TSS

15. Total Solids

TS

16. Triple Sugar Iron agar TSI agar

17. Scanning Electron Microscope SEM

IV

LIST OF TABLES

Sr. No. Title Page

1. Detail of sampling sites along with sample codes 25

2. Operational conditions employed in the determination of Heavy

Metals by Atomic Absorption Spectrophotometer

27

3. Calculations for Biological Oxygen Demand (BOD) in effluent

samples

30

4. Calculations for Chemical Oxygen Demand (COD) in effluent

samples

33

5. Experimental design for optimization of growth conditions of

HMT bacterial isolates

45

6. Composition of PCR reaction mixture used for amplification 49

7.

The instrumental operating conditions for heavy metal analysis

through Inductively Coupled Plasma-Optical

Emission Spectroscopy (ICP-OES)

51

8. Experimental design for the preparation of lyophilized samples

used in FTIR and SEM

54

9. Results of heavy metal analysis in industrial effluent through

atomic absorption spectrophotometer (AAS)

58

10. Analysis of variance (mean squares) for heavy metals present in

effluent samples

59

11. Comparison of means for heavy metals present in effluent

samples

59

12. Results of Physico-Chemical parameters of collected effluent

samples

62

13. Analysis of variance (mean squares) for physico-chemical

parameters

63

14. Comparison of means for physico-chemical parameters 63

15. Bacterial counts on culture media without and with heavy metals 65

16. Analysis of variance (mean squares) table for growth of bacteria

without and with metals

66

17. Comparison of means for growth of bacteria without and with

metals

66

18. MTC of Nickel (Ni) shown by bacterial population present in

collected effluent samples

68

19. Number of isolates growing at different concentrations of Nickel

(Ni) present in collected effluent samples

69

20. MTC of Cobalt (Co) shown by bacterial population present in


76

21. MTC of Chromium (Cr) shown by bacterial population present

in collected effluent samples

76

V

22. MMR shown by bacterial population present in different

collected wastewater samples

76

23. Morphological and biochemical characteristics of isolated HMT

bacterial strains

82

24. Optimum growth conditions for bacterial strain AMIC1

identified as Klebsiella spp.

83

25. Optimum growth conditions for AMIC1 (Klebsiella spp.)

without and with metals

84

25.(a) Group x Temperature interaction Means ±SE 84

25. (b) Group x pH interaction Means ±SE 84

25. (c) Group x Temperature x pH interaction Means ±SE 85


identified as Bacillus spp.

87

27. Optimum growth conditions for AMIC2 (Bacillus spp.) without

and with metals

88

27. (a) Group x Temperature interaction Means ±SE 88




identified as Bacillus spp.

91

29. Optimum growth conditions for AMIC3 (Bacillus spp.) without

and with metals

92

29.(a) Group x Temperature interaction Means ±SE 92



30. Analysis of variance (mean square) table for optimum growth

conditions of three bacterial strains

95

31. Effect of Ni on the growth rate of AMIC1 (Klebsiella spp.) 97

32. Effect of Co on the growth rate of AMIC1 (Klebsiella spp.) 98

33. Effect of Ni on the growth rate of AMIC2 (Bacillus spp.) 100

34. Effect of Co on the growth rate of AMIC2 (Bacillus spp.) 101

35. Effect of Ni on the growth rate of AMIC3 (Bacillus spp.) 103

36. Effect of Co on the growth rate of AMIC3 (Bacillus spp.) 104

37. Antibiotic susceptibility pattern of AMIC1 (Klebsiella spp.) 107

VI

38. Antibiotic susceptibility pattern of AMIC2 (Bacillus spp.) 108

39. Antibiotic susceptibility pattern of AMIC3 (Bacillus spp.) 109

40. Percentage of maximum similarity and GenBank accession

number of HMT bacteria

111

41. Percentage reduction of Nickel (Ni) and Cobalt (Co) by AMIC1

(Klebsiella spp.) through (ICP-OES)

115


(Bacillus spp.) through (ICP-OES)

115


(Bacillus spp.) through (ICP-OES)

116

44.

Comparison of Percentage reduction in Nickel (Ni) and Cobalt

(Co) by AMIC1 (Klebsiella spp.), AMIC2 (Bacillus spp.) and

AMIC3 (Bacillus spp.)

116

VII

LIST OF FIGURES

Sr. no Title Page

1. Regression line showing relation between Ni concentration and

number of bacteria for effluent sample SarDP2

70


number of bacteria for effluent sample RgrDP3

71


number of bacteria for effluent sample SarDP5

72

4. Graph showing the effect of Ni concentration on three different

bacterial isolates

73

5. Microscopic view of typical Gram Positive Rods (100x) 78

6. Microscopic view of typical Gram Negative Rods (100x) 78

7. Growth of bacteria on MacConkey’s agar plate 79

8. Growth of bacteria on EMB agar plate 79

9. Growth of bacteria on TSI agar plate 80

10. Growth of bacteria on TSI agar slant 80

11. Graph showing optimum growth conditions for AMIC1

(Klebsiella spp.) without and with metals

86


(Bacillus spp.) without and with metals

90



94

14. Graph showing effect of Ni on the growth rate of AMIC1

(Klebsiella spp.) 97

15. Graph showing effect of Co on the growth rate of AMIC1

(Klebsiella spp.)

98

16. Graph showing effect of Ni vs. Co on the growth rate of AMIC1

(Klebsiella spp.)

99


(Bacillus spp.) 100


(Bacillus spp.)

101


(Bacillus spp.)

102


(Bacillus spp.)

103


(Bacillus spp.)

104


(Bacillus spp.)

105

23. 16S rRNA sequence-based phylogenetic tree of Klebsiella strain

isolated from textile effluents constructed by Maximum

Likelihood method

112

24. 16S rRNA sequence-based phylogenetic tree of Bacillus strains 113

VIII

isolated from textile effluent constructed by Maximum

Likelihood method

25. Graph showing comparison of Percentage reduction in Nickel

(Ni) and Cobalt (Co) by AMIC1 (K. variicola), AMIC2 (B.

cerus) and AMIC3 (B. cerus)

117

26. FT-IR spectra of AMIC1 biomass without metal loading 119

27. FT-IR spectra of AMIC1 biomass loaded with Ni 119

28. FT-IR spectra of AMIC1 biomass loaded with Co 120







35. Electron micrograph of Klebsiella variicola grown without metal

stress (control) 125

36. Electron micrograph showing the effect of Co on Klebsiella

variicola 125

37. Electron micrograph showing the effect of Co on Klebsiella

variicola 126

38. Electron micrograph of Bacillus cereus grown without metal

stress (control)

126

39. Electron micrograph showing the effect of Ni on Bacillus cereus 127

40. Electron micrograph showing the effect of Co on Bacillus cereus 127

IX

ABSTRACT

Heavy metal contamination now a day is one of the major global environmental concern

and the main sources of heavy metal contamination are either natural or anthropogenic. Industrial

wastewater is commonly used for irrigation in most of the developing third world countries. As

the number of industries is being increased day by day in the modern world, with this the

concentration of heavy metals is also being increased. Several studies have been conducted to

elaborate the effects of these heavy metals on living organisms including animals, plants and

human. This study aims to isolate, identify some indigenous heavy metal tolerant (HMT)

bacteria from textile effluents and to evaluate their biosorptive potential. Three indigenous

isolates were screened out showing maximum tolerable concentration (MTC) and multi metal

resistance (MMR) to Ni and Co at different levels and were given name as AMIC1, AMIC2 and

AMIC3. Molecular characterization confirmed that AMIC1 was (K. variicola, accession number

LT838344) while AMIC2 and AMIC3 were (B. cerus accession numbers LT838345 and

LT838346 respectively). Biosorptive potential was accessed using Inductively Coupled Plasma-

Optical Emission Spectroscopy (ICP-OES) and it was found that AMIC1 reduced (49%, 50%) of

Ni after 24 and 48 hours respectively and (68.6%, 71%) of Co after 24 and 48 hours respectively.

Similarly AMIC2 reduced (48.4%, 49%) of Ni after 24 and 48 hours respectively and (70.6%,

73.6%) of Co after 24 and 48 hours respectively. AMIC3 reduced (51.8%, 50.6%) of Ni after 24

and 48 hours respectively and (73.2%, 71.8%) of Co after 24 and 48 hours respectively. Fourier

transform infrared spectroscopy (FT-IR) was used to analyze the functional groups and overall

nature of chemical bonds in bacterial strains while Scanning Electron Microscope (SEM) was

performed to detect outer morphological changes in the bacteria in response to metal stress. So it

can be concluded that all three bacteria possessed significant bioremediation potential which

could be utilized for the development of bioremediation agents to detoxify textile effluents at

industrial surroundings in the natural environments in Pakistan.

1

Chapter 1

INTRODUCTION

In general, “Heavy Metal” is a broad term, which is used for the group of metals

and metalloids having atomic density greater than 4000 kg m-3 or 5 times more than

water. As compared to organic pollutants, such as pesticides and petroleum by-products,

heavy metals are more persistent and stable in the environment and are non-

biodegradable. Heavy metal contamination now a day is one of the major global

environmental concern and the main sources of heavy metal contamination are either

natural or anthropogenic. Anthropogenic sources involve smelters, mining, power

stations and the application of metal containing pesticides fertilizer and industrial effluent

in agriculture. Depending on soil pH and their specification these heavy metals can

become mobile in soils and in this way, a small part of the total mass can leach to aquifer

or can become bioavailable to living organisms (Hookoom & Puchooa, 2013).

In most of the developing countries industrial effluent is used for the irrigation

(Bouwer, 2002).Wastewater of the urban area is being used profitably to irrigate

vegetable crops in the vicinity of cities from the time unknown. Waste and sewerage

water is still considered most rich in plant nutrients and organic matter. In many cities

and towns the sewerage water is sold and it is a good source of income to municipalities.

However, the situation is changed now and with the establishment of industries in sub-

urban areas, the wastewater is mixed with industrial effluents and big culverts are coming

out from the cities. These culverts and drains not only contain heavily polluted water but

also give noxious and off smell gases. The polluted water even then is still used for

growing vegetables in the nearby area of the cities without knowing their adverse impact

on the life of consumers (Saif et al., 2005).

Additionally, heavy metals can accumulate in biological systems and ultimately

be introduced into food web via different mechanisms. Without proper treatment, release

of heavy metals in effluent waste poses a menace to public health because of its

persistence, bio magnifications and accumulation in food chain (Issazadeh et al., 2014).

As the number of industries is being increased day by day in the modern world, with this

2

the concentration of heavy metals is also being increased. Cadmium, chromium, mercury,

lead, nickel, cobalt and copper are mainly found in the industrial wastewater (Smrithi &

Usha, 2012).

Industrial effluent is mainly responsible for the air, soil and water pollution which

is associated with various diseases and could be the cause for the existing shorter life

expectancy (WHO, 2003). Moderate amounts of metallic cations are present in the

industrial sewage effluents. Various techniques were used to study the mobility of toxic

metals in industrial effluent (Kazi et al., 2005). After contaminating the water bodies,

toxic substances get dissolved in water or get deposited on the bed. As a result of this

“water pollution” occurs and the quality of water deteriorates which affects the aquatic

ecosystems. Soil quality is badly affected when irrigated with such kind of polluted

effluent (Olaniya et al., 1998; Brar& Arora, 1997). Groundwater deposits are also being

affected by the leaching of pollutants from industrial effluent. Living organisms are prone

to heavy metals like cadmium, cobalt, copper, chromium, mercury, nickel, zinc and lead

intoxication. People living in the environs of the dumping sites are facing various health

problems and their health is being steadily affected by the metal contamination of

drinking water and food (Chipasa, 2003; Chisti, 2004).

Several studies have been conducted and being conducted to elaborate the effects

of these heavy metals on living organisms including animals, plants and human (Chipasa,

2003; Chisti, 2004). Heavy metals can damage the living organisms through different

mechanisms such as by affecting the cell membranes, by altering the enzymes specificity,

by disrupting the cellular functions and by damaging the structure of the DNA. These

heavy metals produce toxicity by disrupting ligand interactions or by the displacement of

essential metals from their subject binding sites. Similarly, these can produce toxicity by

altering the conformational structure of the proteins and nucleic acids and by producing

interference with oxidative phosphorylation and osmotic balance. Heavy metals cause

numerous diseases and disorders by accumulating themselves in organisms as they are

not biodegradable (Ozer & Pirincci, 2006).

Several conventional physico-chemical techniques had been used in the past and

still are being used for metal remediation which includes filtration, acid leaching,

3

electrochemical processes or ion exchange. But these are not very much effective with

high cost. In comparison, bioremediation using microorganisms, plants or other

biological systems provides a much cheaper and environment friendly method for metal

remediation. Considerably, heavy metals are toxic for living organisms in the

environment in their free ionic forms (Hookoom & Puchooa, 2013). Bioremediation can

be used to effectively reduce contaminant and toxicity to levels that are harmless to

human health and ecosystem. Therefore, it is necessary to remove heavy metals such as

nickel, cobalt and chromium from the environment, so that major health hazards can be

prevented (Yasar et al., 2013).

Antibiotic resistance occurs when a bacterium face a change in its genetic

makeup, either by facing a genetic mutation or by the transfer of antibiotic resistance

genes between bacteria in the environment. Commonly used products in industry

(disinfectants, sterilants and heavy metals) and house hold products along with antibiotics

are responsible for creating a selective pressure in the environment that is leading the

cause of the mutations in microorganisms (Baquero et al., 1998). Previously it was

notable if microorganisms which cause epidemic diseases acquire resistance and it was an

issue only related to clinically isolated strains but at present, antibiotic resistant bacteria

have been isolated from the environment. In this way, these resistance genes can spread

and is creating a pool of resistance in non-pathogenic organisms found in humans,

animals, and the environment. As a result, non-pathogenic organisms provide genes

which confer resistance in pathogenic organisms, and in turn, they can become resistant

by acquiring genes from pathogens discharged into the environment (Krishna et al.,

2014).

It is notable that previously, many researchers suggested that metal contact is

indirectly responsible for bacterial resistance to unrelated toxicants, particularly

antibiotics, that’s why antibiotic resistance study in the bacteria isolated from the metal

contaminated areas are very imperative. Normally genes responsible for antibiotic and

metal resistance are present on the same plasmids or transposons for example transposons

Tn21 which is responsible for the co-resistance to aminoglycosides, mercury and

sulfonamides. A phenomenon known as cross-resistance occurs when single enzyme

functions as efflux pump for multiple metals and antibiotics. In either case, direct

4

selection for metal tolerance could indirectly go for organisms conferring antibiotic

resistance (Krishna et al., 2014).

Several studies conducted on bacterial diversity in heavy metal contaminated sites

had confirmed a high diversity of microorganisms (Konstantinidis et al., 2003).

Indigenous microorganisms have the ability to adapt themselves according to the

prevailing environments and could flourish under these conditions (Haq & Shakoori,

2000; Roane & Pepper, 2000). Lot of mechanisms has been developed by some

microorganisms to deal with high concentrations of heavy metals and usually is specific

to one or a few metals (Piddock, 2006). Microorganisms have adopted ways to endure the

metals either by presence of heavy metals through efflux, complexation, or reduction of

metal ions or to use them as terminal electron acceptors in anaerobic respiration

(Haferburg & Kothe, 2010). Most microorganisms possess the efflux of metal ions

outside the cell, and genes for tolerance mechanisms have been found on both

chromosomes and plasmids. Metal resistant bacteria play an important role in the

biogeochemical cycling of those metal ions (Hookoom & Puchooa, 2013). Some bacteria

can use mechanisms of tolerance and detoxification of heavy metals and still produce

chelating agents that bound metals and reduce their toxicity (Kavamura & Esposito,

2010). Many living bacteria have been reported to reduce or to transform toxic

contaminants into their less toxic forms (Solecka et al., 2012).

Faisalabad is the 3rd biggest city in Pakistan after Karachi and Lahore. It is the 2nd

biggest city in the province of Punjab after Lahore, and a major industrial center. The city

is also known as the “Manchester of Pakistan” (Jaffrelot, 2002). Faisalabad is a major

contributor towards Pakistan's GDP (gross domestic product), contributing over 20% of

total GDP of the country. According to the World Bank's Doing Business Report of 2010,

Faisalabad was ranked as the best place to do business in Pakistan and the second best

location, after Islamabad, to start a business. The surrounding countryside, irrigated by

the lower Chenab River, produces cotton, wheat, sugarcane, vegetables and fruits.

Due to the heavy industrialization different types of waste is being produced by

the different industries. The textile zone is playing a vital role in the export of the country

but at the same time a lot of environmental pollution is being produced by this zone.

5

Approximately 10, 000 different dyes and pigments are manufactured worldwide with a

total annual market of more than 7×105 metric tons per year (Ahluwalia & Goyal, 2007).

Therefore it was need of the time to analyze these wastes for the isolation and

characterization of some indigenous strains of heavy metal tolerant (HMT) bacteria and

to explore their potential in bioremediation of common heavy metals founds in such

effluents.

Keeping in view the above, present study has been conducted with the following

specific objectives:

1. Isolation and identification of HMT bacteria from the textile effluent of Faisalabad,

Pakistan.

2. Determination of Maximum Tolerable Concentration (MTC) and Multi Metal

Resistance (MMR).

3. Antimicrobial susceptibility testing of indigenous strains of HMT bacteria.

4. Molecular characterization of indigenous HMT bacterial isolates.

5. In-vitro evaluation of Biosorptive potential of HMT bacterial strains.

6

Chapter 2

REVIEW OF LITERATURE

Review of literature and the previous work done in a field provides a guide line in

designing the scientific studies keeping in view the weaknesses of the previous studies.

This chapter furnishes a review of some relevant literature about metal analysis in

industrial effluent, isolation and identification of metal tolerant bacteria, determination of

maximum metal tolerance potential of these bacteria, multi metal tolerance ability of

metal tolerant bacteria, correlation between antibiotic and heavy metal tolerance in

bacterial strains and evaluation of biosorption potential of bacterial strains through

different techniques.

Ugur & Ceylan (2002) studied antibiotic and heavy metal resistance patterns in

Staphylococcus spp. recovered from clinical sources. For this purpose, they isolated total

of 22 strains and processed for biochemical identification by conventional tests followed

by use of API Staph system. Antimicrobial susceptibility of all the isolates was

determined. Resistance patterns of all the isolates were checked by growing the isolates at

different concentrations of nickel chloride (NiCl2), zinc sulfate (ZnSO4), lead acetate Pb

(CH3COO) 2, cobalt chloride (CoCl2), copper sulfate (CuSO4), potassium chromate

(K2Cr2O7), silver nitrate (AgNO3), and mercuric chloride (HgCl2). Results showed that

53% of isolates were screened as oxacillin resistant Staphylococcus aureus whereas 40%

of isolates were screened as MRSA. Plasmid content and profile studies showed that

isolates carried plasmids ranging from 2.224 to 20.650 kb in size. It was observed that

50% of studied strains harbored plasmids and association between occurrence of

plasmids and resistance to antibiotics and heavy metals was observed.

Raja et al. (2006) designed a study to isolate and characterize metal tolerant

Pseudomonas aeruginosa strain. For this purpose, wastewater samples were collected

from oil mil sites located in Madurai and Virudhunagar districts in India. Isolation,

identification and quantification of biomass of HMT bacteria were done by conventional

microbiological methods and spectrophotometer. Minimum inhibitory concentration

(MIC) of the heavy metals was determined by plate dilution method using the different

7

concentration of heavy metal salts. 16S rDNA sequencing of the isolate revealed that it

was closely related to Pseudomonas aeruginosa (94% similarity). Isolate showed

biosorption potential against all four tested metals (Cd, Cr, Pb and Ni) and the

biosorption pattern was found as: Ni (93%), Pb (65%), Cd (50%) and Cr (30%). Further

studies were suggested to have better idea to use the isolated strain for the bioremediation

of metal contaminated sites.

Congeevaram et al. (2007) designed a study to check the biosorption of chromium

and nickel by heavy metal resistant fungal and bacterial isolates. For this purpose, soil

samples were collected from the electroplating industry. Isolation, identification and

quantification of biomass of HMT bacteria were done by conventional microbiological

methods and spectrophotometer. Minimum inhibitory concentration (MIC) of the heavy

metals was determined by plate dilution method using the different concentration of

heavy metal salts. From the results of this study, it was found that expanded stationary

phase was required by bacteria and fungi to remove chromium from the wastewater while

for the removal of nickel no expanded stationary phase was required. It was found that

Micrococcus spp. and Aspergillus spp. have very good potential for the removal of

chromium and nickel from industrial effluent. Further studies were suggested to have

better idea to use these microorganisms as potential bioremediation agents.

Morales et al. (2007) designed a study for the isolation and identification of

chromium resistant bacteria from soil. For this purpose, soil samples were collected.

From the collected samples, bacteria were isolated, identified and tested for the resistance

of chromium. Molecular characterization was done using 16s rDNA technique. The

isolated bacterial strain CG252 was identified as Streptomyces spp. It was evident from

the results of this study that Streptomyces spp. significantly reduced the Cr (VI) to Cr

(III). Further investigation in this field was suggested to have better idea to use these

microorganisms for the bioremediation of chromium contaminated soils.

Altaf et al. (2008) designed a study to see impact of long-term application of

treated tannery effluents on the emergence of resistance traits in Rhizobium spp. isolated

from Trifolium alexandrinum. For this purpose, plant and soil samples were collected

from the agricultural field irrigated with treated tannery effluents Isolation and

8

identification of bacteria was done by conventional microbiological methods. Minimum

inhibitory concentration (MIC) of the heavy metals was determined using plate dilution

method using different concentration of heavy metal salts. By the result of this study, it

was found that highest amount of heavy metal was accumulated in the roots of Trifolium

alexandrinum and the isolated Rhizobium spp. shown highest minimum inhibitory

concentration against Cr+3.

Rajbanshi et al. (2008) designed a study to evaluate metal tolerant bacteria in

sewage water. Different bacterial strains were isolated that were tolerant to different

heavy metals. The results showed that Staphylococcus spp., Escherichia coli, Klebsiella

spp. were resistant to chromium; Acinetobacter spp., Flavobacterium spp., Citrobacter

spp. were resistant to cadmium; Staphylococcus spp., Bacillus spp. Were resistant to

nickel; Pseudomonas spp. was resistant to copper and Methylobacterium spp. was

resistant to cobalt. Out of all isolated strains six of them showed multi metal tolerance

(MMT). Results showed that isolates were able to tolerate chromium and nickel.

Rehman et al. (2008) carried out a study to evaluate the Cr+6 tolerance and

reduction potential of Bacillus spp.ev3 isolated from metal contaminated wastewater. For

this purpose, the wastewater samples were collected from industrial area of Sialkot,

Pakistan. Identification of bacteria was done by using conventional microbiological

methods and some physicochemical parameters such as temperature, pH were measures

by using pH meter. After the isolation the metal processing capability of isolates was

checked by culturing the bacteria with different concentration of chromium. By the result

of this study, it was found that Bacillus sp ev3 was able to reduce chromium hexavalent

form to chromium trivalent form and it was capable of removing 91% of chromium after

96 hour. Along this the isolated bacterial strain showed multiple metal tolerance. Further

investigation in this field was suggested to have better idea to use these microorganisms

for the bioremediation of chromium contaminated sites.

Ezzouhri et al. (2009) designed a study to see heavy metal tolerance of

filamentous fungi isolated from polluted sites in Tangier, Morocco. For this purpose,

water and sediments samples were collected from the Moghogha River and isolation and

identification of HMT bacteria was done using conventional microbiological methods.

9

Minimum inhibitory concentration (MIC) of the heavy metals was determined by plate

dilution method and using the different concentration of heavy metal salts. By the result

of this study, it was found that majority of isolates were tolerant to Cd, Cr, Pb, Hg and

Ni. Out of all the isolates Penicillium and Aspergillus were most tolerant to heavy metals.

Raja et al. (2009) carried out a study for the isolation, identification and

characterization of HMT bacteria from sewage. For this purpose, the wastewater samples

were collected from sewage water of Madurai district, India. Samples were collected in

sterile bottles and isolation and identification of bacteria was done using conventional

microbiological methods. The isolates were screened for metal tolerance and antibiotic

resistance, based on high level of heavy metal and antibiotic resistance four isolates were

selected. By the result of this study, it was found that identified isolates namely Proteus

vulgaris, Pseudomonas aeruginosa and Acinetobacter redioresistens were resistant to Cd,

Ni, Pb, Co, As, Hg and Cr. It was concluded that these isolated, identified bacteria could

be used for the bioremediation purpose, so further investigation in this field was

suggested to have better idea to use these microorganisms for the bioremediation of

sewage and wastewater.

Shakoori et al. (2010) characterized Cr6+ reducing bacteria and evaluated their

bioremediation potential in chromium containing wastewater. For this purpose, they

isolated and characterized three bacterial strains including Bacillus pumilus, Alcaligenes

faecalis and Staphylococcus spp. To check the bioremediation potential of the isolates

and to check their Cr+6 reducing to Cr3+diphenylcarbazide method was used. It was

evident from the results that B. pumilus showed 95%, A. faecalis showed 97% and

Staphylococcus spp. showed 91% ability to reduce Cr6+ into Cr3+ within 24 hours from

the medium containing 100 μg Cr6+/ml. By the results of this study they concluded and

suggested that bacterial strains can be exploited for the bioremediation purpose of

hexavalent chromium containing wastes.

Nanda et al. (2011) investigated the use of bacteria for the removal of heavy

metals from the industrial effluent. For this purpose, the waste water samples were

collected from the pharmaceutical industrial area in Dehradun in sterile bottles and the

samples were transported to lab. Isolation and identification of bacteria was done by

10

using conventional microbiological methods. After the physicochemical analyses the

industrial waste water was treated with isolated bacteria and the potential of

bioremediation of isolates was recorded. It was found that Bacillus spp. and

Pseudomonas spp. were able to eliminate Cd from the effluent. By the result of this

study, it was concluded that bacteria play very vital role in the removal of heavy metal.

Pandey et al. (2011) carried out a study for the isolation and characterization of

HMT bacteria. For this purpose, slag samples were collected from slag disposal sites at

Burnpur, India. Isolation and identification of bacteria was done by using conventional

microbiological methods and molecular characterization of isolates was done by using

16S rDNA. Optimum growth conditions of the isolates were determined at different pH

and temperature. By the results it was found that the isolated bacterial strains which

sowed resistance patterns against arsenic and lead were identified as Bacillus spp. it was

evident from the results that both strains showed bioaccumulation potential for lead and

arsenic. Further studies were suggested in this area to have better idea to use these

microorganisms for the bioremediation.

Alzubaidy (2012) designed a study to evaluate the resistance potential of locally

isolated Serratia marcescens against different heavy metal chlorides. Minimum

inhibitory concentration (MIC) of the heavy metals was determined using the different

concentration of heavy metal chlorides including ZnCl2, PbCl2 and AlCl3. It was evident

from the results that isolates showed highest removal capacity against zinc and lowest

against iron. It was concluded that these isolated HMT bacteria could be used for

bioremediation of soil and water polluted with metals. Further studies were suggested in

this area to have better idea to use these microorganisms for the bioremediation.

Karakagh et al. (2012) carried out a study to evaluate the biosorption of Cadmium

and Nickel by using the inactivated bacteria isolated from agricultural soil treated with

sewage sludge. For this purpose, they collected samples from the agricultural soil treated

with sewage sludge and isolated mainly three strains of bacteria namely Actinomycetes

spp., Streptomyces spp. and Bacillus spp. Minimum inhibitory concentration of Ni and

Cd was determined by the different concentration of salts of these metals in nutrient agar.

By the result of this study, they found that Actinomycetes spp. have the maximum

11

capacity to tolerate both Ni and Cd as compared to Streptomyces and Bacillus spp. and

concluded that the indigenous micro flora of the soil is strong candidate for the purpose

of bioremediation.

Milton & Reetha (2012) designed a study to evaluate the removal of heavy metals

using bacteria isolated from lignite mining environment. For this purpose, they collected

samples from different areas, and isolated HMT bacteria using nutrient agar medium

supplemented with different concentrations of heavy metal salts. After isolation and

identification they evaluated the bioremediation capacity of isolates by two different

approaches namely: biosorption and bioaccumulation. By the result of this study, they

concluded that HMT bacteria isolated from the lignite mining environment have shown a

potential as detoxifying agents and these isolates can be used in future for the purpose of

in-situ bioremediation.

Nath et al. (2012) isolated and characterized HMT bacteria. For this purpose,

samples were collected from different sources contaminated with lead and cadmium.

Isolation and identification of bacteria was done using conventional microbiological

methods. Predominant bacterial strains on selective media were identified as Bacillus

spp., Klebsiella spp., Proteus spp., Pseudomonas spp. and Staphylococcus spp. The result

of this study showed that all isolated bacterial strains had significant tolerance capacity

against both metals (Pb and Cd), however out of all isolates Bacillus spp. was found to

have high metal tolerance pattern against Pb and Cd (1200µg/ml and 1800µg/ml)

respectively. From the results of the study it could be concluded that bacteria can play

important role for the bioremediation of heavy metals. Further studies were suggested in

this area to have better idea to use these microorganisms for the bioremediation.

Smrithi & Usha (2012) carried out a study for the isolation and characterization of

chromium removing bacteria from the tannery effluent disposal sites. For this purpose,

the wastewater samples were collected from selected leather processing industry at

Dindigul in Tamil Nadu, India. Samples were collected in sterile bottles and the samples

and isolation and identification of bacteria was done by using conventional

microbiological methods and some physicochemical parameters such as temperature, pH

were measures by using pH meter and heavy metal concentration was measured by

12

Atomic Absorption Spectrometry (AAS). After the isolation the metal processing

capability of isolates was checked by culturing the bacteria with different concentration

of heavy metal salts. By the result of this study, it was found that Bacillus spp. reduce

85.9% chromium from the medium within 96 hours and also has the ability to remove

heavy metals like Ni, Co, Cd etc. other than chromium found in the tannery effluent.

Elsilk et al. (2013) in Egypt carried out a study to see the accumulation of some

heavy metals by metal resistant avirulent Bacillus anthraces PS2010. For this purpose,

water samples were collected from the electroplating industry wastewater and isolation

and identification of HMT bacteria was done using conventional microbiological

methods. Minimum inhibitory concentration (MIC) of the heavy metals was determined

using plate dilution method and by the different concentration of heavy metal salts. After

the treatment of wastewater containing heavy metals the isolates were observed under

electron microscope to observe any morphological change. For the molecular

characterization of isolates sequencing was done using 16S rRNA technique. By the

result of this study, it was found that potent bacterium had biosorption capacity which is

dependent to nature of metal, incubation time, temperature, pH of solution and contact

time.

Hookoom & Puchooa (2013) in Mauritius designed a study to isolate and identify

metal tolerant bacteria from industrial and agricultural waste. For this purpose, they

collected samples from different areas, which were assumed to be contaminated with

industrial waste. From the collected samples, bacteria were isolated, identified and tested

for the resistance of different metals. Molecular characterization was done using 16s

rDNA technique. From the result of this study, they found that all the bacteria isolated,

identified and characterized belonged to the genera Bacillus and these isolated bacteria

shown metal tolerance.

Kacar & Kocyigit (2013) carried out a study to characterize heavy metal tolerant

and antibiotic resistant bacteria. For this purpose, sediment samples were collected from

Aliaga (main ship dismantling site), Turkey. Isolation and identification of bacteria was

done using conventional microbiological methods. The isolates were screened for metal

resistance and antibiotic resistance. Minimum inhibitory concentration (MIC) of the

13

heavy metals was determined by using the different concentration of heavy metal salts

and antibiotic susceptibility of isolates was determined against commonly used

antibiotics. For the molecular characterization of isolates sequencing was done using 16S

rDNA technique. Phylogenetic analyses of isolates identified that all isolates belonged to

Bacillus spp. It was observed that all isolates were resistant to heavy metals and MIC

pattern of isolates showed that the isolates were highly resistant to lead (Pb) and least

resistant to mercury (Hg). Similarly the isolates were highly resistant to gentamycin and

tobramicin. By the result of this study, it was suggested that presence of these bacteria in

coastal area can be regarded as biological indicators of heavy metal contamination.

Further studies were suggested in this area to have better idea to use these

microorganisms for the bioremediation.

Kamika & Momba (2013) designed a study to evaluate the presence of heavy

metals in industrial wastewater and screened the bioremediation ability of some known

bacteria and protozoan. For this purpose, three bacterial species (Bacillus licheniformis

ATCC12759, Brevibacill laterosporus ATCC64 and Pseudomonas putida ATCC31483)

and three protozoan species (Aspidisca spp., Trachelophyllum spp. and Peranema spp.)

were selected. Qualitative and quantitative analyses of collected wastewater samples for

heavy metals were done by using inductively coupled plasma optical emission

spectrometry. The results showed that all the water samples were polluted with heavy

metals. It was evident from the results of bioremediation experiments that living

Pseudomonas putida from all three bacterial strains and Peranema spp. of protozoa

possessed the highest remediation capacity. It was also found that bacterial spp. contained

the extra genes encoding for heavy metal tolerance. Further studies were suggested in this

area to have better idea to use these microorganisms for the bioremediation.

Nyamboya et al. (2013) in Nairobi, Kenya investigated the heavy metal and

associated antibiotic resistance of fecal coliforms, fecal streptococci and pathogens

isolated from effluent of abattoirs. For this purpose, sludge samples and samples from

slaughter houses were collected from the Nairobi’s Eastland area and were transported to

lab. Isolation and identification of bacteria was done using conventional microbiological

methods. The isolates were screened for metal resistance and antibiotic resistance.

Minimum inhibitory concentration (MIC) of the heavy metals was determined by using

14

the different concentration of heavy metal salts. By the result of this study, it was found

that in the bacteria isolated from wastewater and sludge of cattle there exist heavy metal

resistance which was associated with multiple drug resistance.

Shrivastava et al. (2013) designed a study to evaluate the heavy metal tolerance

capacity of bacteria isolated from industrial effluents. For this purpose, effluents samples

were collected from Agra and Firozabad industrial area. . Isolation and identification of

bacteria was done using conventional microbiological methods. The isolates were

screened for metal resistance and antibiotic resistance. Minimum inhibitory concentration

(MIC) of the heavy metals was determined using the different concentration of heavy

metal chlorides including cadmium, nickel and lead. Three isolates screened having

maximum metal tolerance capacities were identified as Bacillus subtilis, Escherichia coli

and Staphylococcus aureus. MIC values for B. subtilis against cadmium, nickel and lead

were (400, 300 and 400μg/ml) respectively. MIC values for E. coli against cadmium,

nickel and lead were (350, 250 and 350μg/ml) respectively. MIC values for S. aureus

against cadmium, nickel and lead were (450, 450 and 300μg/ml) respectively. Further

studies were suggested to explore the metal accumulation and nanoparticle generation for

the isolated strains at molecular level which can help in genetic manipulation for more

efficiency and practical rationale.

Abbas et al. (2014) designed a study to Isolate and characterize arsenic resistant

bacteria from wastewater. For this purpose, wastewater samples were collected from the

Kala Shah Kakoo, Pakistan and were transported to lab. Isolation and identification of

HMT bacteria was done by conventional microbiological methods. Minimum inhibitory

concentration (MIC) of the heavy metals was determined using plate dilution method by

using the different concentration of heavy metal salts. For the molecular characterization

of isolates sequencing was done using 16S rRNA technique. By the result of this study, it

was found that Enterobacter spp. and Klebsiella pneumonia spp. were most resistant

bacteria spp. against arsenic and showed growth on much higher concentration of arsenic.

Further studies were suggested as these bacteria may be helpful in future in

bioremediation of industrial effluent especially with reference to heavy metals.

15

Abbas et al. (2014) designed a study to Isolate and characterize cadmium resistant

bacteria from wastewater. For this purpose, wastewater samples were collected from

industrial area of Penang, Malaysia and were transported to lab. Isolation and

identification of HMT bacteria was done by conventional microbiological methods.

Minimum inhibitory concentration (MIC) of the selected isolate was found to be

550µg/ml. For the molecular characterization of isolates sequencing was done using 16S

rDNA technique. The selected strain identified as pseudomonas spp.M3. By the result of

this study, it was found that the selected strain was able to remove 70% of cadmium in

the log phase. Further studies were suggested as these bacteria may be helpful in future in

bioremediation of industrial effluent especially with reference to heavy metals.

Alboghobeish et al. (2014) studied nickel resistant bacteria (NiRB) isolated from

wastewater polluted with different industrial sources. For this purpose they isolated eight

nickel resistant bacteria out of the isolated strains, three strains were selected on the basis

of their maximum tolerable concentration. From the results it was observed that bacterial

strain ATHA3 was able to tolerate 08mM Ni+2, ATHA6 was able to tolerate 16mM Ni+2

and ATHA7 was able to tolerate 24mM Ni+2. 16s rDNA gene sequencing identified

ATHA3 as Cupriavidus sp, ATHA6 Klebsiella oxytoca and ATHA7 as Methylobacterium

spp. It was observed that K. oxytoca decreased 83mg/l of Ni+2 from the medium after 72

hours.

Gawali et al. (2014) evaluated the bioremediation potential of HMT bacteria

isolated from industrial wastewater. For this purpose, wastewater samples were collected

from industrial area in Akola, in sterile plastic bottles. Isolation and identification of

bacteria was done by conventional microbiological methods. Isolated HMT bacteria were

identified as E. coli, P. aeruginosa and E. acrogens. It was evident from the results that

E. coli was able to remove Pb and Cu with removal percentage of 45% and 62%

respectively. P. aeruginosa was able to remove Cd, Ni and Co with removal percentage

of 56%, 34% and 53% respectively. While E. acrogens was able remove Cd and Cu with

removal percentage of 44% and 34% respectively. From the results of the study it could

be concluded that bacteria can play important role for the bioremediation of heavy

metals.

16

Issazadeh et al. (2014) carried out a study to isolate and identify the HMT bacteria

from industrial wastewaters in Guilan Province. For this purpose, the waste water

samples were collected from five different ponds in industrial area of Rasht in Guilan

Province. Samples were collected in sterile bottles and isolation and identification of

bacteria was done by conventional microbiological methods and some physicochemical

parameters such as temperature, pH was measured by using pH meter and heavy metal

concentration was measured by Atomic Absorption Spectrometry (AAS). After the

isolation the metal processing capability of isolates was checked by inoculating the

bacteria with different concentration of heavy metal salts. It was found that Bacillus spp.

and Pseudomonas spp. were able to eliminate Cd from the effluent. By the result of this

study, it was concluded that bacteria play very vital role in the removal of heavy metal.

Kumar (2014) carried out a study for the isolation, molecular characterization of

metal tolerant bacteria and its heavy metal capability. For this purpose, samples were

collected from the electronic waste recycling facility and were transported to lab.

Isolation and identification of bacteria was done by conventional microbiological

methods. 16S rRNA technique was used for the molecular characterization of isolated

bacteria. The isolates were screened for metal resistance and antibiotic resistance.

Minimum inhibitory concentration (MIC) of the heavy metals was determined by using

the different concentration of heavy metal salts. By the result of this study, it was

observed that Pseudomonas aeruginosa isolated from the cadmium containing effluent

can effectively remediate the cadmium in wastewater so further studies should be

conducted to have a better idea of using this microorganism for the purpose of

bioremediation.

Tamiru et al. (2014) designed a study in Bahir Dar, Ethiopia for the assessment of

heavy metals and antibiotic resistance in Rhizobacteria which were isolated from

rhizosphere soils contaminated with tannery effluents. For this purpose, soil samples

were collected from the rhizosphere plant in sterile polyethylene bags with the help of

sterile spatula and were transported to lab. Isolation and identification of bacteria was

done by conventional microbiological methods. The isolates were screened for metal

resistance and antibiotic resistance. By the result of this study, it was revealed that

Rhizobacteria isolated from the rhizosphere soils which were contaminated with the

17

tannery effluent a were resistant to Cr as well as other heavy metals commonly present in

tannery effluent and these isolated Rhizobacteria can use the tannery effluent as enriched

media for their growth. Further studies were suggested in this area to have better idea to

use these microorganisms for the bioremediation of tannery effluent.

Baz et al. (2015) carried out a study to check the resistance and accumulation of

heavy metals by Actinobacteria which were isolated from abandoned mining area. For

this purpose, soil samples were collected from the abandoned mining areas in sterile

polyethylene bags with the help of sterile spatula and isolation and identification of

Actinobacteria was done by conventional microbiological methods. The isolates were

screened for metal resistance and antibiotic resistance. Molecular characterization of

selected isolates of Actinobacteria was done by isolating the DNA of selected bacteria.

PCR was used to amplify 16S rDNA. By the result of this study, it was observed that

Actinobacteria possessed different level of metal resistance for different metals and it

was concluded that abandoned mining areas are the suitable sites for the isolation of

HMT bacteria. Also the Actinobacteria strains isolated from the mining sites showed

good potential for bioremediation purpose. Further studies, were suggested to enhance

the bioremediation potentialities of the isolated Actinobacteria strains.

Iram & Abrar (2015) designed a study to evaluate the biosorption potential of

heavy metal tolerant fungi isolated from metal contaminated soil. For this purpose, they

collected soil samples and isolated two metal tolerant fungal species (Aspergillus flavus

and Aspergillus niger). The isolated fungal species showed tolerance against copper and

lead. After isolation the biosorption potential of isolates were determined by using

different concentration of metals used at varying pH and temperature. By the results of

this study it was observed that biosorption capacity of A. flavus against copper was 20.75-

93.65 mg/g and biosorption capacity of A. niger against lead was 3.25-172.25 mg/g.

From the present study it was concluded that Aspergillus spp. have the good biosorption

capacity of metals. Further studies, were suggested in this area to have better idea to use

these microorganisms for the bioremediation of heavy metals.

Kumar et al. (2015) evaluated the bioremediation potential of HMT bacteria

isolated from agricultural soil irrigated with industrial wastewater. For this purpose, soil

18

samples were collected from the soil of Ludhiana, India irrigated with industrial effluent,

in sterile polyethylene bags with the help of sterile spatula and isolation and identification

of bacteria was done by conventional microbiological methods. The isolates were

screened for metal tolerance and antibiotic resistance. By the result of this study, it was

found that Bacillus thuringiensis strains possessed better bioremediation potential as

compared to Bacillus subtilis. Further studies, were suggested to enhance the

bioremediation potentialities of the isolated Bacillus thuringiensis.

Pattanayak et al. (2015) carried out a study to evaluate the bioremediation

potential of wild type cadmium resistant bacteria and genetically mutated cadmium

resistant bacteria isolated from industrial effluents. For this purpose, wastewater sample

was collected from Nalco, Kullad, situated in the district of Anugul, Odisha.

Physicochemical parameters such as temperature, pH was measured by using pH meter

and heavy metal concentration was measured by Atomic Absorption Spectrometry

(AAS). Isolation and identification of bacteria was done by conventional microbiological

methods, after the isolation and identification of bacteria the cadmium (Cd) processing

capability of isolates was checked by inoculating the bacteria with different concentration

of cadmium (Cd). It was found that out of three isolated and identified Pseudomonas spp.

only one Pseudomonas aeruginosa strain was able to eliminate Cd from the effluent.

After metal screening the isolate was subjected to mutagenic agents. Then MIC of wild

type P. aeruginosa and mutated P. aeruginosa was measured at two different

concentration of Cd. The results showed that both forms of Pseudomonas (wild and

mutated) removed Cd from the medium at both concentrations of Cd (30 mg/l and 60

mg/l) but most efficient removal was observed at less concentration of Cd. So by the

results of this study it was concluded that biomass of the P. aeruginosa isolated could be

used for the bioremediation of cadmium. Further studies, were suggested to enhance the

bioremediation potentialities of the isolated P. aeruginosa.

Ahirwar et al. (2016) planned a study to isolate and characterize metal tolerant

bacteria from metal affected soil in central India. For this purpose, soil samples were

collected from industrial contaminated soil areas near by different industries. Isolation

and identification of bacteria was done by conventional microbiological methods. The

isolates were screened for metal resistance and antibiotic resistance. It was evident from

19

the results that strains Pseudomonas vulgaris, Pseudomonas fluorescence and Bacillus

cereus were found to be the most efficient strains in terms of metal resistance. So by the

results of this study it was concluded that isolated bacterial strains could be used for the

bioremediation of heavy metals. Further studies, were suggested to enhance the

bioremediation potentialities of the isolated bacterial strains.

Ansari et al. (2016) carried out a study to isolate and characterize metal tolerant

bacteria from metal affected soil in central India. For this purpose, soil samples were

collected from industrial contaminated soil areas near by different industries. Isolation

and identification of bacteria was done by conventional microbiological methods while

molecular characterization of the isolates was done through 16s rRNA technique. The

isolates were screened for metal tolerating capacity. MTC of the heavy metals was

determined using the different concentration of heavy metal salts. Biosorption potential

of the isolates was determined by using atomic absorption spectrometry (AAS). In this

effort six isolates were isolated showing maximum metal tolerance. All the isolates were

identified by PCR and phylogenetic tree (from each sequence obtained from sequencing)

was established, and it was found that out of six isolates four isolates; HM-7, HM-24,

HM-27 and HM-51 were identified as Alcaligenes Spp. and two isolates; HM-6 and HM-

85 as Bacillus cereus. Results of biosorption showed that the isolate accumulated the

metal ions in varying concentrations at different pH and temperature. By the results of

this study it was concluded that the isolated novel bacterial strain could be used for the

purpose of in situ bioremediation of the polluted aqueous systems. Further studies, were

suggested to have better idea to use this microorganisms for the bioremediation of heavy

metals.

Benmalek & Fardeau (2016) evaluated industrial wastewater for the isolation

and characterization of heavy metal resistant bacteria. For this purpose, effluent

samples were collected in sterile bottles and were transported to lab for microbiological

analyses. Isolation and identification of bacteria was done by conventional

microbiological methods, while molecular characterization of the isolates was done

through 16s rRNA technique. The isolates were screened for metal resistance and

antibiotic resistance. In this effort a novel strain of the genus Micrococcus was isolated

which showed metal resistance to different heavy metals screened (Co, Cr, Cu, Ni and

20

Zn). Results of biosorption showed that the isolate accumulated the metal ions in varying

concentrations at different pH and temperature. By the results of this study it was

concluded that the isolated novel bacterial strain could be used for the purpose of in situ

bioremediation of the polluted aqueous systems. Further studies, were suggested to have

better idea to use this microorganisms for the bioremediation of heavy metals.

El-Sayed (2016) designed a study to isolate and characterize heavy metal resistant

bacteria from industrial effluents. For this purpose, effluent samples were collected from

the outlet of plastic factory located at Hafar Al Baten governorate, Saudi Arabia. Samples

were collected in sterile bottles and some physicochemical parameters such as

temperature and pH etc. pH was measured by using pH meter. Isolation and identification

of bacteria was done by conventional microbiological methods, while molecular

characterization of the isolates was done through 16s rRNA technique. The isolates were

screened for metal resistance and antibiotic resistance. It was evident from the results that

strain HAF-13 was the most resistant bacteria strain which were found resistant to heavy

metals (As, Cd, Cr, Hg and Pb) and antibiotics (Amikacin, Amoxicilline, Ceftazidime,

Chloramphenicol, Ciprofloxacin and Vancomycin). It was concluded that industrial use

of heavy metals is main cause of environmental pollution. Further studies, were

suggested in this area to have better idea to use this microorganisms for the

bioremediation of heavy metals.

Govarthanan et al. (2016) designed a study to evaluate the bioremediation

potential of endophytic bacteria Paenibacillus spp. isolated from the roots of Tridax

procumbens. For this purpose, 05 bacterial strains were isolated and screened for heavy

metal (Ag, Cu, Pb and Zn) resistance. Isolation and identification of bacteria was done by

conventional microbiological methods. By the result of this study, it was observed that

bacterial strain RM identified as Paenibacillus spp. was resistant against all the heavy

metals (Ag, Cu, Pb and Zn) tested. So by the results of this study it was concluded that

RM could be used for the bioremediation and detoxification of heavy metals. Further

studies, were suggested in this area to have better idea to use this microorganisms for the


21

Gupta et al. (2016) carried out a study to isolate and characterize heavy metal

resistant bacteria from soil. For this purpose, soil samples were collected in and around of

iron industries of Sonipat district, Haryana, India. Samples were collected in sterile

polyethylene bags with the help of sterile spatula and were transported to lab. Isolation

and identification of bacteria was done by conventional microbiological methods, while

molecular characterization of the isolates was done through 16s rRNA technique. The

isolates were screened for metal resistance and antibiotic resistance. By the result of this

study, it was observed that bacterial strain RT7 identified as Rhizobium halophytocola

was resistant against all the heavy metals (Fe, Mn, Ni and Pb) tested. So by the results of

this study it was concluded that R. halophytocola could be used for the bioremediation

and detoxification of polluted soil.

Guzman et al. (2016) designed a study for the isolation and characterization of

metal resistant bacteria from soil. For this purpose, soil samples were collected from the

surface of industrially effected soil located in Marikina City, Philippines. Samples were

collected in sterile polyethylene bags with the help of sterile spatula and were transported

to lab. Isolation and identification of bacteria was done by conventional microbiological

methods, while molecular characterization of the isolates was done through 16s rDNA

technique. The isolates were screened for metal resistance and antibiotic resistance. MTC

of the heavy metals was determined using the different concentration of heavy metal salts

(CdCl2, Pb (NO3)2, and NiSO4). By the result of this study it was observed that Bacillus

cereus and Bacillus amyloliquefaciens out of all isolated bacterial strains were more

efficient in metal tolerating phenomenon and were able to tolerate Pb up to 2000 µg/ml.

Moreover none of the isolate was able to tolerate more than one metal at a time. Further

studies, were suggested in this area to have better idea to use this microorganisms for the


Mahalingam et al. (2016) carried out a study to isolate and characterize nickel

resistant bacteria from electroplating effluent sediments. For this purpose, wastewater

samples and soil samples were collected bottles and some physicochemical parameters

such as temperature; pH was measured by using pH meter. Isolation and identification of

bacteria was done using conventional microbiological methods. The isolates were

screened for metal resistance minimum inhibitory concentration (MIC) of the nickel was

22

determined by using the different concentration of nickel salt. It was observed that out of

all isolates Pseudomonas Spp. was able to tolerate the high concentration of nickel. By

the results obtained from this study it was concluded that Pseudomonas Spp. could be

used for the bioremediation of nickel. Further studies, were suggested in this area to have

better idea to use these microorganisms for the bioremediation of nickel.

Mihdhir et al. (2016) evaluated wastewater for the isolation, identification and

characterization of heavy metal resistant bacteria. For this purpose, effluent samples

were collected from Makkah city, Saudi Arabia. Samples were collected in sterile bottles

and were transported to lab for microbiological analyses. Isolation and identification of

bacteria was done by conventional microbiological methods, while molecular


screened for metal resistance and minimum inhibitory concentration (MIC) of the heavy

metals was determined using the different concentration of heavy metal salts. Different

bacterial strains showed metal resistance pattern but the isolate S7 identified and

characterized as Pseudomonas aeruginosa was found the most efficient bacterial isolate

which showed metal resistance to different heavy metals screened (Cd, Co, Cu, and Zn).

By the results of this study it was concluded that the isolated bacterial strain could be

used for the purpose of bioremediation of the metal contaminated area. Further studies,

were suggested to have better idea to use this microorganisms for the bioremediation of

heavy metals.

Niveshika et al. (2016) designed a study to isolate and characterize multiple metal

tolerant and antibiotic resistant bacteria from river Ganga, Varanasi, India. For this

purpose, water samples were collected from 05 different Ghats of river. Heterogeneous

groups of bacteria were isolated from all collected samples. Isolation and identification of

bacteria was done by conventional microbiological methods, while molecular


screened for metal resistance and antibiotic resistance. By the result of this study, it was

observed that bacterial strains like Pseudomonas, Serratia, Enterobacter, and Proteus

vulgaris were mainly found at the Dashashwamedh Ghat and the Assi Ghat were able to

tolerate copper, nickel, lead, and chromium up to 200–300 mg/L. It was concluded that

23

mixing of sewage along with industrial effluents into the river was affecting the quality of

water.

Saini et al. (2016) carried out a study to isolate and characterize heavy metal

resistant bacteria from soil. For this purpose, soil samples were collected from the surface

of soil located near the sugar mill industry at Iqbalpur, Roorkee; District Haridwar, India.

Samples were collected in sterile polyethylene bags with the help of sterile spatula and

were transported to lab. Isolation and identification of bacteria was done by conventional

microbiological methods, while molecular characterization of the isolates was done

through 16s rDNA technique. The isolates were screened for metal resistance and

antibiotic resistance. It was concluded that industrial use of heavy metals is main cause of

environmental pollution. Further studies, were suggested in this area to have better idea

to use this microorganisms for the bioremediation of heavy metals.

Marzan et al. (2017) evaluated the bioremediation potential of HMT bacteria

isolated from tannery effluent. For this purpose, samples from different tannery industrial

drain were collected in sterile bottles and were transported to lab. Isolation and

identification of bacteria was done by conventional microbiological methods. By the

result of this study, it was observed that bacterial strains like Gemella spp., Micrococcus

spp. and Hafnia spp. were able to tolerate metal salts. After calculating MIC

bioremediation capability of the isolates was determined. It was found that all three

isolates possessed significant bioremediation potential. Further studies, were suggested in

this area to have better idea to use these microorganisms for the bioremediation of heavy

metals.

24

Chapter 3

METERIALS & METHODS

3.1. Study Area

Faisalabad is the 3rd biggest city in Pakistan after Karachi and Lahore. It is the 2nd

biggest city in the province of Punjab after Lahore, and a major industrial center. The city

is also known as the “Manchester of Pakistan” (Jaffrelot, 2002). Due to the heavy

industrialization, different types of waste are being produced by the different industries.

The textile zone is playing a vital role in the export of the country but at the same time a

lot of environmental pollution is being produced by this zone (Yasar et al., 2013).

Keeping in view the above facts and figures, in the present study sampling was

done from the textile effluent drains present in and around of Faisalabad Punjab Pakistan.

3.1.1. Sample collection

Wastewater samples were collected from the textile effluent. For this purpose, 06

main drains present in and around Faisalabad, Pakistan receiving the textile effluents and

surrounding different textile units were selected. From each drain, 05 samples were taken

keeping the distance of about 1000 meter between two points. In this way 30 samples

were collected and tagged with specific sample codes as given in the Table 1. Samples

were collected in sterile plastic bottles using aseptic techniques, transported on ice to

Postgraduate Research Lab of Department of Microbiology, Government College

University Faisalabad, Pakistan and further processed within 06 hours of collection (Baby

et al., 2014; Srinath et al, 2001).

25

Table 1: Detail of sampling sites along with sample codes

Sr. No. Location of effluent drains Collection

points

Sample

Codes

1. Drain surrounding the textile units located at Jaranwala

road Khurrianwala, Faisalabad Pakistan (KhrD).

P1 (KhrDP1)

P2 (KhrDP2)

P3 (KhrDP3)

P4 (KhrDP4)

P5 (KhrDP5)

2.

Drain surrounding the textile units located at small

industrial estate and main Sargodha road, Faisalabad

Pakistan (SarD).

P1 (SarDP1)

P2 (SarDP2)

P3 (SarDP3)

P4 (SarDP4)

P5 (SarDP5)

3. Drain surrounding the textile units located at Jhumrah

road, Abdullahpur, Faisalabad Pakistan (JhuD).

P1 (JhuDP1)

P2 (JhuDP2)

P3 (JhuDP3)

P4 (JhuDP4)

P5 (JhuDP5)

4. Drain surrounding the textile units located at Satiana

road, Faisalabad Pakistan (SatD).

P1 (SatDP1)

P2 (SatDP2)

P3 (SatDP3)

P4 (SatDP4)

P5 (SatDP5)

5. Drain surrounding the textile units located at Raja

Ghulam Rasool Nagar, Faisalabad Pakistan (RgrD).

P1 (RgrDP1)

P2 (RgrDP2)

P3 (RgrDP3)

P4 (RgrDP4)

P5 (RgrDP5)

6. Drain surrounding the textile units located at Samundri

road Faisalabad Pakistan (SamD).

P1 (SamDP1)

P2 (SamDP2)

P3 (SamDP3)

P4 (SamDP4)

P5 (SamDP5)

26

3.2. Determination of heavy metals in the effluent

For the analysis of different heavy metals i.e. Cobalt (Co), Chromium (Cr), Nickel

(Ni), Lead (Pb) and Zinc (Zn) present in the effluent, water samples (200 mL) were

digested with 5 mL of di-acid mixture (HNO3:HClO4=9:4 ratio) on a hot plate and were

filtered by Whatman no.1 filter paper (Sinha et al., 2014). The analysis for the heavy

metals was done by Atomic Absorption Spectrophotometer (AAS) (Hitachi Polarized

Zeeman AAS, Z-8200, Japan) following the conditions described in AOAC (1990). The

instrumental operating conditions for the said elements are summarized in Table 2.

3.2.1. Preparations of standards for AAS analysis

Calibrated standards were prepared from the commercially available stock

solution (Applichem®) in the form of an aqueous solution (1000 ppm). Highly purified

de-ionized water was used for the preparation of working standards. All the glass

apparatus used throughout the process of analytical work were immersed in 8N HNO3

overnight and washed with several changes of de-ionized water prior to use (AOAC,

1990).

27

Table 2: Operational conditions employed in the determination of Heavy Metals by

Atomic Absorption Spectrophotometer

Parameters

Set Value

Co Cr Ni Pb Zn

Wavelength (nm) 240.7 359.3 232.0 283.3 213.9

Slit Width (nm) 0.2 1.3 0.2 1.3 1.3

Lamp Current (mA) 12.5 7.5 10.0 7.5 10.0

Burner Head Standard

type

Standard

type

Standard

type

Standard

type

Standard

type

Flame Air-C2H2 Air-C2H2 Air-C2H2 Air-C2H2 Air-C2H2

Burner Height (mm) 7.5 7.5 7.5 7.5 7.5

Oxidant gas pressure

(Flow rate) (kpa) 160 160 160 160 160

Fuel gas pressure (Flow

rate) (kpa) 7 12 7 7 6

28

3.3. Measurement of Physico-chemical parameters

The physico-chemical parameters of the effluent samples were measured for all

samples. The pH was determined by digital pH meter, Electric conductivity (EC) was

measured by using EC meter, Dissolved Oxygen (DO) was measured by using DO meter,

Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD) were

measured by titration method (Nanda et al., 2011). Total Dissolved Solids (TDS), Total

Suspended Solids (TSS) and Total Solids (TS) were measured by following the standard

procedures (APHA, 2005).

3.3.1. Biological Oxygen Demand (BOD)

It is a chemical procedure for the determination of the amount of dissolved

oxygen needed by microorganisms in water to break the organic components present in

the water sample at specific temperature and time. For this test to perform usually

incubation time is taken as 5 days and incubation temperature is taken as 20oC.

Principle

The samples were filled in air tight bottles and incubated at 20oC for 05 days. The

dissolved oxygen (DO) content of the samples were determined before and after 05 days

of incubation at 20oC and the BOD was calculated from the difference between initial and

final DO. Manganese sulphate produces a white precipitate of manganese hydroxide

under alkaline conditions which reacts with the DO present in the sample to form a

brown precipitate. While in acidic condition, manganese diverts to its divalent state and

release iodine which is titrated against Sodium thiosulphate using starch as an indicator.

Protocol

1. For each sample four 300 mL glass stoppered BOD bottles were taken (two of

them for sample and two for blank).

2. Then 10 mL of sample was poured into each of two BOD bottles while remaining

portion of bottles was filled with dilution water, in this way the samples were

diluted by 30 times.

29

3. Remaining two BOD bottles were filled with dilution water and kept as

control/blank.

4. After filling, glass stoppers were placed on the BOD bottles and the numbers of

bottles were noted down for further identification.

5. After this two BOD bottles out of four for each sample (01 sample bottle and 01

blank bottle) were preserved for 05 days in BOD incubator at 20oC.

6. The remaining two BOD bottles for each sample were analyzed for the

determination of initial DO.

7. For this purpose, 02ml of manganese sulfate was added to BOD bottles using

pipette.

8. The 02ml of alkali-iodide-azide reagent was added in the same manner. These

solutions were allowed to settle down completely in order to react with oxygen.

9. After the floc has settled to the bottom, the contents were shaken down

thoroughly.

10. Then 02ml of concentrated sulfuric acid was added and bottles were shaken to

dissolve the floc completely.

11. After this the contents were transferred to Erlenmeyer flask and titration was

started.

12. Titration was done with sodium thiosulphate solution until the yellow color of the

liberated iodine was faded out.

13. After that 01ml of starch was added and continued the titration until the blue color

of iodine was faded out to colorless solution.

14. After this the volume of sodium thiosulphate added was measured and noted

down as it gave the DO in mg/L.

15. After 05 days, the bottles from BOD incubator were taken out and analyzed by

repeating the procedure of titration as described.

Calculations for the determination of BOD in effluent samples are shown in the

Table3.

30

Table 3: Calculations for Biological Oxygen Demand (BOD) in effluent samples

Sample

number Day

Volume of

sample

(mL)

Burette

reading (mL)

Volume of

Titrant

(mL)

Na2S2O3

Dissolved

Oxygen

(DO) mg/L Initial Final

Blank 0 200 0 9.0 9.0 9.0

01 0 200 0 8.4 8.4 8.4

03 0 200 0 8.4 8.4 8.4

Blank 05 200 0 8.8 8.8 8.8

02 05 200 0 3.2 3.2 3.2

04 05 200 0 3.2 3.2 3.2

Formula for calculation

Biochemical Oxygen Demand (BOD) = {𝑫𝟎−𝑫𝟓−𝑩𝑪}×𝑽𝒐𝒍𝒖𝒎𝒆𝒐𝒇𝒕𝒉𝒆𝒅𝒊𝒍𝒖𝒕𝒆𝒅𝑺𝒂𝒎𝒑𝒍𝒆

𝑽𝒐𝒍𝒖𝒎𝒆𝒐𝒇𝒕𝒉𝒆𝑺𝒂𝒎𝒑𝒍𝒆𝒕𝒂𝒌𝒆𝒏

Where,

D0 =Initial DO of the diluted sample

D5 =Dissolved oxygen at 05 days of diluted sample

BC (C0- C5) = Blank correction

C0 =Initial DO of blank

C5 = Dissolved oxygen at 05 days of blank

31

3.3.2. Chemical Oxygen Demand (COD)

It is the measurement of the amount of oxygen required for the chemical

oxidation of the pollutants. It determines the quantity of oxygen which is needed for the

oxidation of organic matter present in wastewater samples under specific conditions.

Principle

The organic matter present in the wastewater samples gets oxidized completely by

potassium dichromate (K2Cr2O7) in the presence of sulphuric acid (H2SO4), silver sulfate

(AgSO4) and mercury sulfate (HgSO4) to produce carbon dioxide (CO2) and water (H2O).

The sample is refluxed with the known amount of potassium dichromate (K2Cr2O7) in

sulphuric acid media. Titration is done against the ferrous ammonium sulfate to know the

excess amount of potassium dichromate (K2Cr2O7) by using the ferroin as an indicator. In

this process the dichromate consumed by the sample is considered equivalent to the

amount of oxygen required to oxidize the organic matter.

Protocol

1. For each sample two COD vials with glass stopper were taken (one for sample

and other for blank) and marked.

2. 2.5mL of wastewater sample was poured into the sample vial and 2.5mL of

distilled water in blank vial.

3. After this 1.5mL of already prepared potassium dichromate reagent was added in

both vials followed by 3.5mL of sulphuric acid reagent.

4. After this both vials were capped tightly and kept in the COD digester with preset

temperature of 150o C for two hours.

5. After two hours the vials were removed and cooled to room temperature.

6. Meanwhile the burette was filled with ferrous ammonium sulfate solution and was

fixed to stand for the titration.

7. Then the contents of blank were transferred to the conical flask and provided with

few drops of ferroin indicator.

32

8. Titration was done and end point was noted which was the appearance of reddish

brown colour.

9. Then the added volume of ferrous ammonium sulfate was noted down for blank.

10. The same procedure was repeated for the sample vial.

Calculations for the determination of COD in effluent samples are shown in the

Table 4.

33

Table 4: Calculations for Chemical Oxygen Demand (COD) in effluent samples

Sr. No. Sample Volume of

sample

Burette reading (mL) Volume of

0.1N FAS mL Initial Final

1. Blank 2.5 0 14.1 14.1

2. Sample 2.5 0

13.3 13.3

Chemical Oxygen Demand (COD) = (𝑨−𝑩×𝑵×𝟖×𝟏𝟎𝟎𝟎)

𝒗𝒐𝒍𝒖𝒎𝒆𝒐𝒇𝒔𝒂𝒎𝒑𝒍𝒆𝒕𝒂𝒌𝒆𝒏

Where,

A = Volume of ferrous ammonium sulfate (FAS) for blank

B = Volume of ferrous ammonium sulfate (FAS) for sample

N = Normality of ferrous ammonium sulfate (FAS)

V = Volume of the sample

34

3.4. Selection of heavy metals for the study

Results obtained by the analyses of atomic absorption spectrometry (AAS)

confirmed the presence of an abundant amount of Nickel (Ni) and Cobalt (Co) in all

collected samples. So on the basis of these analyses, these two metals were selected for

further study of heavy metal tolerance by the indigenous bacterial strains.

3.4.1. Preparation of Stock Solutions for Nickel

i. Salt used = Ni(NO3)2.6H2O

ii. MW= 290.80 g/mol

iii. AW of Ni= 58.6934

3.4.1. a. Calculation in mM: For 100 mM concentration

Dissolved 58.6934g in 1000ml distilled water to get 1M solution

Means:

58.6934/ 1000*100 = 5.86934/1000 ml

5.86934/1000 ml = 2.93467/500 ml

Now,

58.6934 g of Ni, in = 290.80 of Ni (NO3)2.6H2O

01 g of Ni = 290.80/58.6934* 2.93467 = 14.54 grams of Ni (NO3)2.6H2O

Finally, to prepare 100 mM solution of Ni, we dissolved 14.54 grams of Ni (NO3)2.6H2O

in 500ml of distilled water.

Formula for calculating working solutions

Vi = Vf×Cf

𝐶𝑖

Where,

35

Initial concentration of stock solution (Ci) = 100 mM

Initial volume of stock solution taken (Vi) = 02 ml

Final media volume required (Vf) = 200 ml

Final concentration (Cf) = 01 mM

Vi = 200×01

100 = 02 ml ( Took 02 ml from stock solution and mixed it with 198 ml of media

to make the final volume 200 ml in order to get 01 mM of nickel in media).

3.4.1. b. Calculation in ppm: For 1000 ppm concentration

i. Salt used = Ni(NO3)2.6H2O


iii. AW of Ni = 58.6934

Calculation in ppm: For 1000 ppm concentration was done as per following formula

1000mg Ni

𝐿×

1g Ni

1000mg Ni×

1 mol Ni

58.69 Ni ×

1 mol Ni (NO3)2.6H2O

1 mol Ni ×

290.80 𝑔 Ni (NO3)2.6H2O

1 mol Ni (NO3)2.6H2O ×

100 𝑔 Ni (NO3)2.6H2O 𝑝𝑜𝑤𝑑𝑒𝑟

98.0 Ni (NO3)2.6H2O = 5.055 grams/liter (2.527 grams of Ni(NO3)2.6H2O salt

dissolved in 500 ml of deionized distilled water to get 1000 ppm concentration of pure

nickel in stock solution).


Vi = Vf×Cf

𝐶𝑖

Where,

Initial concentration of stock solution (Ci) = 1000 ppm



Final concentration (Cf) = 500 ppm

36

Vi = 200×500

1000 = 100 ml ( Took 100 ml from stock solution and mixed it with 100 ml

media, to make the final volume 200 ml in order to get 500 ppm of nickel in media.

3.4.2. Preparation of Stock Solutions for Cobalt

i. Salt used = CoCl2.6H2O


iii. AW of Co = 58.933

3.4.2. a. Calculation in mM: For 100 mM concentration

Dissolved 58.6934 g in 1000ml distilled water to get 1M solution

Means:

58.933/ 1000*100 = 5.933/1000 ml

5.86934/1000 ml = 2.94465/500 ml

Now,

58.933 g of Co, in = 237.93 of CoCl2.6H2O

01 g of Ni = 237.93 /58. 933* 2.94465 = 11.888 grams of CoCl2.6H2O

Finally, to prepare 100 mM solution of Co, we dissolved 11.888 grams of CoCl2.6H2O in

500ml of distilled water.


Vi = Vf×Cf

𝐶𝑖

Where,

Initial concentration of stock solution (Ci) = 100 mM



37

Final concentration (Cf) = 01 mM

Vi = 200×01

100 = 02 ml (Took 02 ml from stock solution and mixed it with 198 ml media

to make the final volume 200 ml in order to get 01 mM of cobalt in media.

3.4.2. b. Calculation in ppm: For 1000 ppm concentration

i. Salt used = CoCl2.6H2O


iii. AW of Ni= 58.933

Calculation in ppm: For 1000 ppm concentration was done as per following

formula

1000mg Co

𝐿×

1g Co

1000mg Co×

1 mol Co

58.9331Co ×

1 mol CoCl2.6H2O

1 mol Co ×

237.93 𝑔 CoCl2.6H2O

1 mol CoCl2.6H2O ×

100 𝑔 CoCl2.6H2O 𝑝𝑜𝑤𝑑𝑒𝑟

98.0 CoCl2.6H2O = 4.119 grams/liter (2.059 grams of CoCl2.6H2O salt dissolve in

500 ml of deionized distilled water to get 1000 ppm concentration of pure cobalt in stock

solution).


Vi = Vf×Cf

𝐶𝑖

Initial concentration of stock solution (Ci) = 1000 ppm



Final concentration (Cf) = 500 ppm

Vi = 200×500

1000 = 100 ml (Took 100 ml from stock solution and mixed it with 100 ml media

to make the final volume 200 ml in order to get 500 ppm of cobalt in media).

3.5. Isolation and identification of HMT bacteria

All the collected effluent samples were serially diluted tenfold in sterile distilled

water up to 10-5 dilutions (Lucious et al., 2013).

38

3.5.1. Bacterial Count

0.1ml from each sample dilution was inoculated in duplicate on pre-sterilized

nutrient agar (Difco, USA) plates. All plates were incubated at 370C in incubator (Binder,

Germany) for 24 hours. Spread plate method of bacterial count was used to count the

bacterial number/ml of the sample. After 24 hours of incubation, the plates containing

250 to 300 colonies of bacteria were selected, colonies were counted using automated

digital colony counter (Irmeco, Germany) and numbers of bacteria were calculated as per

following formula:

CFU/ml of original sample = No. of colonies on plate x reciprocal of dilution factor

Isolation of Nickel and cobalt tolerant bacteria was done through spread plate

method. For this purpose 500ml nutrient agar was prepared in distilled water. Then 05ml

of 100mM Ni (NO3)2 was added in 500ml nutrient agar media. Similarly, 05ml of

100mM CoCl2 was added in 500ml nutrient agar media. Then 0.1ml from each sample

dilution was inoculated onto the nutrient agar plates having 01mM of Ni and Co

concentration and were incubated (Samanta et al. 2012). The numbers Ni and Co tolerant

bacteria were calculated and compared with bacterial counts without adding heavy metals

and percentages of Ni and Co tolerant bacteria were calculated as per following formula.

Percentage of Metal tolerant bacteria = No. of tolerant bacteria (Ni or Co) x 100

No. of bacteria without metal

3.5.2. Determination of Maximum Tolerable Concentration (MTC)

The MTC of heavy metal was selected as the highest concentration of heavy

metal that allowed visible bacterial growth after 48 to 96 hours of incubation. The

increasing concentration of both heavy metals (Ni and Co) i.e. (0.5mM, 1mM, 1.5mM,

02mM, 2.5mM, 03mM, 3.5mM, 04mM, 4.5mM, 05mM, 5.5mM, 06mM, 6.5mM, 07mM,

7.5mM, 08mM, 8.5mM, 09mM, 9.5mM, and 10mM) were added in pre-sterilized

nutrient agar plates for testing the MTCs of isolates (Hassen et al, 1998; Alboghobeish et

al, 2014; Vashishth & Khanna 2015). MTC was determined by two different protocols as

described in detail below.

39

Protocol 01: Assessment of heavy metal tolerance on solid medium

1. Different metal concentrations (0.5mM to 10 mM) from prepared stock solutions

of different heavy metals including Ni and Co were added in pre-autoclaved

nutrient agar at 121oC and 15 lbs/inch2. Metal solutions were separately filter

sterilized using 0.22μm filter paper (Ghane et al., 2013).

2. The medium was poured in Petri plates under aseptic conditions and allowed to

solidify at room temperature. The above isolated HMT bacteria from different

effluent samples were streaked out and were incubated.

3. Then, the plates were observed for the visible bacterial colonies.

4. The plates having visible bacterial growth were selected and the bacterial colonies

were then transferred to the next high concentration of metal using same protocol.

Protocol 02: Assessment of heavy metal tolerance in liquid medium

1. To access the MTC in liquid media, different concentrations of heavy metals (Ni

and Co) were prepared from stock solutions in sterilized glass test tubes with a

final volume of 10ml of growth medium with metal concentrations.

2. Three tubes were prepared for each metal concentration and inoculated with

200µl of 18 hour old isolated bacterial cultures having turbidity equal to

0.5MacFerland solution.

3. A positive control consisting of medium without metal was inoculated with the

same quantity of bacterial culture as described above and a negative control

having medium with metal but without inoculation was also maintained for

comparison.

4. After this the tubes were kept in incubator at 37o C for 03 days. The highest

concentration of metal allowing the growth of bacteria (turbidity) was termed as

the MTC of that metal.

3.5.3. Multi Metal Resistance (MMR)

MMR of bacterial isolates was determined by inoculating the isolated metal

tolerant bacteria on nutrient agar medium incorporated with Nickel (Ni), Cobalt (Co) and

40

Chromium (Cr) in equal concentration i.e. (1:1:1). The MMR of all bacterial isolates was

determined on agar medium as well as in the liquid medium.

3.6. Identification of Bacteria

After 48 hours of incubation, colonies were selected based on the morphology,

shape and color. All the isolates were purified by repeated streaking on nutrient agar and

stored at 4°C for further studies. The isolated bacteria were identified up to genus level

on the basis of cultural characteristics (nutrient agar colonies, slant culture and stab

culture), microscopic examination after Gram’s staining (shape, arrangement and staining

character), and physiological/biochemical characteristics (motility, oxidase reaction,

catalase reaction, glucose utilization & fermentation tests and starch hydrolysis). All

identification tests were performed following the protocols mentioned in Bergey’s

Manual of Determinative Bacteriology.

3.6.1. Gram’s staining

To observe the morphology, arrangement and staining characteristics, all bacterial

isolates were subjected to Gram’s staining by following the protocol described by (Cain

et al., 2013; Lepp et al., 2010).

3.6.2. Motility Test

This test was done to determine the motility of isolates using the following procedure.

1. A drop of distilled water was placed on a cleaned glass slide then a small bacterial

colony was mixed and covered by a cover slip.

2. The motility was observed at 40X magnification of light microscope (Irmeco,

Germany).

3.6.3. Growth on selective and differential culture media

Different types of selective and differential culture media were used for the

identification of bacterial isolates including MacConkey’s agar (Difco, USA), Eosin

Methylene Blue (EMB) agar (Difco, USA), Salmonella Shigella (SS) agar (Difco, USA)

41

and Triple Sugar Iron (TSI) agar (Difco, USA). Characteristics of each medium are

described below.

i. MacConkey’s agar

It is selective as well as a differential medium as it only allows the growth of

Gram -ve bacteria and differentiates the Gram -ve bacteria on the basis of their lactose

fermentation ability. It contains crystal violet and bile salts which inhibits the growth of

Gram +ve bacteria but allows the growth of Gram -ve bacteria. Lactose fermenter Gram -

ve bacteria will appear pink whereas non lactose fermenter Gram -ve bacteria will appear

yellow to colorless.

ii. Eosin Methylene Blue (EMB) agar

It is selective as well as a differential medium and only allows the growth of

Gram -ve bacteria. It contains two dyes i.e. eosin and methylene blue which are toxic for

the Gram +ve bacteria. It differentiates between lactose fermenter and lactose non

fermenter by producing colour. Gram -ve bacteria which can ferment lactose will produce

nucleated colonies (colonies with black center). E. coli in particular produces colonies

showing green metallic sheath on it.

iii. Triple Sugar Iron test

Triple Sugar Iron test is used to differentiate bacteria on the basis of their ability

to ferment three sugars (sucrose, lactose and glucose). Triple Sugar Iron agar was used as

medium as it contains phenol red as indicator which indicates the sugar fermentation and

ferrous ammonium sulphate which indicates the H2S production (Woodland et al., 2004).

3.6.4. Biochemical characterization

Different biochemical tests were performed as per standard protocols for the

identification of bacterial isolates. Principle and brief procedures of these tests have been

described below.

42

i. Catalase test

Catalase test was used to detect the presence of enzyme (catalase). Catalase reacts

with H2O2 and converts it into molecular oxygen (O2) and water (H2O) (Hemraj et al.,

2013; Woodland et al., 2004).

ii. Oxidase test

Oxidase test was performed to evaluate bacterial ability to produce cytochrome c

oxidase. For this purpose oxidase reagent N, N-dimethyl-p-phenylenediamine (DMPD)

was used.

• DMPD reagent was placed on wet filter

• A loopful of bacterial culture was transferred on it and result was recorded.

• Production of blue to purple colour within 2 to 3 minutes indicates the presence of

oxidase positive bacteria.

iii. Indole test

Tryptophan is an essential amino acid produced by bacteria and indole test was

used to differentiate the bacteria on the basis of their ability to produce indole from

tryptophan by enzyme tryptophanase. Indole formation was indicated by Kovac’s reagent

(Woodland et al., 2004; Hemraj et al., 2013).

iv. Methyl red test

Methyl red test was performed to differentiate the bacteria which carry out mixed

acid fermentation from glucose. MR-VP broth was used which contains peptone, glucose

and phosphate buffer. If bacteria have the ability to carry out mixed acid fermentation

then they produce sufficient acid that overcomes the buffering capacity of the broth and

lowers the pH of end product which is indicated by the addition of methyl red. Methyl

red is yellow at pH above 6 and is red at below pH 4.4 (Cain et al., 2004; Hemraj et al.,

2013).

v. Voges-Proskauer test

Voges-Proskauer test determines the ability of bacteria to ferment glucose and

produce acetoin. Two reagents are used in this test; α- naphthol and potassium hydroxide.

43

In the presence of oxygen, α- naphthol catalyze the conversion of acetoin to diacetyl. In

the presence of α- naphthol, diacetyl react with arginine to form red end product.

Potassium hydroxide acts as oxidizing agent and absorbs carbon dioxide. It accelerates

the reaction that converts acetoin to diacetyl (Hemraj et al., 2013).

vi. Citrate utilization test

Citrate utilization test distinguishes the microorganism that utilizes citrate as sole

source of carbon and energy. Citrate utilization test is based on the enzyme “citrate

permease” which is produced by some bacteria. Bromothymol blue is used as indicator

when sodium citrate is the only source of carbon, carbon dioxide is produced which

combine with water and sodium. Sodium carbonate is formed which is responsible for

colour in change from green to blue (Hemraj et al., 2013; Lepp et al., 2010).

vii. Carbohydrate fermentation

Many microorganism use carbohydrates differently to obtain energy depending on

their enzyme complement. Some organisms are capable of fermenting sugars such as

glucose anaerobically while others use the aerobic pathway. Different types of sugars

were used for different tests including arabinose, glucose, inositol, lactose, maltose,

mannitol, mannose, sucrose and starch. For this purpose, different types of broths were

prepared with the addition of sugar and phenol red as indicator. The sugar fermentation

by bacterial isolates was indicated by acid production and thus the decrease in pH of

media. The final colour change from red to yellow was recorded as positive.

3.7. Optimization of growth conditions

The growth conditions (pH and temperature) of isolated HMT bacteria were

optimized. For this purpose 20 glass test tubes were arranged in 05 sets each containing

04 tubes. All test tubes had 10ml of nutrient broth and their pH was adjusted differently

in each set of tubes i.e. Set 1;6, Set 2;6.5, Set 3;7, Set 4;7.5 and Set 5;08. All the tubes

were autoclaved at 121oC and 15lb/inch2. After autoclaving each tube was inoculated

with 20 μL of freshly prepared culture of each bacterial isolate. Then 04 tubes in each set

of tubes were incubated at 25ºC, 30ºC, 37ºC and 40ºC, respectively. After an incubation

44

period of 18 hours, their absorbance was measured at 600 nm using a Lambda 650

UV/Vis Spectrophotometer (PerkinElmer, USA) (Shakoori et al., 2010).

The same experiment was repeated with the addition of metals (Ni and Co) in

nutrient broth at 01mM concentration and the results were compared without and with

metals. Experimental design for optimization of growth conditions is given in Table 5.

45

Table 5: Experimental design for optimization of growth conditions of

HMT bacterial isolates

Experimental

Group

Growth

parameters

Growth conditions

No. of

tubes

Sets of tubes

1 2 3 4 5

Without metal

pH 6 6.5 7.0 7.5 8.0

Tem

peratu

re

I 25ºC 25ºC 25ºC 25ºC 25ºC

Ii 30ºC 30ºC 30ºC 30ºC 30ºC

Iii 37ºC 37ºC 37ºC 37ºC 37ºC

Iv 40ºC 40ºC 40ºC 40ºC 40ºC

With Ni

(01mM)

concentration

pH 6 6.5 7.0 7.5 8.0

Tem

peratu

re

i 25ºC 25ºC 25ºC 25ºC 25ºC

ii 30ºC 30ºC 30ºC 30ºC 30ºC

iii 37ºC 37ºC 37ºC 37ºC 37ºC

iv 40ºC 40ºC 40ºC 40ºC 40ºC

With Co

(01mM)

concentration

pH 6 6.5 7.0 7.5 8.0

Tem

peratu

re

i 25ºC 25ºC 25ºC 25ºC 25ºC

ii 30ºC 30ºC 30ºC 30ºC 30ºC

iii 37ºC 37ºC 37ºC 37ºC 37ºC

iv 40ºC 40ºC 40ºC 40ºC 40ºC

46

3.8. Effect of Ni and Co on bacterial growth

To observe the effect of Ni and Co separately as well as in combination on

bacterial growth, growth curve experiment for all bacterial isolates was conducted in

nutrient broth. For this purpose, nutrient broth tubes with Ni (01mM), Co (01mM), Ni

and Co (0.5 mM each) and without Ni and Co (control) were prepared. For each bacterial

isolate 100 ml medium was taken in one set consisting of 08 test tubes for all four groups

(i.e. three with metals and one control), autoclaved and then inoculated with 20 μL of

freshly prepared inoculum. These tubes were incubated in shaking incubator at 37ºC on

80-100 rpm. Then after 0, 4, 8, 12, 16, 20, 24 and 28 hours one tube out of 08 in each

group was removed and absorbance was measured at 600 nm. Growth curve was plotted

by the readings obtained from the experiment and compared (Shakoori et al., 2010).

3.9. Antibiotic Susceptibility testing

The antibiotic susceptibility testing of all isolates was done by disc diffusion

method to commonly used antibiotics. The turbidity of test inoculum was adjusted

according to 0.5 McFarland standards. The swabs were used to distribute the bacteria

evenly over the entire surface of Mueller Hinton agar plates. The inoculated plates were

left at room temperature to dry and antibiotic discs with the different concentrations were

then applied at equidistance on the surface of a Muller Hinton agar plate. After

incubation, diameters of zones of inhibition around the discs were measured, and the

isolates were classified as sensitive, intermediate and resistant as per CLSI guidelines

(Udobi et al., 2013).

3.9.1. Disc diffusion method

Antibacterial activity of different antibiotics e.g. (Amoxicillin/Clavulanic acid,

Ampicillin, Aztreonam, Ceftriaxone, Cefepime, Imipenem, Meropenem, Nalidixic acid

and Trimethoprim-sulphamethoxazole) against the isolated HMT bacteria was

determined by disc diffusion method (Bhat et al., 2011; Alebachew et al., 2012).

47

3.10. Molecular Characterization

Ribotyping was done for the molecular characterization of identified HMT

bacteria by amplifying 16S rRNA gene. Total genomic DNA was extracted by CTAB

method (Wilson, 2001). Polymerase Chain Reaction (PCR) was used for the

amplification of 16S rRNA using 16S rRNA PCR primers, PA (5′-

AGAGTTTGATCCTGGCTCAG-3′), and PH (5′-AAGGAGGTGATCCAGCCGCA-3′)

(Zaheer et al., 2016). For ribotyping, all the isolates were grown in LB broth and total

genomic DNA was extracted as per detailed protocol given below. After amplification,

the 16S rRNA sequences were compared with known sequences in the GenBank database

(Abbas et al., 2014).

3.10.1. Extraction of genomic DNA

1. 1.5 ml of isolated bacterial cultures were inoculated in the LB broth and incubated

overnight at 37oC.

2. After incubation, the cells were harvested by centrifugation at 6000 rpm, 4oC for 10

minutes until a compact pellet formed.

3. After centrifugation, supernatant was discarded and pellet was resuspended the in a

mixture of 567μl TE (Tris 10 mM; EDTA 1 mM) buffer and 5μl RNAse A.

4. Then the lyses were done by adding 30 μL 10% SDS and 3 μL proteinase K (10

mg/mL). Mixed thoroughly and incubated for 1hour at 30°C until all the cells were

lysed.

5. After incubation time, 100μl of 5M NaCl and 80μl of CTAB/NaCl (10% w/v; 0.7M)

solution were added and lysate were mixed thoroughly and incubated at 65°C for

10minutes.

6. After this the purification of extracted DNA was done by sequential phenol, phenol-

chloroform and chloroform extraction. For this purpose, equal volume of

chloroform/isoamyl alcohol (24:1) was added, mixed thoroughly and centrifuged at

13000 for 5 minutes.

7. Then for the precipitation of DNA isopropanol was added.

48

8. At the end the DNA precipitates were washed with 70% ethanol, for this purpose 1ml

of 70% ethanol was added, centrifuged at 10,000 rpm for 5 minutes. Ethanol was

discarded and drying was done on the bench top at room temperature.

9. After this the pellet was resuspended in 100 µL of TE buffer and stored at -20°C until

used.

3.10.2. PCR amplification

The reaction was performed using BactReady™ multiplex PCR system

(Genescript, USA). The reaction mixture (20 μL) was prepared in thin walled with flat

cape, DNase-RNase free 0.2mL Thermo-Tubes (Thermo-scientific, UK) with 1 μL of

template DNA. Amplifications were performed using a micro-processed controlled

Swift™ Maxi Thermal Cycler Block (ESCO Technologies Inc. France) under the

following conditions: activation of Script™ DNA polymerase at 94ºC for 15 minutes

followed by 35 cycles of denaturation (95ºC for 1 minute), annealing (55ºC for 1 minute),

extension (72ºC for 1 min), and a final extension step at 72ºC for 3 minutes. The

composition of reaction mixture is given in the Table 6.

3.10.3. Agarose gel electrophoresis

The amplicons were analyzed by agarose gel electrophoresis using a horizontal

mini agarose gel electrophoresis system (ENDURO™ Labnet International Inc.,

Woodbrige, USA). PCR products were eluted using a gel extraction kit (Fermentas,

Germany) and sent for commercial sequencing (Eurofins MWG Operon LLC, USA).

49

Table 6: Composition of PCR reaction mixture used for amplification

Reagents Volume (µL) Final concentration

PCR grade (DNAse free) water 7 ----

Forward primer 1 200nM

Reverse primer 1 200nM

DNA solution 1 ----

PCR premix 10 ----

Total volume 20 ----

50

3.10.4. Phylogenetic analysis

The 16S rRNA gene from three pure culture sequences from the NCBI database

were aligned using Clustal X (Thompson et al., 1997) and the maximum likelihood

(ML)-based phylogenetic tree was constructed using MEGA (version 6) (Tamura et al.,

2013).


strains

The biosorption potential of isolated and characterized indigenous HMT bacterial

strains was determined against two metals i.e. Nickel (Ni) and Cobalt (Co). For this

purpose, one set (each containing 02 glass culture bottles) having capacity of 500ml was

prepared for each isolate and then supplemented with 200ml of LB broth with initial

metal concentration of 50ppm for each metal. After autoclaving at 121oC each set was

inoculated with 02 ml of 18-hour old bacterial culture having turbidity equal to

0.5McFarland turbidity solution. Then these culture bottles were kept under constant

agitation at 37oC for 24 and 48 hours. After specified incubation time the cultures were

centrifuged at 14,000 rpm for 05 minutes and supernatants were used for the

determination of residual metal concentrations by using

Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) (Shakoori et al.,

2010; Nanda et al., 2011; Alboghobeish et al., 2014).

3.11.1. Determination of heavy metals in supernatant

For the analysis of concentrations of heavy metals i.e. Nickel (Ni) and Cobalt

(Co) present in the supernatant, effluent samples (200 mL) were digested with 5 mL of

di-acid mixture (HNO3:HClO4=9:4 ratio) on a hot plate and filtered by Whatman no.1

filter paper (Sinha et al, 2014). The analysis for the heavy metals remained in the samples

was done by ICP-OES (Agilent Technologies) following the conditions described in

APHA 3120 B (1990). The instrumental operating conditions for the said metals are

summarized in Table 7.

51

Table 7: The instrumental operating conditions for heavy metal analysis through

Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES)

Parameters Ni Co

Wavelength (nm) 231.6 238.8

Plasma Argon Argon

Torch Height (mm) 10 10

Plasma Flow (l/min) 15 15

Auxiliary Flow (l/min) 1.5 1.5

Nebulizer Flow (l/min) 0.75 0.75

52

3.11.2. Preparation of standards for ICP-OES analysis

Calibrated standards were prepared from the commercially available stock

solution (AccuStandard®) in the form of an aqueous solution (APHA 3120 B).

3.11.3. Estimation of metal Reduction

Percentage metal reduction was calculated by using the following formula

Percentage metal reduction = { Ic–Fc

Ic× 100}

Where,

IC = Initial concentration of metal used for the experiment

FC= Final concentration of metal remained after the experiment

3.12. Preparation of samples for FTIR and SEM

The lyophilized samples were required to perform the above mentioned analyses.

For this purpose, 02 sets (each containing 04 tubes) for each bacterial strain were

prepared. Then 100ml of nutrient broth was prepared with and without metal for each

strain. The metal concentration used was 01mM. After autoclaving at 121oC the prepared

media was inoculated with 01ml of 18-hour old bacterial culture and incubated at

optimum temperature for 24 and 48 hours separately. Experimental design for preparation

of samples is given in Table 8. After incubation time the cultures were harvested by

centrifugation at 14000 rpm for 05 minutes. The pellets were washed thrice, suspended in

0.9% normal saline and transferred to sterilized eppendrof tubes for lyophilization (Durve

& Chandra., 2014). After lyophilization of samples, powder (lyophilized) form of

bacterial cultures was used to perform FTIR and SEM analyses.

3.12.1. Lyophilization of samples

Lyophilization or Freeze-drying is a process used to remove water from the frozen

samples. For this purpose, bacteria are suspended in an appropriate protective medium,

53

frozen and exposed to a vacuum. After this the bacteria are stored under vacuum in glass

vials. Protocol for the lyophilization of samples is given below (Pastorino et al, 2015;

Kang et al, 2010).

3.12.1. a. Preparation & filling of vials

Flat bottomed glass vials (03 ml) were washed with a detergent rinsed in tap water

and then in deionized water. Then these vials were sterilized at 121°C for 20 minutes and

labeled before use. 10% skim milk was used as suspension media. Then equal volume

(0.5ml) of harvested culture was mixed with the equal volume (0.5ml) of suspension

medium (10% skim milk). In this way final volume of cell suspension was made 01ml.

Then prepared vials were filled with cell suspension. Filling was carried out under aseptic

conditions using a sterile syringe. After filling the vials, sterile double cut stopper were

placed on the mouth of the vials and filled vials were proceeded for the process of freeze-

drying (Lyophilization) by using VirTis lyophilizer (genesis 25 LE, VirTis, NY).

3.12.1. b. Lyophilization

Following lyophilization protocol was adapted:

• Freezing at -40°C for 08 hours.

• Primary drying at -35°C for 05 hours.

• Secondary drying at (-5°C for 03 hours; at 0°C for 03 hours; at 5°C for 03 hours;

at 10°C for 05 hours; at 15°C for 06 hours and at 20°C for 07 hours).

• During whole process pressure was maintained at 50 to 100 militorr and the

condenser temperature was maintained at -40°C. Stoppering of the vial was done

under vacuum at the completion of lyophilization process.

• After freeze-drying the prepared ampoules were stored at 04°C.

54

Table 8: Experimental design for lyophilization of samples used in FTIR and SEM

Bacterial

strain

Metal used

Incubation time

Nickel (Ni)/Cobalt (Co)

24 hours 48 hours

Isolate (with metal) Isolate (with metal)

Isolate (without metal) Isolate (without metal)

55

3.13. Fourier Transform Infrared Spectroscopy (FT-IR)

Fourier Transform Infrared Spectroscopy (FT-IR) was used to analyze the

functional groups and overall nature of chemical bonds in the isolates. Infrared spectra of

the control (bacteria grown without metal stress) and tested (bacteria grown with metal

stress, Ni or Co) biomass were obtained by grinding 02 mg of freeze-dried biomass with

200mg dry potassium bromide (KBr) powder (1:100) ratio in agate mortar. After this the

obtained mixture was pressed to obtain translucent sample disks using pressure bench

press. The FTIR- analysis was performed by using PerkinElmer Spectrum Version

10.4.3. The spectral data were collected over the range of 450 – 4000 cm-1

(Ramyakrishna & Sudhamani 2016).

3.14. Scanning Electron Microscopy (SEM)

Outer morphology of the bacterial cells before and after biosorption was

examined through scanning electron microscopy (SEM) to observe the effect of metals on

bacterial cells (Carl Zeiss Supra 55 Gemin; German Technology, Jena, Germany).

Prepared samples were placed on the sample holder (stub) with carbon tape. In order to

increase the electron conduction and to improve the quality of micrographs, a conductive

layer of gold was made with portable SC7620 ‘Mini’ sputter coater/glow discharge

system (Quorum Technologies Ltd, Laughton, UK) (Michalak et al., 2014). Thereafter,

the samples were placed in a sample holding vacuum chamber and a voltage of 500 kV

was applied. Images were captured by signal SE2 detectors with a working distance of

6.8 mm. The spot sizes varied from 2μm to 200nm depending on the applied

magnifications (Ramyakrishna & Sudhamani 2016).

3.16. Statistical analysis

The data was analyzed by calculating Means ± SE, Analysis of Variance

(ANOVA), Regression, co-relation and Z-test was performed by using Minitab software.

P value was calculated and the value less than 0.05 were considered as significant

(P<0.05) and results showing P value less than 0.01 was considered as highly significant

(P<0.01).

56

Chapter 4

RESULTS & DISCUSSION

The present study was conducted in the Department of Microbiology,

Government College University Faisalabad Pakistan. Six main drains present in and

around Faisalabad, receiving the textile effluents and surrounding different textile units

were selected. From each drain, 05 effluent samples were collected at the distance of

about 1000 meter between two points. In this way, total 30 samples were collected and

subjected to the analysis for the presence of heavy metals like Ni, Co, Cr, Zn and Pb. The

physico-chemical properties like pH, EC, DO, COD, BOD, TDS, TSS and TS were

measured. Then the isolation and identification of HMT bacteria was done by growing

the bacterial isolates on selective growth media having different concentrations of metal

salts. Molecular characterization and phylogenetic analysis of isolated bacteria was done

through PCR and sequencing. Antibiotic susceptibility pattern of HMT bacteria was

determined through disc diffusion method. Biosorption potential of isolated HMT

indigenous bacterial strains was evaluated by inductively coupled plasma optical

emission spectroscopy (ICP-OES). FTIR was used to analyze the functional groups and

overall nature of chemical bonds in the isolates in response to heavy metal stress.

Finally, scanning electron microscopy (SEM) was done to observe any surface

morphological changes developed in HMT bacteria due to metal stress.

4.1. Determination of heavy metals in effluent

All 30 samples of textile effluent were analyzed for the presence of heavy metals

including Ni, Co, Cr, Zn and Pb. The results of AAS revealed that Nickel (Ni) was

present in almost all samples at concentrations between 0.07ppm to 0.27ppm and the

highest concentration of Nickel (Ni) i.e. 0.27ppm was found in two samples collected

from drain surrounding the textile units located at small industrial estate and main

Sargodha road, Faisalabad Pakistan (SarDP1, SarDP4). Cobalt (Co) was ranked as the

second most abundant heavy metal in the collected samples at the concentration range

between 0ppm to 0.28 ppm. The maximum concentration of Cobalt (Co) was also found

in sample (SarDP1) collected from the industrial drain located at small industrial estate

57

and main Sargodha road, Faisalabad. On the basis of these results, Nickel (Ni) and Cobalt

(Co) were selected for further study. The results of heavy metal analysis through AAS

have been presented in Table 9 whereas the statistical analyses of the same have been

shown in Table 10 and 11.

58

Table 9: Results of heavy metal analysis in industrial effluent through atomic

absorption spectrophotometer (AAS)

Sr. No. Sample Code

& No.

Concentration of heavy metals in ppm

Ni Co Cr Pb Zn

1 KhrDP1 0.24 0.22 0.05 0.40 0.20

2 SarDP1 0.27 0.28 0.11 0.16 0.32

3 JhuDP1 0.24 0.14 0.05 0.00 0.10

4 SatDP1 0.19 0.00 0.00 0.00 0.18

5 RgrDP1 0.24 0.19 0.04 0.008 0.48

6 SamDP1 0.17 0.25 0.13 0.6 0.37

7 KhrDP2 0.10 0.21 0.003 0.8 0.25

8 SarDP2 0.21 0.13 0.10 0.1 0.31

9 JhuDP2 0.25 0.18 0.14 0.12 0.14

10 SatDP2 0.20 0.20 0.06 0.00 0.30

11 RgrDP2 0.19 0.21 0.08 0.00 0.27

12 SamDP2 0.21 0.00 0.16 0.00 0.40

13 KhrDP3 0.23 0.22 0.1 0.00 0.42

14 SarDP3 0.17 0.19 0.05 0.004 0.38

15 JhuDP3 0.16 0.22 0.09 0.007 0.35

16 SatDP3 0.22 0.19 0.10 0.14 0.28

17 RgrDP3 0.07 0.13 0.002 0.18 0.13

18 SamDP3 0.14 0.20 0.00 0.16 0.10

19 KhrDP4 0.17 0.24 0.00 0.002 0.20

20 SarDP4 0.27 0.16 0.10 0.00 0.30

21 SatDP4 0.19 0.23 0.07 0.00 0.15

22 JhuDP4 0.15 0.14 0.09 0.10 0.24

23 RgrDP4 0.24 0.27 0.15 0.00 0.09

24 SamDP4 0.24 0.00 0.05 0.19 0.12

25 KhrDP5 0.12 0.19 0.00 0.00 0.08

26 SarDP5 0.23 0.17 0.00 0.10 0.37

27 SatDP5 0.25 0.18 0.14 0.005 0.39

28 JhuDP5 0.23 0.19 0.12 0.15 0.27

29 RgrDP5 0.10 0.24 0.17 0.12 0.25

30 SamDP5 0.24 0.19 0.00 0.00 0.10

59

Table 10: Analysis of variance (mean squares) for heavy metals present in effluent samples

Source of

variation

Degrees of

freedom

Mean squares

Ni Co Cr Pb Zn

Location

Error

Total

5

24

29

0.00300NS

0.00277

0.00621NS

0.00481

0.00268NS

0.00309

0.03513NS

0.03466

0.00944NS

0.01387

NS = Non-significant (P>0.05); * = Significant (P<0.05); ** = Highly significant (P<0.01)

Table 11: Comparison of means for heavy metals present in effluent samples

Location Means ± SE

Ni Co Cr Pb Zn

KhrD 0.172±0.028A 0.216±0.008A 0.031±0.020A 0.240±0.160A 0.230±0.055A

SarD 0.230±0.019A 0.186±0.025A 0.072±0.021A 0.073±0.031A 0.336±0.016A

JhuD 0.218±0.018A 0.190±0.016A 0.098±0.018A 0.026±0.023A 0.226±0.060A

SatD 0.198±0.014A 0.144±0.037A 0.074±0.021A 0.078±0.033A 0.254±0.021A

RgrD 0.168±0.035A 0.208±0.024A 0.088±0.032A 0.062±0.037A 0.244±0.068A

SamD 0.200±0.020A 0.128±0.053A 0.068±0.033A 0.190±0.110A 0.218±0.068A

Means sharing similar letters in a column are statistically non-significant (P>0.05)

60

4.2. Measurement of physico-chemical parameters

The different physico-chemical parameters of all effluent samples were measured.

Digital pH meter was used to determine the pH, Electric Conductivity (EC) was

measured by using EC meter, Dissolved Oxygen (DO) was measured by using DO meter,

Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD) were

measured by titration method. Total Dissolved Solids (TDS), Total Suspended Solids

(TSS) and Total Solids (TS) were measured by following the standard procedures

(APHA, 2005).

It was observed that all samples collected from the industrial drain located at

Khurrianwala, Faisalabad had pH ranging from 7.51 to 8.61, EC from 103.2 µS/cm to

127.6 µS/cm, DO from 1.19 mg/l to 3.76 mg/l, COD from 115 mg/l to 254 mg/l, BOD

from 47 mg/l to 101.8 mg/l, TSS from 149 mg/l to 215 mg/l, TDS from 3482 mg/l to

4549 mg/l and TS ranging from 363 mg/l to 4767 mg/l.

The five samples collected from the industrial drain located at small industrial estate

and main Sargodha road, Faisalabad had pH ranging from 7.3 9 to 8.28, EC from 104.9

µS/cm to 120.7 µS/cm, DO from 1.19mg/l to 2.78 mg/l, COD from 115.9 mg/l to 288

mg/l, BOD from 40 mg/l to 116 mg/l, TSS from 135.75 mg/l to 198.8 mg/l, TDS from

3350 mg/l to 3980 mg/l and TS ranging from 3485.75 mg/l to 4178.8 mg/l.

All the samples collected from the industrial drain located at Jhumrah road,

Abdullahpur, Faisalabad had pH ranging from 8.66 to 7.58, EC from 118.9 µS/cm to

159.7 µS/cm, DO from 1.19 mg/l to 3.5 mg/l, COD from 115.3 mg/l to 280 mg/l, BOD

from 44.8 mg/l to 112.6 mg/l , TSS from 125 mg/l to 178 mg/l, TDS from 2765 mg/l to

3750 mg/l and TS ranging from 2890 mg/l to 3928 mg/l.

Whereas the samples collected from the drain located at Satiana road, Faisalabad had

pH from 8.62 to 7.09, EC from 117.7 µS/cm to 159.7 µS/cm, DO from 1.55 mg/l to 3.67

mg/l, COD from 115.7 mg/l to 267 mg/l, BOD from 44.9 mg/l to 107.4 mg/l, TSS from

122 mg/l to 230.45 mg/l, TDS from 2950 mg/l to 3980 mg/l and TS ranging from 3070

mg/l to 4210.45 mg/l.

61

Similarly, the samples collected from the drain located at Raja Ghulam Rasool Nagar,

Faisalabad had pH ranging from 7.02 to 8.87, EC from 103.7 µS/cm to 152.7 µS/cm, DO

from 1.58 mg/l to 3.88 mg/l, COD from 116.78 mg/l to 261 mg/l, BOD from 46.77 mg/l

to 105.3 mg/l, TSS from 130 mg/l to 240 mg/l, TDS from 3200 mg/l to 4370 mg/l and

TS ranging from 3330 mg/l to 4360 mg/l.

The samples collected from the drain located at Samundri road Faisalabad, had pH

ranging from 7.03 to 8.9, EC from 104.9 µS/cm to 156.3 µS/cm, DO from 1.2 mg/l to

3.76 mg/l, COD from 110.47 mg/l to 270 mg/l, BOD from 42.3 mg/l to 108.6 mg/l, TSS

from 137 mg/l to 248 mg/l, TDS from 3370 mg/l to 4567 mg/l and TS ranging from 3507

mg/l to 4815 mg/l.

The overall results of physico-chemical parameters in effluent samples collected

from all locations are given in Table 12 in comparison to the limits of National

Environmental Quality Standards (NEQS) for wastewater discharge set by Government

of Pakistan. The analysis of variance and comparison of means for physico-chemical

parameters is shown in Table 13 and 14.

62

Table 12: Results of Physico-Chemical parameters of collected effluent samples

*NEQS limits: National Environmental Quality Standards for wastewater discharge set by

Government of Pakistan

**NG: Not given in the NEQS list

Parameters pH EC DO COD BOD TSS

TDS

TS

*NEQS limits 6-10 **NG **NG 150 80 150 3500 **NG

Sr. No. Sample

Code & No. - (µS/cm) (mg/l)

1 KhrDP1 7.51 117.7 1.2 115 47 210 3740 3950

2 SarDP1 7.86 119.4 1.19 203 82.2 180.3 3643 3823.3

3 JhuDP1 8.66 125.2 1.55 118 46.6 155.66 3450.70 3606.36

4 SatDP1 8.62 156.3 2.06 264 104.8 230.45 3980 4210.45

5 RgrDP1 7.02 103.7 3.88 261 105.3 240 4100 4340

6 SamDP1 7.03 104.9 3.76 257 103.4 237.65 3950 4187.65

7 KhrDP2 7.55 127.6 2.78 224 88.6 160.9 3553 3713.9

8 SarDP2 7.83 120.7 1.67 165 67 135.75 3350 3485.75

9 JhuDP2 7.9 118.9 1.26 208 83.6 155 3290 3445

10 SatDP2 7.95 159.7 3.67 267 107.4 140 2950 3090

11 RgrDP2 8.65 125.2 1.58 120 49 130 3200 3330

12 SamDP2 8.56 156.3 1.2 116 47.2 137 3370 3507

13 KhrDP3 7.54 103.7 1.19 196 78.6 206 4205 4411

14 SarDP3 7.39 104.9 1.55 110 44.8 195 3870 4065

15 JhuDP3 8.02 127.6 2.06 280 112.6 125 2950 3075

16 SatDP3 7.09 117.7 1.55 120 48 122 3149 3271

17 RgrDP3 8.1 119.4 2.06 250 100.5 143 3308 3451

18 SamDP3 8.23 127.6 3.88 270 108.6 147.7 3492 3639.7

19 KhrDP4 7.44 120.7 3.76 254 101.8 215 4549 4764

20 SarDP4 8.28 118.9 2.78 288 116 198.8 3980 4178.8

21 JhuDP4 8.66 159.7 1.19 200 82.6 178 3750 3928

22 SatDP4 7.51 127.3 1.55 170.8 75.8 166 3680 3846

23 RgrDP4 7.86 115.8 2.06 183.6 78.2 235 4370 4605

24 SamDP4 8.66 116.7 1.55 189.8 79.9 248 4567 4815

25 KhrDP5 8.61 103.2 2.06 168.5 67.3 149 3482 3631

26 SarDP5 7.89 114.3 2.29 105.9 40 142 3370 3512

27 JhuDP5 7.58 149.5 3.5 115.3 45.2 125 2765 2890

28 SatDP5 7.23 123.8 3.57 115.7 44.9 128 2950 3078

29 RgrDP5 8.87 152.7 2.88 116.78 46.77 220 4140 4360

30 SamDP5 8.9 134.5 2.34 110.47 42.3 184 3942 4126

63

Table 13: Analysis of variance (mean squares) for physico-chemical parameters

Source of

variation

Degrees of

freedom

Mean squares

pH EC DO COD BOD TSS TDS TS

Location

Error

Total

5

24

29

0.30421NS

0.33854

472.197NS

258.844

0.4412NS

0.9970

175.71NS

4869.00

32.363NS

799.903

1849.52NS

1609.97

402571NS

194280

457650NS

227863

Table 14: Comparison of means for physico-chemical parameters

Location pH EC DO COD BOD TSS TDS TS

KhrD 7.73±0.22A 114.58±4.82A 2.20±0.49A 191.50±23.84A 76.66±9.34A 188.18±13.77A 3905.8±204.3A 4094.0±215.5A

SarD 7.85±0.14A 115.64±2.89A 1.90±0.28A 174.38±33.65A 70.00±13.80A 170.37±13.26A 3642.6±127.6A 3813.0±140.6A

JhuD 8.16±0.21A 136.18±7.82A 1.91±0.43A 184.26±30.92A 74.12±12.72A 147.73±10.16A 3241.1±175.6A 3388.9±185.5A

SatD 7.68±0.28A 136.96±8.74A 2.48±0.47A 187.50±33.29A 76.18±13.35A 157.29±19.79A 3341.8±208.1A 3499.1±226.2A

RgrD 8.10±0.33A 123.36±8.14A 2.49±0.41A 186.28±30.72A 75.95±12.34A 193.60±23.63A 3823.6±237.7A 4017.2±260.8A

SamD 8.28±0.33A 128.00±8.67A 2.55±0.55A 188.65±33.68A 76.28±13.77A 190.87±22.66A 3864.2±211.0A 4055.1±231.6A

64

4.3. Isolation and identification of HMT bacteria

4.3.1. Bacterial count

For the estimation of bacterial count in effluents, diluted samples were streaked

on general purpose media i.e. nutrient agar, and selective media i.e. nutrient agar

incorporated with Nickel (Ni) and Cobalt (Co) for the screening of HMT bacteria. It was

observed that the samples collected from the industrial drain located at Khurrianwala,

Faisalabad had an overall bacterial population ranged from 3.4×105 to 8.9×105/ml,

whereas, Nickel resistant bacteria ranged from 0 to 45×10-5/ml and Cobalt resistant

bacteria were from 0 to 40×10-5/ml. The samples collected from the industrial drain

located at small industrial estate and main Sargodha road Faisalabad had bacterial load

ranged from 2.7 to 8×105/ml with Nickel resistant bacteria from 0 to 26×10-5/ml and

Cobalt resistant bacteria from 12 to 38×10-5/ml.

Similarly, the samples collected from the industrial drain located at Jhumrah road,

Abdullahpur, Faisalabad had bacterial population ranged from 1.9 to 78×105/ml with

Nickel resistant bacteria from 0 to 65×10-5/ml and Cobalt resistant bacteria from 0 to

70×10-5/ml. Whereas, the samples collected from the drain located at Satiana road,

Faisalabad had bacterial load ranged from 7.2 to 109×105/ml with Nickel resistant

bacteria ranged from 0 to 30×10-5/ml and Cobalt resistant bacteria from 0 to 25×10-5/ml.

The samples collected from the drain located at Raja Ghulam Rasool Nagar,

Faisalabad had bacterial population ranged from 9.2 to 101×105/ml with Nickel resistant

bacteria from 0 to 50×10-5/ml and Cobalt resistant bacteria from 0 to 40×10-5/ml.

Similarly, the samples collected from the drain located at Samundri road Faisalabad had

bacterial load ranged from 5.3 to 52×105/ml with Nickel resistant bacteria from 0 to

28×10-5/ml and Cobalt resistant bacteria from 0to 32×10-5/ml. The results of bacterial

count without and with metals are given in the Table 15, whereas analysis of variance and

comparison of means for growth of bacteria without and with metals is shown in Table

16 and 17.

65

Table 15: Bacterial counts on culture media without and with heavy metals

Sr.

No.

Sample

Code &

No.

CFU/ml

(×105)

on Nutrient

agar

CFU/ml

on Nutrient

agar with

Ni

(%) age of

Ni tolerant

bacteria

(×10-5)

CFU/ml

on Nutrient

agar with

Co

(%) age of

Co tolerant

bacteria

(×10-5)

1 KhrDP1 3.4 15 4.41 20 5.88

2 SarDP1 8 20 0.025 12 1.5

3 JhuDP1 10 00 00 06 0.6

4 SatDP1 92 00 00 00 00

5 RgrDP1 101 00 00 00 00

6 SamDP1 8.1 00 00 00 00

7 KhrDP2 6.5 32 4.92 10 1.538

8 SarDP2 3.4 25 7.35 38 11.17

9 JhuDP2 22 00 00 20 0.90

10 SatDP2 109 05 0.045 10 0.091

11 RgrDP2 63 00 00 10 0.15

12 SamDP2 5.3 00 00 10 1.88

13 KhrDP3 8.9 45 5.05 40 4.49

14 SarDP3 4.6 00 00 18 3.91

15 JhuDP3 78 00 00 00 00

16 SatDP3 7.3 00 00 00 00

17 RgrDP3 86 50 0.581 40 0.465

18 SamDP3 52 00 00 00 00

19 KhrDP4 9.7 00 00 00 00

20 SarDP4 13.5 26 1.92 20 1.48

21 JhuDP4 11.7 00 00 20 0.170

22 SatDP4 18 00 00 00 00

23 RgrDP4 75 10 0.133 15 0.2

24 SamDP4 7.1 28 3.94 32 4.5

25 KhrDP5 4.9 23 4.69 30 6.122

26 SarDP5 2.7 10 3.70 15 5.555

27 JhuDP5 1.9 65 34.21 70 36.842

28 SatDP5 7.2 30 4.16 25 3.47

29 RgrDP5 9.2 40 4.34 00 00

30 SamDP5 2.8 00 00 00 00

66

Table 16: Analysis of variance (mean squares) table for growth of bacteria without and with metals

Source of

variation

Degrees

of

freedom

Mean squares CFU/ml

on Nutrient

agar(× 105)

CFU/ml

on Nutrient

agar with Ni

(%) age

of Ni tolerant

bacteria

CFU/ml

on Nutrient

agar with Co

(%) age

of Co tolerant

bacteria

Location

Error

Total

5

24

29

2955.41*

849.56

242.293NS

355.583

28.3569NS

43.0241

234.353NS

282.967

41.6977NS

49.1910

Table 17: Comparison of means for growth of bacteria without and with metals

Location Mean ± SE

CFU/ml

on Nutrient

agar(× 105)

CFU/ml

on Nutrient

agar with Ni

(%) age

of Ni tolerant

bacteria

CFU/ml

on Nutrient

agar with Co

(%) age

of Co tolerant

bacteria

KhrD 6.68±1.18B 23.00±7.61A 3.81±0.96A 20.00±7.07A 3.61±1.22A

SarD 6.44±1.99B 16.20±4.94A 2.60±1.37A 20.60±4.56A 4.72±1.79A

JhuD 24.72±13.7AB 13.00±13.00A 6.84±6.84A 23.20±12.34A 7.70±7.29A

SatD 46.70±22.2AB 7.00±5.83A 0.84±0.83A 7.00±4.90A 0.71±0.69A

RgrD 66.84±15.7A 20.00±10.49A 1.01±0.84A 13.00±7.35A 0.16±0.09A

SamD 15.06±9.28AB 5.60±5.60A 0.79±0.79A 8.40±6.21A 1.28±0.88A

Means sharing similar letters in a column are statistically non-significant (P>0.05)

67

4.3.2. Determination of MTC of Nickel (Ni)

The MTC of Nickel (Ni) was taken as the highest concentration of Nickel (Ni) that

allowed visible bacterial growth after 48 to 96 hours. The increasing concentration of

Nickel (Ni) i.e. 0.5mM, 1mM, 1.5mM, 02mM, 2.5mM, 03mM, 3.5mM, 04mM, 4.5mM,

05mM, 5.5mM, 06mM, 6.5mM, 07mM, 7.5mM, 08mM, 8.5mM, 09mM, 9.5mM and

10mM were added in nutrient agar plates to determine the MTCs of isolates in the solid

media and same concentrations of Nickel (Ni) were added in the nutrient broth to

determine the MTCs of isolates in the liquid media.

For this purpose, thirteen effluent samples exhibited bacterial growths on the

screening media (nutrient agar incorporated with 0.5mM of Ni) were selected and their

MTC against Nickel (Ni) was determined. Bacterial isolates showing growth above

06mM concentration of Ni were selected for the further studies. From the results, it was

observed that bacterial population in three samples i.e. SarDP2, RgrDP3 and SarDP5

tolerated maximum Ni concentration up to 08mM. MTC values of different samples

against Ni are shown in Table 18 whereas; number of isolates tolerant to Ni present in

different effluent samples are presented in Table 19. Then pure cultures of bacteria from

these samples were obtained by streaking and single colonies were grown for the further

studies. Regression line showing relation between Ni concentration and number of

bacteria for effluent sample SarDP2, RgrDP3 and SarDP5 have been shown in Figure 1, 2

and3 respectively whereas the overall relationship has been exhibited in Figure 4.

68

Table 18: MTC of Nickel (Ni) shown by bacterial population present in collected effluent

samples

Sr.

No.

Sample

Code &

No.

Concentration of Ni (mM)

1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

1 KhrDP1 + + - - - - - - - - - - - - - - -

2 KhrDP2 + + - - - - - - - - - - - - - - -

3 SarDP2 + + + + + + + + + + + + + + + - -

4 JhuDP2 + + + + + + + + - - - - - - - - -

5 SatDP2 + + + + + + + + + + - - - - - - -

6 SatDP3 + + + + + + + + + + - - - - - - -

7 RgrDP3 + + + + + + + + + + + + + + + - -

8 KhrDP4 + + - - - - - - - - - - - - - - -

9 SarDP4 + + - - - - - - - - - - - - - - -

10 RgrDP4 + - - - - - - - - - - - - - - - -

11 SamD4 + + - - - - - - - - - - - - - - -

12 KhrDP5 + + + + + + + + + + - - - - - - -

13 SarDP5 + + + + + + + + + + + + + + + - -

69

Table 19: Number of isolates growing at different concentrations of Nickel (Ni) present in


Sr. No.

Sample

Code &

No.

Concentration of Ni (mM)

1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

1 KhrDP1 3 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

2 KhrDP2 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

3 SarDP2 7 6 6 6 5 5 5 4 4 4 2 1 1 1 1 0 0

4 JhuDP2 6 5 5 3 2 2 2 2 0 0 0 0 0 0 0 0 0

5 SatDP2 5 5 5 4 4 4 4 3 3 1 0 0 0 0 0 0 0

6 SatDP3 4 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0

7 RgrDP3 10 10 4 4 4 4 3 3 2 1 1 1 1 1 1 0 0

8 KhrDP4 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

9 SarDP4 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

10 RgrDP4 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

11 SamD4 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

12 KhrDP5 4 2 2 2 2 2 1 1 1 0 0 0 0 0 0 0 0

13 SarDP5 12 10 6 5 3 3 3 3 3 2 2 2 1 1 1 0 0

70

Figure 1: Regression line showing relation between Ni concentration and number

of bacteria for effluent sample SarDP2

y = -0.9167x + 7.9951R² = 0.9511

0

1

2

3

4

5

6

7

8

0 1 2 3 4 5 6 7 8 9 10

Nu

mb

er o

f b

acte

ria

Ni contration (mM)

71


of bacteria for effluent sample RgrDP3

y = -4.422ln(x) + 9.3433R² = 0.8906

0

2

4

6

8

10

12

0 1 2 3 4 5 6 7 8 9 10

Nu

mb

er o

f b

acte

ria

Ni concentration (mM)

72


of bacteria for effluent sample SarDP5

y = -4.908ln(x) + 10.458R² = 0.9144

0

2

4

6

8

10

12

14

0 2 4 6 8 10

Nu

mb

er o

f b

acte

ria


73

Figure 4: Graph showing the effect of Ni concentration on three different

bacterial isolates

0

2

4

6

8

10

12

14

1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

Nu

mb

er o

f b

acte

ria


Sr2 Rg3 Sr5

74

4.3.3. Determination of MTC of Cobalt (Co)

The MTC of Cobalt (Co) was taken as the highest concentration of Cobalt (Co) that

allowed visible bacterial growth after 48 to 96 hours. The increasing concentration of

Cobalt (Co) i.e. 0.5mM, 1mM, 1.5mM, 02mM, 2.5mM, 03mM, 3.5mM, 04mM, 4.5mM,

05mM, 5.5mM, 06mM, 6.5mM, 07mM, 7.5mM, 08mM, 8.5mM, 09mM, 9.5mM, and

10mM were added in nutrient agar plates to determine the MTCs of isolates in the solid

media and same concentrations of Cobalt (Co) were added in the nutrient broth to

determine the MTCs of isolates in the liquid media.

For this purpose, bacterial isolates which tolerated the highest concentration of

Nickel (Ni) were evaluated for MTC of Cobalt (Co). From the results, it was observed

that bacteria isolated from sample SarDP2 was able to tolerate Co up to 06mM, from

sample RgrDP3 up to 07mM and from sample SarDP5 up to 6.5mM. The MTC values for

Co are given in the Table 20.

4.3.4. Determination of MTC of Chromium (Cr)

The MTC of Chromium (Cr) was considered as the highest concentration of

Chromium (Cr) that allowed visible bacterial growth after 48 to 96 hours. The increasing

concentration of Chromium (Cr) i.e. 0.5mM, 1mM, 1.5mM, 02mM, 2.5mM, 03mM,

3.5mM, 04mM, 4.5mM, 05mM, 5.5mM, 06mM, 6.5mM, 07mM, 7.5mM, 08mM,

8.5mM, 09mM, 9.5mM, and 10mM were added in nutrient agar plates to determine the

MTCs of isolates in the solid media and same concentrations of Chromium (Cr) were

added in the nutrient broth to determine the MTCs of isolates in the liquid media.

For this purpose, bacterial isolates which tolerated the highest concentration of

Nickel (Ni) were evaluated for MTC of Cr. From the results, it was observed that bacteria

isolated from sample SarDP2 was able to tolerate Cr up to 07.5mM, from sample RgrDP3

up to 07mM and from sample SarDP5 up to 07mM. The MTC values for Cr are given in

the Table 21.

75

4.3.5. Determination of Multi Metal Resistance (MMR)

MMR of bacterial isolates was determined by inoculating the isolated metal tolerant

bacteria on nutrient agar incorporated with Nickel (Ni), Cobalt (Co) and Chromium (Cr)

in equal concentration i.e. ((1:1:1) means to obtain 1 mM metal solution 05 ml of each

metal solution having concentration of 01 mM were mixed together). Then this multi

meal solution was added in nutrient agar to determine the MMR of isolates in the solid

media and same concentrations of said metals were added in the nutrient broth to

determine the MMR of isolates in the liquid media.

From the results, it was observed that bacteria isolated from sample SarDP2 was able

to tolerate Nickel (Ni), Cobalt (Co) and Chromium (Cr) in equal concentration up to

5.5mM, from sample RgrDP3 up to 4.5mM and from SarDP5 up to 4.5mM. The results of

MMR are given in Table 22.

76

Table 20: MTC of Cobalt (Co) shown by bacterial population present in collected effluent

samples

Sr.

No.

Sample

Code &

No.

Concentration of Co (mM)

1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

1 SarDP2

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

2 RgrDP3

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

3 SarDP5

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

Table 21: MTC of Chromium (Cr) shown by bacterial population present in collected

effluent samples

Sr.

No.

Sample

Code &

No.

Concentration of Cr (mM)

1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

1 SarDP2

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

2 RgrDP3

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

3 SarDP5

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

Table 22: MMR shown by bacterial population present in different collected wastewater

samples

Sr.

No.

Sample

Code &

No.

Concentration of Ni, Co and Cr (mM) at 1:1:1

1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

1 SarDP2

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

2 RgrDP3

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

3 SarDP5

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

77

4.3.6. Identification of bacterial isolates

4.3.6. a. Gram’s staining

Three bacterial strains which were able to tolerate the highest concentration of

heavy metals isolated from effluent samples RgrDP3, SarDP2and SarDP5 were named as

AMIC1(Abuzar Microbiology 1), AMIC2 (Abuzar Microbiology 2) and AMIC3 (Abuzar

Microbiology 3), respectively. After Gram’s staining of these strains, it was observed that

bacterial strains AMIC2 and AMIC3 were Gram +ve rods (Figure 5) whereas bacterial

strain AMIC1 was Gram -ve rods (Figure 6).

4.3.6. b. Motility test

Motility was checked by preparing slides from the isolated cultures and slides

were then observed at 40X magnification. Out of three bacterial strains, two i.e. AMIC2

and AMIC3 were motile whereas AMIC1 was non motile.

4.3.6. c. Growth on selective and differential culture media

After Gram’s staining of isolated bacterial strains, different types of selective and

differential culture media were used for further confirmation. For this purpose, Gram -ve

bacterial strain AMIC1 isolated from RgrDP3 were grown on different types of selective

and differential media i.e. MecChonkey, Eosin Methylene Blue (EMB), Salmonella

Shigella (SS) agar and Triple Sugar Iron (TSI) agar. After inoculation the media plates

were incubated at 37oC for 24 hours and results were recorded. It was observed that on

MecChonkey agar bacteria produced pink colour colonies confirming the lactose

fermenter (Figure 7). On EMB agar bacteria produced large mucoid colonies without

green metallic sheen (Figure 8), and on TSI agar slant bacteria produced yellow colour on

butt and slant (Figure 9 and 10). Results are summarized in Table 23.

78

Figure 5: Microscopic view of typical Gram positive rods (100x)

Figure 6: Microscopic view of typical Gram negative rods (100x)

79

Figure 7: Growth of bacteria on MacConkey’s agar plate

Figure 8: Growth of bacteria on EMB agar plate

80

Figure 9: Growth of bacteria on TSI agar plate

Figure 10: Growth of bacteria on TSI agar slant

81

4.3.6. d. Biochemical characterization

After identification through Gram’s staining and colony characteristics, these

strains were further processed for identification. Results are summarized in Table 23.

4.3.6. e. Carbohydrate fermentation

Carbohydrate fermentation ability of isolated bacteria was checked by inoculating

broths having different types of sugars in it. Sugars used for test were arabinose, glucose,

inositol, lactose, maltose, mannitol, mannose, sucrose and starch. Results of sugar

fermentation tests are summarized in Table 23.

On the basis of overall results obtained from Gram’s staining, colony characteristics,

biochemical tests and carbohydrate fermentation, it was concluded that the bacterial

strain AMIC1 isolated from effluent sample RgrDP3 was identified as Klebsiella spp.

whereas AMIC2 and AMIC3 isolated from SarDP2 and SarDP5 were identified as

Bacillus spp.

4.4. Optimization of growth conditions

Growth conditions i.e. pH and temperature were optimized for the isolated and

identified HMT bacteria. An optimum growth condition for each strain was determined

without and with metal stress.

It was found that Klebsiella spp. in nutrient broth with and without any metal showed

maximum growth in terms of highest OD values at pH 7.5 and temperature 37oC.

Whereas Bacillus spp. in nutrient broth with and without metal revealed maximum

growth in terms of highest OD values at pH 08 and temperature 37o C. Results of

optimum growth conditions for bacterial strain AMIC1 identified as Klebsiella spp. along

with statistical analysis has been given in Table 24 and Table 25 (a, b, c) and presented in

Figure 11. Results of optimum growth conditions for bacterial strain AMIC2 identified as

Bacillus spp. along with statistical analysis has been given in Table 26 and Table 27 (a, b,

c) and presented in Figure 12. Results of optimum growth conditions for bacterial strain

AMIC3 identified as Bacillus spp. along with statistical analysis has been given in Table

28 and Table 29 (a, b, c) and presented in Figure 13. Analysis of variance (mean square)

for optimum growth conditions of all three bacterial strains is given in Table 30.

82

Table 23: Morphological and biochemical characteristics of isolated HMT bacterial strains

Morphological

Tests

Test Name Isolated HMT bacterial strains

AMIC1 AMIC2 AMIC3

Cell

Morphology Rod Rod Rod

Gram’s reaction -ve +ve +ve

Motility -ve +ve +ve

Flagella -ve +ve +ve

Colonies

characteristics

on selective

and differential

media

Nutrient agar White to cream

colour colonies

White to cream

colour colonies

White to cream

colour colonies

MacConkey’s

agar

Pink color

colonies NP NP

Eosin

Methylene blue

agar

Large mucoid

colonies, no

metallic sheen

NP NP

Salmonella

Shigella agar

Slight growth,

light pink color

colonies

NP NP

TSI agar slant

Yellow colour

on butt and

slant

NP NP

Biochemical

tests

Catalase + + +

Oxidase - - -

Indole - - -

VP + + +

MR + - -

Citrate

Utilization + + +

H2S production - NP NP

Carbohydrate

fermentation

tests

Arabinose + - -

Glucose + + +

Inositol - - -

Lactose + - -

Maltose + + +

Mannitol + - -

Mannose NP - -

Sucrose + + +

Starch NP + +

NP= Not performed

83

Table 24: Optimum growth conditions for bacterial strain AMIC1 identified

as Klebsiella spp.

Without metal

(OD at 600 nm)

Temperature pH

6 6.5 7.0 7.5 8.0

25ºC 0.421 0.460 0.4685 0.516 0.502

30ºC 0.495 0.498 0.523 0.5421 0.532

37ºC 0.893 0.9465 1.4505 1.4985 0.8665

40ºC 0.593 0.653 0.759 0.8532 0.8123

With Ni (01mM)

concentration

(OD at 600 nm)

Temperature pH

6 6.5 7.0 7.5 8.0

25ºC 0.382 0.4025 0.421 0.455 0.4095

30ºC 0.421 0.472 0.514 0.5321 0.5101

37ºC 0.577 0.660 0.763 0.837 0.6235

40ºC 0.472 0.517 0.589 0.667 0.6143

With Co (01mM)

concentration

(OD at 600 nm)

Temperature pH

6 6.5 7.0 7.5 8.0

25ºC 0.156 0.177 0.471 0.425 0.3485

30ºC 0.2 0.232 0.483 0.4341 0.3912

37ºC 0.324 0.597 0.7095 0.8585 0.611

40ºC 0.3192 0.40 0.587 0.7132 0.5932

84

Table 25: Optimum growth conditions for AMIC1 (Klebsiella spp.) without and with

metals

(a) Group x Temperature interaction Means ±SE

Temp Metal Mean

Without with Ni With Co

25 0.474±0.010g 0.414±0.007h 0.316±0.034j 0.401±0.015D

30 0.518±0.007f 0.490±0.011g 0.348±0.030i 0.452±0.016C

37 1.131±0.076a 0.692±0.026c 0.620±0.047d 0.814±0.046A

40 0.734±0.026b 0.572±0.019e 0.523±0.038f 0.609±0.021B

Mean 0.714±0.039A 0.542±0.016B 0.452±0.025C

(b) Group x pH interaction Means ±SE

pH Metal Mean


6 0.601±0.054ef 0.463±0.022k 0.250±0.022m 0.438±0.032E

6.5 0.639±0.058d 0.513±0.029ij 0.352±0.050l 0.501±0.033D

7 0.800±0.118b 0.572±0.038fg 0.563±0.030gh 0.645±0.045B

7.5 0.852±0.119a 0.623±0.044de 0.608±0.056e 0.694±0.049A

8 0.678±0.049c 0.539±0.026hi 0.486±0.035jk 0.568±0.025C

85

(c) Group x Temperature x pH interaction Means ±SE

Temp pH Metal Mean


25 6 0.193±0.002v-y 0.059±0.000z 0.039±0.002z 0.097±0.024K

6.5 0.214±0.013u-y 0.069±0.000z 0.271±0.117s-w 0.185±0.045J

7 0.325±0.006p-u 0.172±0.004w-z 0.131±0.002yz 0.209±0.030J

7.5 0.367±0.010o-s 0.216±0.005u-y 0.275±0.007s-w 0.286±0.022I

8 0.402±0.005m-q 0.417±0.010m-p 0.321±0.004p-u 0.380±0.015GH

30 6 0.246±0.015t-x 0.153±0.004xyz 0.287±0.005r-v 0.229±0.020J

6.5 0.357±0.007p-t 0.325±0.003p-u 0.301±0.005q-v 0.328±0.009HI

7 0.474±0.010l-o 0.397±0.003m-r 0.342±0.013p-t 0.404±0.020G

7.5 0.572±0.004h-l 0.488±0.009j-n 0.377±0.004n-s 0.479±0.029EF

8 0.690±0.006c-g 0.547±0.005i-l 0.494±0.005j-m 0.577±0.029D

37 6 0.342±0.013p-t 0.348±0.006p-t 0.587±0.007g-k 0.426±0.041FG

6.5 0.692±0.055c-g 0.651±0.000d-i 0.611±0.008f-i 0.651±0.020C

7 0.788±0.011bc 0.738±0.006b-e 0.637±0.004e-i 0.721±0.023B

7.5 0.794±0.003bc 0.759±0.006bcd 0.695±0.006c-g 0.749±0.015B

8 1.799±0.052a 0.801±0.001bc 0.723±0.003b-f 1.107±0.174A

40 6 0.301±0.001q-v 0.303±0.004q-v 0.421±0.001m-p 0.342±0.020HI

6.5 0.475±0.012k-o 0.594±0.003g-j 0.487±0.002j-n 0.519±0.019E

7 0.593±0.010g-j 0.614±0.005f-i 0.562±0.004h-l 0.590±0.008D

7.5 0.699±0.006c-g 0.662±0.002d-h 0.597±0.008g-j 0.653±0.015C

8 0.821±0.001b 0.723±0.004b-f 0.600±0.010g-j 0.715±0.032B

86

Figure 11: Graph showing optimum growth conditions for AMIC1

(Klebsiella spp.) Without and with metals

25oC 40oC 37oC 30oC

Temperature & pH

87


as Bacillus spp.

Without metal

(OD at 600 nm)

Temperature pH

6 6.5 7.0 7.5 8.0

25ºC 0.193 0.2135 0.3245 0.3665 0.402

30ºC 0.2456 0.3574 0.4735 0.5723 0.6897

37ºC 0.342 0.6915 0.7875 0.7935 1.799

40ºC 0.301 0.4745 0.5926 0.6992 0.821

With Ni (01mM) concentration

(OD at 600 nm)

Temperature pH

6 6.5 7.0 7.5 8.0

25ºC 0.0594 0.06915 0.1715 0.2155 0.4165

30ºC 0.1534 0.3245 0.3967 0.4875 0.5473

37ºC 0.3476 0.6505 0.7375 0.759 0.8005

40ºC 0.3025 0.594 0.6143 0.662 0.7231

With Co (01mM) concentration

(OD at 600 nm)

Temperature pH

6 6.5 7.0 7.5 8.0

25ºC 0.039 0.041 0.131 0.2745 0.3205

30ºC 0.287 0.3012 0.3421 0.3765 0.4943

37ºC 0.587 0.611 0.6365 0.6945 0.7225

40ºC 0.4213 0.4872 0.5621 0.597 0.60

88

Table 27: Optimum growth conditions for AMIC2 (Bacillus spp.) without and with metals


Temp Metal Mean


25 0.300±0.022g 0.186±0.035h 0.207±0.034h 0.231±0.019D

30 0.468±0.042e 0.382±0.037f 0.360±0.020f 0.403±0.021C

37 0.883±0.131a 0.659±0.044b 0.650±0.014b 0.731±0.048A

40 0.578±0.048c 0.579±0.039c 0.534±0.019d 0.563±0.021B

Mean 0.557±0.045A 0.452±0.030B 0.438±0.025B


pH Metal Mean


6 0.270±0.017i 0.216±0.035j 0.334±0.060h 0.273±0.025E

6.5 0.434±0.054fg 0.410±0.070g 0.418±0.049g 0.420±0.033D

7 0.545±0.051c 0.480±0.065ef 0.418±0.060g 0.481±0.034C

7.5 0.608±0.048b 0.531±0.062cd 0.486±0.051de 0.542±0.032B

8 0.928±0.159a 0.622±0.045b 0.534±0.045c 0.695±0.062A

Means sharing similar letter in a row or in a column are statistically non-significant (P>0.05).

Small letters represent comparison among interaction means and capital letters are used for

overall mean.

89


Temp pH Metal Mean


25 6 0.421±0.005v-z 0.382±0.011z 0.156±0.004z 0.320±0.041O

6.5 0.460±0.016s-y 0.403±0.009w-z 0.177±0.011z 0.347±0.044NO

7 0.469±0.002r-x 0.421±0.008v-z 0.471±0.013q-x 0.454±0.009JK

7.5 0.516±0.008o-s 0.455±0.009s-y 0.425±0.003u-z 0.465±0.014J

8 0.502±0.009q-t 0.410±0.006w-z 0.349±0.007z 0.420±0.023KL

30 6 0.495±0.008q-u 0.421±0.001v-z 0.200±0.014z 0.372±0.045MN

6.5 0.498±0.020q-t 0.472±0.008q-w 0.232±0.014z 0.401±0.043LM

7 0.523±0.013n-s 0.514±0.005p-s 0.483±0.014q-v 0.507±0.008HI

7.5 0.542±0.001l-q 0.532±0.016m-r 0.434±0.002t-z 0.503±0.018HI

8 0.532±0.013m-r 0.510±0.007p-s 0.391±0.011yz 0.478±0.023IJ

37 6 0.893±0.018bc 0.577±0.010k-p 0.324±0.009z 0.598±0.083G

6.5 0.947±0.006b 0.660±0.014ghi 0.597±0.006h-m 0.735±0.054CD

7 1.451±0.030a 0.763±0.014ef 0.710±0.011fg 0.974±0.120B

7.5 1.499±0.011a 0.837±0.025cd 0.859±0.014cd 1.065±0.109A

8 0.867±0.018cd 0.624±0.008h-k 0.611±0.005h-l 0.700±0.042DE

40 6 0.593±0.007i-n 0.472±0.010q-w 0.319±0.004z 0.461±0.040J

6.5 0.653±0.016g-j 0.517±0.008o-s 0.400±0.014xyz 0.523±0.037H

7 0.759±0.016ef 0.589±0.012i-n 0.587±0.018j-o 0.645±0.030F

7.5 0.853±0.012cd 0.667±0.022gh 0.713±0.013fg 0.744±0.029C

8 0.812±0.007de 0.614±0.009h-k 0.593±0.005i-n 0.673±0.035EF

90



25oC 30oC 37oC 40oC

Temperature & pH

91


as Bacillus spp.

Without metal

(OD at 600 nm)

Temperature pH

6 6.5 7.0 7.5 8.0

25ºC 0.1532 0.1965 0.2905 0.317 0.3995

30ºC 0.213 0.373 0.4521 0.4987 0.5872

37ºC 0.4123 0.6425 0.7155 0.754 0.7955

40ºC 0.38754 0.4532 0.4987 0.5745 0.6723

With Ni (01mM) concentration

(OD at 600 nm)

Temperature pH

6 6.5 7.0 7.5 8.0

25ºC 0.0450 0.0505 0.1405 0.172 0.2845

30ºC 0.1983 0.2456 0.321 0.3945 0.4765

37ºC 0.3874 0.5785 0.668 0.697 0.7115

40ºC 0.3154 0.4543 0.5103 0.5532 0.6237

With Co (01mM) concentration

(OD at 600 nm)

Temperature pH

6 6.5 7.0 7.5 8.0

25ºC 0.038 0.062 0.138 0.287 0.325

30ºC 0.1763 0.2453 0.3031 0.4213 0.5023

37ºC 0.300 0.5685 0.6175 0.6915 0.722

40ºC 0.2876 0.3765 0.4123 0.5253 0.5934

92

Table 29: Optimum growth conditions for AMIC3 (Bacillus spp.) without and with metals


Temp Metal Mean


25 0.271±0.024h 0.139±0.024j 0.170±0.031i 0.193±0.017D

30 0.425±0.035f 0.327±0.027g 0.330±0.032g 0.361±0.019C

37 0.664±0.036a 0.608±0.032b 0.580±0.040c 0.617±0.021A

40 0.517±0.026d 0.491±0.028e 0.439±0.029f 0.483±0.016B

Mean 0.469±0.024A 0.391±0.027B 0.380±0.025C


pH Metal Mean


6 0.292±0.034i 0.237±0.039j 0.200±0.032k 0.243±0.021E

6.5 0.416±0.048e 0.332±0.061g 0.313±0.056h 0.354±0.032D

7 0.489±0.046c 0.410±0.060e 0.368±0.053f 0.422±0.031C

7.5 0.536±0.048b 0.454±0.059d 0.481±0.045c 0.491±0.029B

8 0.614±0.043a 0.524±0.049b 0.536±0.044b 0.558±0.026A

Means sharing similar letter in a row or in a column are statistically non-significant (P>0.05).

Small letters represent comparison among interaction means and capital letters are used for

overall mean.

93


Temp pH Metal Mean


25 6 0.153±0.015wx 0.045±0.002y 0.038±0.002y 0.079±0.019P

6.5 0.197±0.005vw 0.051±0.001y 0.062±0.001y 0.103±0.023O

7 0.291±0.007s 0.141±0.001x 0.138±0.002x 0.190±0.025N

7.5 0.317±0.004s 0.172±0.015vwx 0.287±0.003st 0.259±0.023M

8 0.400±0.004qr 0.285±0.007st 0.325±0.006s 0.336±0.017K

30 6 0.213±0.004uv 0.198±0.006v 0.176±0.005vwx 0.196±0.006N

6.5 0.373±0.005r 0.246±0.002tu 0.245±0.005tu 0.288±0.021L

7 0.452±0.006op 0.321±0.003s 0.303±0.005s 0.359±0.024J

7.5 0.499±0.040mn 0.395±0.003qr 0.421±0.003pq 0.438±0.019I

8 0.587±0.002hij 0.477±0.005no 0.502±0.003mn 0.522±0.017G

37 6 0.412±0.011pqr 0.387±0.007qr 0.300±0.006s 0.367±0.018J

6.5 0.643±0.002fg 0.579±0.010ij 0.569±0.005jk 0.597±0.012E

7 0.716±0.006bcd 0.668±0.006ef 0.618±0.002ghi 0.667±0.014C

7.5 0.754±0.002ab 0.697±0.006cde 0.692±0.001cde 0.714±0.010B

8 0.796±0.004a 0.712±0.004b-e 0.722±0.005bc 0.743±0.013A

40 6 0.388±0.005qr 0.315±0.003s 0.288±0.006st 0.330±0.015K

6.5 0.453±0.003op 0.454±0.004op 0.377±0.004r 0.428±0.013I

7 0.499±0.006mn 0.510±0.007lmn 0.412±0.004pqr 0.474±0.016H

7.5 0.575±0.003ij 0.553±0.002jkl 0.525±0.007klm 0.551±0.007F

8 0.672±0.002def 0.623±0.007gh 0.593±0.005hij 0.630±0.012D

94



25oC 40oC 37oC 30oC

Temperature & pH

95

Table 30: Analysis of variance (mean square) table for optimum growth conditions of three

bacterial strains

Source of

variation

Degrees

of

freedom

Mean squares

Optimum growth

conditions for

AMIC1

(Klebsiella spp.)

Optimum growth

conditions For

AMIC2

(Bacillus spp.)

Optimum growth

conditions for

AMIC3

(Bacillus spp.)

Group 2 1.06809** 0.25497** 0.14262**

Temperature 3 1.55645** 2.06381** 1.46488**

pH 4 0.38945** 0.86539** 0.53545**

Group*Temp 6 0.16102** 0.03955** 0.00911**

Group*pH 8 0.02947** 0.09878** 0.00345**

Temp*pH 12 0.04976** 0.04325** 0.01205**

Group*Temp*pH 24 0.01690** 0.05620** 0.00139**

Error 120 0.00044 0.00110 0.00017

Total 179


96

4.5. Effect of Nickel (Ni) on bacterial growth

To observe the effect of Ni on all three isolated HMT bacterial strains i.e. AMIC1

(Klebsiella spp.), AMIC2 (Bacillus spp.) and AMIC3 (Bacillus spp.), bacteria were

grown without and with Ni and the growth curve patterns were studied. Results showed

that Ni ions significantly reduced the rate of growth of all bacterial strains as compared to

control group. Results are summarized in Tables 31, 33 & 35 and Figures 14, 17 & 20.

4.6. Effect of Cobalt (Co) on bacterial growth

To examine the effect of Co on all three isolated HMT bacterial strains i.e.

AMIC1 (Klebsiella spp.), AMIC2 (Bacillus spp.) and AMIC3 (Bacillus spp.), bacteria

were cultured without and with Co and the growth curve experiment was performed.

Results exhibited that Co ions significantly reduced the rate of growth of all bacterial

strains when compared with control. Results are summarized in Tables 32, 34 & 36 and

Figures 15, 18 & 21. The comparative effect of Ni vs Co on growth rates of all three

bacterial strains has been shown in Figures 16, 19 & 22.

97

Table 31: Effect of Ni on the growth rate of AMIC1 (Klebsiella spp.)

Growth with

Ni

OD

at

600

nm

Reading intervals

0hour 04hours 08hours 12hours 16hours 20hours 24hours 28hours

0.004 0.008 0.19 0.3 0.42 0.49 0.6 0.68

Growth

without Ni

Reading intervals


0.0045 0.009 0.23 0.34 0.45 0.56 0.637 0.71

Figure 14: Graph showing effect of Ni on the growth rate of AMIC1

(Klebsiella spp.)

Growth with Ni

Growth without Ni

98

Table 32: Effect of Co on the growth rate of AMIC1 (Klebsiella spp.)

Growth with

Co

OD

at

600

nm

Reading intervals


0.004 0.007 0.18 0.29 0.34 0.38 0.406 0.457

Growth

without Co

Reading intervals


0.0045 0.009 0.23 0.34 0.45 0.56 0.637 0.71

Figure 15: Graph showing effect of Co on the growth rate of AMIC1

(Klebsiella spp.)

Growth with Co

Growth without Co

99

Figure 16: Graph showing effect of Ni vs. Co on the growth rate

of AMIC1 (Klebsiella spp.)

Growth with Ni

Growth with Co

100

Table 33: Effect of Ni on the growth rate of AMIC2 (Bacillus spp.)

Growth

with Ni

OD

at

600

nm

Reading intervals


0.0042 0.006 0.10 0.21 0.34 0.443 0.521 0.534

Growth

without Ni

Reading intervals


0.0045 0.008 0.12 0.29 0.41 0.57 0.621 0.69

Figure 17: Graph showing effect of Ni on the growth rate of AMIC2 (Bacillus spp.)

Growth with Ni

Growth without Ni

101

Table 34: Effect of Co on the growth rate of AMIC2 (Bacillus spp.)

Growth

with Co

OD

at

600

nm

Reading intervals


0.004 0.0075 0.15 0.2 0.28 0.34 0.37 0.40

Growth

without Co

Reading intervals


0.0045 0.008 0.12 0.29 0.41 0.57 0.621 0.69

Figure 18: Graph showing effect of Co on the growth rate of AMIC2 (Bacillus spp.)

Growth with Co

Growth without Co

102

Figure 19: Graph showing effect of Ni vs. Co on the growth AMIC2 (Bacillus spp.)

Growth with Co

Growth with Ni

103

Table 35: Effect of Ni on the growth rate of AMIC3 (Bacillus spp.)

Growth

with Ni

OD

at

600

nm

Reading intervals


0.004 0.009 0.123 0.257 0.358 0.489 0.549 0.61

Growth

without Ni

Reading intervals


0.0045 0.1 0.129 0.29 0.387 0.538 0.652 0.71

Figure 20: Graph showing effect of Ni on the growth rate of AMIC3 (Bacillus spp.)

Growth with Ni

Growth without Ni

104

Table 36: Effect of Co on the growth rate of AMIC3 (Bacillus spp.)

Growth

with Co

OD

at

600

nm

Reading intervals


0.004 0.008 0.11 0.235 0.337 0.39 0.455 0.523

Growth

without Co

Reading intervals


0.0045 0.1 0.129 0.29 0.387 0.538 0.652 0.71

Figure 21: Graph showing effect of Co on the growth rate of AMIC3 (Bacillus spp.)

Growth with Co Growth without Co

105

Figure 22: Graph showing effect of Ni vs. Co on the growth rate of AMIC3 (Bacillus spp.)

Growth with Ni Growth with Co

106

4.7. Antibiotic susceptibility testing

Antibiotic susceptibility of all isolated HMT bacterial strains i.e. AMIC1

(Klebsiella spp.), AMIC2 (Bacillus spp.) and AMIC3 (Bacillus spp.) was determined by

disc diffusion method against commonly used antibiotics. Results revealed that strain

AMIC1 (Klebsiella spp.) was found resistant to AMC and AMP whereas sensitive to

remaining antibiotics used (Table 37). AMIC2 (Bacillus spp.) was found resistant to

ATM and MET whereas it was sensitive to remaining antibiotics used for the test (Table

38).Similarly, AMIC3 (Bacillus spp.) was resistant to CAZ, FOX and MET whereas it

was sensitive to remaining antibiotics (Table 39).

107

Table 37: Antibiotic susceptibility pattern of AMIC1 (Klebsiella spp.)

Sr.

No. Antibiotics Abbreviation

Concentration

(µg)

Zone

diameter

(mm)

Interpretation

1. Amoxicillin/

Clavulanic acid AMC 30 0 R*

2. Ampicillin AMP 10 0 R

3. Aztreonam ATM 30 20 S*

4. Ceftriaxone CRO 30 20 S

5. Cefepime FEP 30 09 I*

6. Imipenem IPM 10 25 S

7. Meropenem MEM 10 08 I

8. Nalidixic acid NA 30 20 S

9. Trimethoprim-

sulphamethoxazole SXT 25 20 S

R*: Resistant, S*: Sensitive, I*: Intermediate

108

Table 38: Antibiotic susceptibility pattern of AMIC2 (Bacillus spp.)

Sr.


Concentration

(µg)

Zone

diameter

(mm)

Interpretation

1. Aztreonam ATM 30 0 R*

2. Ciprofloxacin CIP 05 30 S*

3. Gentamicin CN 10 25 S

4. Imipenem IPM 10 25 S

5. Linezolid LZD 30 30 S

6. Meropenem MEM 10 12 I*

7. Metronidazole MET 05 0 R

8. Ofloxacin OFX 05 30 S

9. Cefoxitin FOX 05 14 I

10. Piperacillin-

tazobactam TZP 110 25 S

11. Vancomycin VA 30 11 I


109

Table 39: Antibiotic susceptibility pattern of AMIC3 (Bacillus spp.)

Sr.


Concentration

(µg)

Zone

Radius

(mm)

Interpretation

1. Amikacin AK 30 25 S*

2. Ceftazidime CAZ 30 0 R*

3. Ciprofloxacin CIP 05 25 S

4. Gentamicin CN 10 22 S

5. Ertapenem ETP 10 16 I*

6. Cefoxitin FOX 30 0 R

7. Metronidazole MET 05 0 R

8. Ofloxacin OFX 05 25 S

9. Piperacillin-

tazobactam TZP 110 25 S

10. Vancomycin VA 30 14 I


110

4.8. Molecular characterization

Molecular characterization of the three indigenous HMT bacterial isolates named as

AMIC1, AMIC2 and AMIC3 was done and the results showed that bacterial strain

AMIC1 was confirmed as Klebsiella spp. showing 99.79% similarity with Klebsiella

variicola DSM 15968T(AJ783916). AMIC2 confirmed as Bacillus spp. showing 99.86%

similarity with Bacillus cereus ATCC 14579T (AE016877). Similarly, AMIC3 confirmed

as Bacillus spp. showing 99.79% similarity with Bacillus cereus ATCC 14579T

(AE016877). Percentage of maximum similarity and GenBank accession number of

isolated HMT bacteria are given in Table 40. The constructed phylogenetic tree for

Klebsiella variicola constructed by maximum likelihood method is shown in Figure 23

whereas for Bacillus cereus is presented in Figure 24.

111

Table 40: Percentage of maximum similarity and GenBank accession number of HMT

bacteria

Sr. No. Strain name Identified as with

accession No. Homology; %

1 AMIC1 Klebsiella spp.

(LT838344)

Klebsiella variicola DSM

15968T(AJ783916); 99.79%

2 AMIC2 Bacillus spp.

(LT838345)

Bacillus cereus ATCC

14579T(AE016877); 99.86%

3 AMIC3 Bacillus spp.

(LT838346)

Bacillus cereus ATCC

14579T(AE016877); 99.79%

112

Figure 23: 16S rRNA sequence-based phylogenetic tree of Klebsiella variicola isolated from

textile effluents constructed by Maximum Likelihood method

113

Figure 24: 16S rRNA sequence-based phylogenetic tree of Bacillus cereus isolated from

textile effluent constructed by Maximum Likelihood method

114


strains

4.9.1. Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-

OES)

Biosorption potential of isolated bacterial strains i.e. AMIC1 (Klebsiella variicola),

AMIC2 (Bacillus cerus) and AMIC3 (Bacillus cerus) was determined against two metals

i.e. Nickel (Ni) and Cobalt (Co) through Inductively Coupled Plasma-Optical

Emission Spectroscopy (ICP-OES). Percentage reduction in metal concentrations after 24

and 48hours were determined. The results showed that AMIC1 (K. variicola) reduced

Nickel (Ni) 49 and 50% whereas reduction of Cobalt (Co) was 68.6 and 71% after 24 and

48hours respectively (Table 41). AMIC2 (B. cerus) reduced Nickel (Ni) 48.4 and 49%

whereas reduction of Cobalt (Co) was 70.6 and 73.6% after 24 and 48hours, respectively

(Table 42). Similarly, AMIC3 (B. cerus) reduced Nickel (Ni) 50.6 and 51.8% whereas

reduction of Cobalt (Co) was 71.8 and 73.2 after 24 and 48hours respectively (Table 43).

Comparison of percentage reduction in Nickel (Ni) and Cobalt (Co) by AMIC1 (K.

variicola), AMIC2 (B. cerus) and AMIC3 (B. cerus) and summarized in Table 44 and

Figure 25.

115

Table 41: Percentage reduction of Nickel (Ni) and Cobalt (Co) by AMIC1 (Klebsiella

variicola) through ICP-OES

Bacterial

strain Metal

24 hours (S1) 48 hours (S2) Z- value

Initial Final % age Initial Final % age S1 vs. S2

AMIC1

(Klebsiella

variicola)

Ni 50 25 49 50 25.5 50 0.20NS

CO 50 15.7 68.6 50 14.5 71 0.22NS

Z-test Ni vs.

CO 2.07* 2.09*

Table 42: Percentage reduction of Nickel (Ni) and Cobalt (Co) by AMIC2 (Bacillus cereus)

through ICP-OES

Bacterial

strain Metal

24 hours (S1) 48 hours (S2) Z- value


AMIC2

(B. cerus)

Ni

50 25. 8 48.4 50 25.5 49 0.20NS

CO

50 14.7 70.6 50 13.2 73.6 0.45NS

Z-value Ni vs. CO 2.29* 2.77**


116

Table 43: Percentage reduction of Nickel (Ni) and Cobalt (Co) by AMIC3 (Bacillus cereus)

through ICP-OES

Bacterial

strain Metal

24 hours (S1) 48 hours (S2) Bacterial

strain


AMIC3

(B. cerus)

Ni

50 24.7 50.6 50 24.1 51.8 0.20NS

CO

50 14.1 71.8 50 13.4 73.2 0.23NS

Z- value Ni vs. CO 2.31* 2.34*

Table 44: Comparison of percentage reduction in Nickel (Ni) and Cobalt (Co) by AMIC1

(Klebsiella variicola)), AMIC2 (Bacillus cerus) and AMIC3 (Bacillus cerus)

Bacterial

strain Metal

S1 S2 Z- value

I F % age I F % age S1 vs. S2

AMIC1

(K. variicola)

Ni 50 25 49 50 25.5 50 0.20NS

CO 50 15.7 68.6 50 14.5 71 0.22NS

Z-test Ni vs.

CO 2.07*

2.09*

Bacterial

strain Metal

S1 S2 Z-value


AMIC2

(B. cerus)

Ni 50 25. 8 48.4 50 25.5 49 0.20NS

CO 50 14.7 70.6 50 13.2 73.6 0.45NS

Z-value Ni vs.

CO 2.29*

2.77**

Bacterial

strain Metal

S1 S2 Z-value


AMIC3

(B. cerus)

Ni 50 24.7 50.6 50 24.1 51.8 0.20NS

CO 50 14.1 71.8 50 13.4 73.2 0.23NS

Z-value Ni vs.

CO 2.31*

2.34*

117

Figure 25: Graph showing comparison of percentage reduction in Nickel (Ni) and

Cobalt (Co) by AMIC1 (Klebsiella variicola), AMIC2 (Bacillus cerus) and AMIC3

(Bacillus cerus)

AMIC1 AMIC2 AMIC3

118

4.10. FT-IR

To confirm the difference between functional groups in relation to biosorption of

metal (Ni and Co), FT-IR analysis was carried out using metal-loaded (Ni or Co) bacteria

in comparison to control. Metal loaded biomass were washed and freeze-dried after

biosorption of metal ions under the same conditions used in the preparation of control.

The control sample demonstrated the presence of a number of absorption peaks and

reflected the complex nature of the biomass.

A change of absorption bands were observed, when we compared the FT-IR

spectra of control and metal loaded biomass. Figure 26 reflects the changes in spectra for

control and Figure 27 and Figure 28 shows the changes in the spectrum of the biomass

after sorption of Ni and Co respectively by AMIC1 (K. variicola). A change in peak at

3500–3200 cm-1 region in spectrum of Ni and Co was observed and was considered as

the binding of Ni and Co with amino and hydroxyl group. Similarly a change in peak at

1500- 1750 cm-1 region in spectrum of Ni and Co was observed which indicated the

binding of Ni and Co with carboxyl group.

Similarly a change of absorption bands were observed, when we compared the

FT-IR spectra of control and metal loaded biomass. Figure 29 reflects the changes in

spectra for control and Figure 30 and Figure 31 shows the changes in the spectrum of the

biomass after sorption of Ni and Co respectively by AMIC2 (B. cerus). While Figure 32

shows the changes in spectra for control and Figure 33 and Figure 34 shows the changes

in the spectrum of the biomass after sorption of Ni and Co respectively by AMIC3 (B.

cerus). A change in peak at 3500–3200 cm-1 regions in spectrum of Ni and Co was

observed and was considered as the binding of Ni and Co with amino and hydroxyl

group. Similarly a change in peak at 2900-3000 cm−1 regions in spectrum of Ni and Co it

could was considered as the binding of Ni and Co with –CH2 groups combined with that

of the CH3 groups. A similar change in peak at 1300–1067 cm−1 regions in spectrum of

Ni and Co was considered as the binding of Ni and Co with carboxyl and phosphate

groups.

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Figure 26: FT-IR spectra of AMIC1 (Klebsiella variicola) biomass without metal loading

Figure 27: FT-IR spectra of AMIC1 (Klebsiella variicola) biomass loaded with Ni

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Figure 28: FT-IR spectra of AMIC1 (Klebsiella variicola) biomass loaded with Co

Figure 29: FT-IR spectra of AMIC2 (Bacillus cereus) biomass without metal loading

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Figure 30: FT-IR spectra of AMIC2 (Bacillus cereus) biomass loaded with Ni

Figure 31: FT-IR spectra of AMIC2 (Bacillus cereus) biomass loaded With Co

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Figure 32: FT-IR spectra of AMIC3 (Bacillus cereus) biomass without metal loading

Figure 33: FT-IR spectra of AMIC3 (Bacillus cereus) biomass loaded with Ni

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Figure 34: FT-IR spectra of AMIC3 (Bacillus cereus) biomass loaded with Co

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4.12. Scanning Electron Microscopy (SEM)

SEM was performed to check any morphological changes occurred in the outer

membrane of bacteria in response to heavy metals (Ni and Co). The normal electron

micrographs of Klebsiella variicola and Bacillus cereus without metal stress (control)

were compared with metal stress to see the surface changes in bacteria due to Ni and Co.

The results revealed that both heavy metals showed significant changes in outer

membrane of bacteria in terms of roughness of outer membrane, deterioration of normal

intact membrane structure, indentation, formation of pores, vaculation etc. as a result of

their adsorption with bacterial cell wall and subsequent absorption in to the cell. Among

two metals, Ni had more severe effect on bacterial outer membrane than Co. Likewise,

when two categories of bacteria were compared; it was evident that both metals had more

pronounced effects on the outer membrane of G +ve bacteria (Bacillus cereus) as

compared to G -ve bacteria (Klebsiella variicola). The results are shown in electron

micrographs in Figure 35 to Plate 40.

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Figure 35: Electron micrograph of Klebsiella variicola grown without metal stress

(control)

Figure 36: Electron micrograph showing the effect of Ni on Klebsiella variicola

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Figure 37: Electron micrograph showing the effect of Co on Klebsiella variicola

Figure 38: Electron micrograph of Bacillus cereus grown without metal stress

(control)

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Figure 39: Electron micrograph showing the effect of Ni on Bacillus cereus

Figure 40: Electron micrograph showing the effect of Co on Bacillus cereus

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DISCUSSION

The present research work was completed successfully and highlighted the

significance of indigenous HMT bacteria and evaluation of their biosorption potential

against heavy metals. There is an increasing interest and obviously the need of the time in

the country for the isolation and identification of some indigenous HMT bacteria and

their possible use for the bioremediation of polluted/contaminated areas with heavy

metals. As a matter of interest and need of time, the present study was designed for

isolation, molecular characterization and evaluation of biosorptive potential of HMT

bacteria from textile effluents of Faisalabad, Pakistan.

The study was designed with two core objectives; 1st was the isolation and

molecular characterization of indigenous HMT bacteria from textile effluents of

Faisalabad, Pakistan in order to search for some novel strains and 2nd was to explore the

biosorptive potential of these strains against frequently found heavy metals in such

effluents. Isolation of HMT bacteria was done as previously described by Lucious et al.

(2013) and Samanta et al. (2012). MTC of heavy metals by indigenous strains was

determined as previously described by Hassen et al, (1998); Alboghobeish et al, (2014)

and Vashishth & Khanna (2015). Identification of bacteria was done by following the

protocols mentioned in Bergey’s Manual of Determinative Bacteriology. Optimum

growth conditions and effect of heavy metals on the growth of bacteria was determined as

previously described by Shakoori et al, (2010). The antibiotic susceptibility of the

isolated bacteria against different antibiotics was determined as previously described by

Udobi et al. (2013). Molecular characterization of the isolates was done as previously

described by Abbas et al. (2014) and Zaheer et al., (2016). Finally, biosorption potential

of indigenous strains was determined as previously described by Shakoori et al, (2010);

Nanda et al, (2011); Alboghobeish et al, (2014) and Ramyakrishna& Sudhamani (2016).

For isolation of HMT bacteria, effluents samples were collected from industrial

drains present in and around of Faisalabad, Pakistan as previously described by Baby et

al, (2014) and Srinath et al, (2001). After collection, the samples were subjected to

Atomic Absorption Spectrophotometer (AAS) for heavy metal analyses in order to find

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out the most frequent metals in these samples. It was observed that Nickel (Ni) was the

most frequent metal followed by Cobalt (Co) in all samples thus both were selected for

further studies. The overall values of different physico-chemical parameters in effluent

samples collected from all locations were on the higher side when compared to the limits

of NEQS, which provide evidence that all the collected samples were highly polluted.

Statistically there was non- significant difference (P>0.05) among physico-chemical

parameters of samples from different locations. These results of present study were in

agreement with the work of Ali et al. (2006) who performed similar work by collecting

the textile effluents and reported all physico-chemical parameters above permissible

limits of Environmental Protection Agency (EPA) and concluded that all samples were

highly polluted and needed treatment.

MTC of Ni and Co above which the growth of bacteria was completely inhibited

was determined. Bacterial count was carried out from the collected samples. It was

observed that the samples collected from the industrial drain located at Khurrianwala,

Faisalabad had an overall bacterial population ranged from 3.4×105 to 8.9×105, whereas,

Nickel tolerant bacteria ranged from 0 to 45×10-5 and Cobalt tolerant bacteria were from

0 to 40×10-5. The samples collected from the industrial drain located at small industrial

estate and main Sargodha road Faisalabad had bacterial load ranged from 2.7 to 8×105

with Nickel tolerant bacteria from 0 to 26×10-5 and Cobalt tolerant bacteria from 12 to

38×10-5. Similarly, the samples collected from the industrial drain located at Jhumrah

road, Abdullahpur, Faisalabad had bacterial population ranged from 1.9 to 78×105 with

Nickel tolerant bacteria from 0 to 65×10-5 and Cobalt tolerant bacteria from 0to 70×10-5.

Whereas, the samples collected from the drain located at Satiana road, Faisalabad had

bacterial load ranged from 7.2 to 109×105 with Nickel tolerant bacteria ranged from 0 to

30×10-5 and Cobalt tolerant bacteria from 0to 25×10-5. The samples collected from the

drain located at Raja Ghulam Rasool Nagar, Faisalabad had bacterial population ranged

from 9.2 to 101×105 with Nickel tolerant bacteria from 0 to 50×10-5 and Cobalt tolerant

bacteria from 0to 40×10-5. Similarly, the samples collected from the drain located at

Samundri road Faisalabad had bacterial load ranged from 5.3 to 52×105 with Nickel

tolerant bacteria from 0 to 28×10-5 and Cobalt tolerant bacteria from 0to 32×10-5.

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Statistically significant difference (P<0.05) was observed among bacterial count of

samples KhrD, SarD and RgrD.

Following initial screening, 13 out of total 30 effluent samples exhibited bacterial

growth on Nutrient agar incorporated with 0.5mM of Ni. After determination of their

MTC, it was observed that 03 samples i.e. SarDP2, RgrDP3 and SarDP5 found have some

novel bacterial strains which were able to grow on Nutrient agar incorporated with 08mM

of Ni. Then pure cultures of bacteria from these samples were obtained through streak

plate method and single colonies were cultured for further studies. Statistical analyses

revealed a highly negative correlation coefficient (r) between the number of isolates and

Ni ion concentration for these samples; SarDP2 (r=-0.916x), RgrDP3 (r=-4.42x) &

SarDP5 (r=-4.90x).

These three samples were then screened for tolerance to Co & Cr and MMR

against Ni, Co and Cr. It was evident from the results that bacteria from sample SarDP2

were able to tolerate Co up to 06mM & Cr up to 7.5mM separately and also exhibited

MMR to Ni, Co and Cr (1:1:1) up to 5.5mM. Isolate from RgrDP3 was able to tolerate Co

up to 07mM, Cr up to 07mM and showed MMR to Ni, Co and Cr (1:1:1) up to 4.5mM.

Similarly, isolate from SarDP5 was able to tolerate Co up to 6.5mM, Cr up to 07mM and

exhibited MMR to Ni, Co and Cr (1:1:1) up to 4.5mM.

These three bacterial strains which were able to tolerate the maximum

concentration of heavy metals isolated from effluent samples RgrDP3, SarDP2and SarDP5

were named as AMIC1, AMIC2 and AMIC3, respectively. After Gram’s staining of these

strains, it was observed that bacterial strains AMIC2 and AMIC3 were Gram +ve rods

whereas bacterial strain AMIC1 was Gram -ve rods. After examination of colony

characteristics on selective & differential media, biochemical and sugar fermentation

tests results, it was confirmed that bacterial strain AMIC1 isolated from effluent sample

RgrDP3 was Klebsiella spp. whereas AMIC2 and AMIC3 isolated from SarDP2 and

SarDP5 were Bacillus spp.

The results of present study are in agreement with the work of El Hameed et al.

(2015) who performed the similar work by isolating the fungi from phosphatic sources

and screened the isolates for heavy metal (Co, Cu, Cr, Pb, U and Zn) tolerance. They

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found that eighteen out of twenty six isolates were able to tolerate the different

concentrations of different heavy metals tested. Quantitative analyses of isolates showed

that isolate number decreased as the concentration of different heavy metal increased in

the growth media. Statistical data also provided a negative correlation between isolates

and metal concentrations. Similar study was performed by Selvi et al. (2012) for the

isolation and characterization of HMT bacteria from tannery effluents. Initially they

obtained fifty isolates out of which five isolates showed maximum tolerance capacity to

different metals were selected and identified as Escherichia coli, Bacillus spp.,

Pseudomonas spp., Flavobacterium spp. and Alcaligenes spp. MIC of the isolates was

determined for different heavy metals (Cu, Cr, Hg, Pb and Zn) and it was found that all

isolates exhibited tolerance to heavy metals in the respective order; Pb> Cu> Zn> Cr>

Hg.

Similarly, Raja et al. (2006) performed a study for the isolation and

characterization of metal tolerant Pseudomonas aeruginosa strain. Isolation,

identification and quantification of biomass of HMT bacteria were done by conventional

microbiological methods and spectrophotometer. Minimum inhibitory concentration

(MIC) of the heavy metals was determined by plate dilution method using the different

concentration of heavy metal salts. 16S rDNA sequencing of the isolate revealed that it

was closely related to Pseudomonas aeruginosa (94% similarity). Isolate showed

biosorption potential against all four tested metals (Cd, Cr, Pb and Ni) and the

biosorption pattern was found as: Cr (30%) < Cd (50%) < Pb (65%) < Ni (93%).

The results of the present study are also in agreement with the work of

Alboghobeish et al. (2014) who isolated Nickel resistant bacteria (NiRB) from

wastewater polluted with different industrial sources. For this purpose, they isolated eight

Nickel resistant bacteria out of which three strains were selected on the basis of their

maximum tolerable concentration. From the results it was observed that bacterial strain

ATHA3 was able to tolerate 08mM Ni+2, ATHA6 was able to tolerate 16mM Ni+2 and

ATHA7 was able to tolerate 24mM Ni+2. 16s rDNA gene sequencing identified ATHA3

as Cupriavidus spp., ATHA6 Klebsiella oxytoca and ATHA7 as Methylobacterium spp.

Similar study was performed by Ahirwar et al. (2016). For this purpose, they collected

soil samples from industrial contaminated soil areas near by different industries. Isolation

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and identification of bacteria was done by conventional microbiological methods. The

isolates were screened for metal resistance and antibiotic resistance. The results showed

that bacterial strains identified as Pseudomonas vulgaris, Pseudomonas fluorescence and

Bacillus cereus were found to be the most efficient strains in terms of metal resistance.

Growth conditions i.e. pH and temperature were optimized for the isolated and

identified HMT bacteria. An optimum growth condition for each strain was determined

without and with metal stress. It was found that AMIC1 (Klebsiella spp.) in nutrient broth

with and without any metal showed maximum growth in terms of highest OD values at

pH 7.5 and temperature 37oC. Whereas AMIC2 and AMIC3 (Bacillus spp.) in nutrient

broth with and without metal revealed maximum growth in terms of highest OD values at

pH 08 and temperature 37oC. Effect of heavy metals (Ni or Co) was observed on all three

strains i.e. AMIC1 (Klebsiella spp.), AMIC2 and AMIC3 (Bacillus spp.). Bacteria were

grown without and with metal (Ni or Co) and the growth curve patterns were studied. It

was evident from the results that metal ions (Ni or Co) significantly (P<0.05) reduced the

rate of growth of all bacterial strains as compared to control group.

Similar study was performed by Shakoori et al. (2010) for the isolation and

characterization of Cr6+ reducing bacteria. For this purpose, they isolated and

characterized three bacterial strains including Bacillus pumilus, Alcaligenes faecalis and

Staphylococcus spp. Optimum growth conditions and growth curve pattern of the isolates

was determined by growing bacteria without and with metal stress. It was evident from

the results that B. pumilus and Staphylococcus spp. showed optimum growth at

temperature 37oC and pH 8 whereas A. faecalis exhibited optimum growth at temperature

37oC and pH 7.

Studies were conducted to check the antibiotic susceptibility of all isolated HMT

bacterial strains i.e. AMIC1 (Klebsiella spp.), AMIC2 and AMIC3 (Bacillus spp.). It was

evident from the results that strain AMIC1 (Klebsiella spp.) was found resistant to AMC

and AMP whereas sensitive to remaining antibiotics used showing 22% resistance.

AMIC2 (Bacillus spp.) was found resistant to ATM and MET whereas it was sensitive to

remaining antibiotics used for the test showing an overall 18.18% resistance. Similarly,

AMIC3 (Bacillus spp.) was resistant to CAZ, FOX and MET whereas it was sensitive to

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remaining antibiotics showing 30% resistance. It was evident from the results that all the

strains were sensitive to most of the commonly used antibiotics and therefore can be used

for the bioremediation of the textile effluents. Secondly results described that these

effluents were not contaminated with the hospital waste that’s why the isolated strains did

not possess the antibiotic resistance genes.

The results of antibiotic susceptibility pattern in present study are in agreement

with the work of Sivan et al. (2015) who found that E. coli isolated from industrial

effluent was resistant to penicillin, cephalexin and erythromycin whereas it was sensitive

to remaining antibiotics showing 30% resistance. Similar results were documented by

Gupta et al. (2016) who found that R. halophytocola isolated from industrial effluent was

resistant to only kanamycin whereas it was sensitive to remaining antibiotics showing

12.5% resistance. Similar results were reported by Sapale et al. (2015)who found that

Bacillus spp. isolated from contaminated soil was resistance to neomycin, nitrofurantoin

and aztreonam whereas it was sensitive to remaining antibiotics showing 30% resistance.

Molecular characterization of the three isolates named as AMIC1, AMIC2 and

AMIC3 was done and the results showed that bacterial strain AMIC1 was confirmed as

Klebsiella variicola showing 99.79% similarity with Klebsiella variicola DSM

15968T(AJ783916). AMIC2 confirmed as Bacillus cereus showing 99.86% similarity

with Bacillus cereus ATCC 14579T (AE016877). Similarly, AMIC3 also confirmed as

Bacillus cereus showing 99.79% similarity with Bacillus cereus ATCC 14579T

(AE016877).

After the molecular characterization and species identification, biosorption

potential of indigenous bacterial strains i.e. AMIC1 (Klebsiella variicola), AMIC2 and

AMIC3 (Bacillus cerus) was determined against two metals i.e. Nickel (Ni) and Cobalt

(Co) through ICP-OES. Percentage reduction in metal concentrations after 24 and

48hours were determined. The results showed that AMIC1 (Klebsiella spp.) reduced

Nickel (Ni) 49 and 50% whereas reduction of Cobalt (Co) was 68.6 and 71% after 24 and

48hours respectively. AMIC2 (B. cerus) reduced Nickel (Ni) 48.4 and 49% whereas

reduction of Cobalt (Co) was 70.6 and 73.6% after 24 and 48hours. Similarly, AMIC3

(B. cerus) reduced Nickel (Ni) 50.6 and 51.8% whereas reduction of Cobalt (Co) was

71.8 and 73.2 after 24 and 48hours respectively. For statistical analysis Z-test was

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performed to compare the biosorption potential of each bacterial strain at two different

incubation times and to compare the biosorption capacity of each bacterial strain for both

metals i.e. Ni and Co at each incubation time. Results revealed a non-significant

difference (P>0.05) in the metal absorption capacity of all the bacterial strains when

incubated for 24 hours and 48 hours but there was a significant difference (P<0.05) in

biosorption capacity of each bacterial strain for both metals. Results showed a significant

difference (P<0.05) in the reduction of Ni and Co for all the strains. It was concluded

from the results of biosorption experiment that reduction pattern for Ni was found as

AMIC3>AMIC1>AMIC2 and for Co as AMIC2>AMIC3>AMIC1.

The results of metal absorption potential in present study were in agreement with

the work of Das et al. (2016) who found that Enterobacter spp. and Klebsiella spp.

isolated from industrial effluents significantly (P<0.05) reduced Pb. Similar results were

reported by Abbas et al. (2014) who found that Pseudomonas spp.M3 isolated from

wastewater samples was able to reduce 70% Cd from medium. In another study, Abbas et

al. (2014) found that Enterobacter spp. and K. pneumonia isolated from industrial

effluents significantly (P<0.05) reduced Ar. Similar results were documented by

Alboghobeish et al. (2014) who found that K. oxytoca decreased 83mg/l of Ni+2 from the

medium after 72 hours. Similarly Gawali et al. (2014) reported that E. coli was able to

remove Pb and Cu with removal percentage of 45% and 62% respectively. P. aeruginosa

was able to remove Cd, Ni and Co with removal percentage of 56%, 34% and 53%

respectively. Whereas E. acrogens was able remove Cd and Cu with removal percentage

of 44% and 34% respectively.

FT-IR study was carried out to confirm the difference between functional groups

in relation to biosorption of metal (Ni and Co) using metal-loaded (Ni or Co) biomass in

comparison to control (bacteria grown in normal conditions). The control sample

demonstrated the presence of a number of absorption peaks and reflected the complex

nature of the biomass. A change of absorption bands were observed, when we compared

the FT-IR spectra of control and metal loaded biomass. After the evaluation of AMIC1

(K. variicola) spectra it was observed that there was a change in peak at 3500–3200 cm-1

region in spectrum of Ni and Co and it was considered as the binding of Ni and Co with

amino and hydroxyl group. Similarly a change in peak at 1500-1750 cm-1 region in

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spectrum of Ni and Co was observed which indicated the binding of Ni and Co with

carboxyl group. After the evaluation of AMIC2 and AMIC3 (B. cerus) spectra it was

observed that there was a change in peak at 3500–3200 cm-1 regions in spectrum of Ni

and Co and was considered as the binding of Ni and Co with amino and hydroxyl group.

Similarly a change in peak at 2900-3000 cm−1 regions in spectrum of Ni and Co was

considered as the binding of Ni and Co with –CH2 groups combined with that of the CH3

groups. A similar change in peak at 1300–1067 cm−1 regions considered as the binding of

Ni and Co with carboxyl and phosphate groups.

The results of the present study are in agreement with Park et al. 2005 who

performed a similar study and described that a peak at 3500–3200 cm-1 region is due to

the stretching of the N–H bond of amino groups and indicates bonded hydroxyl group.

Similarly Kazy et al. 2006 described that the absorption peaks at 2900–3000 cm−1 are

attributed to the asymmetric stretching of C–H bond of the –CH2 groups combined with

that of the CH3 groups. Pistorius, 1995 described that the peaks in the range 1300–1067

cm−1 are attributable to the presence of carboxyl and phosphate groups. Pradhan et al.,

2007; Volesky, 2007 insisted that mainly functional groups including (hydroxyl,

carbonyl, carboxyl, sulfonate, amide, imidazole, phosphonate and phosphodiester) are

responsible for the biosorption of metals. Quintelas et al. 2009 performed a similar study

and observed that functional groups on the biomass, such as hydroxyl, carboxyl and

phosphate groups, would be the main binding sites for biosorption of the studied heavy

metals by E. coli. Similar results were documented by Kang et al. 2006 who compared

the FT-IR spectra of pristine and chromium loaded biomass and found that P. aeruginosa

before and after metal binding indicated that –NH is involved in Cr (VI) biosorption.

For the identification of morphological changes occurred in the outer surface of

the bacteria in response to metal (Ni or Co) SEM was performed. It was evident from the

results that both metals (Ni & Co) affected the Gram +ve bacterial cell wall more

adversely as compared to Gram-ve cell wall. This might be associated with the presence

of more peptidoglycan in the cell wall of G +ve bacteria and possible affiliation of heavy

metals with it. Metals adsorbed with the cell wall and destroyed its normal structure and

also created pores in the cell wall when absorbed in to the cell. It was clearly evident that

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damaging effect of Ni was more prominent on both types of bacteria (Gram +ve & Gram-

ve) as compared to Co. Results are in agreement with the results of Sujatha et al. (2013)

who documented that the surface modifications occurred by reducing the irregularity,

after binding of Ni(II) ions onto the surface of Trichoderma viride biomass. In a similar

study, Chakravarty & Banerjee (2008) reported that there was a clear change (rough cell

surface and membrane indentations) in the outer surface of acidophilic bacterium under

metal stress condition.

Conclusion

In this study 30 samples were collected from textiles drains present in and around

Faisalabad Punjab Pakistan. Out of 30 samples, 13 were found positive for HMT bacteria,

out of which 03 samples were found to have novels HMT bacterial strains which were

able to tolerate NI, Co and also exhibited MMR. These strains were provisionally named

as AMIC1, AMIC2 and AMIC3. Molecular characterization confirmed them as AMIC1

(Klebsiella variicola) whereas AMIC2 and AMIC3 (Bacillus cerus). Their biosorptive

potential was evaluated against Ni and Co through different in-vitro analyses and found

to have significant biosorptive potential against both metals in varying concentration. It

was evident from the results of biosorption experiment that reduction pattern for Ni was

AMIC3>AMIC1>AMIC2 and for Co it was AMIC2>AMIC3>AMIC1. On the basis of

overall results it was concluded that all three indigenous strains (Klebsiella variicola,

accession number LT838344), AMIC2 and AMIC3(Bacillus cereus accession numbers

LT838345 and LT838346) had considerable bioremediation potential which may be

utilized in future as potential candidate for the development of bioremediation agents to

detoxify textile effluents at industrial surroundings within natural environments in

Pakistan.

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Chapter 5

SUMMARY

Several studies have been conducted and being conducted to elaborate the effects

of heavy metals on living organisms including animals, plants and human.

Microorganisms that are able to survive well in high concentration of heavy metals are of

great interest as bioremediation agents because they can achieve different transformation

and immobilization processes. Specifically, they conduct bioaccumulation based on the

incorporation of metals inside the living biomass or biosorption, in which metal ions are

adsorbed at the cellular surface by different mechanisms.

Faisalabad is the major industrial center. Due to the heavy industrialization

different types of waste is being produced by the different industries. The textile zone is

playing a vital role in the export of the country but at the same time a lot of

environmental pollution is being produced by this zone so it is one of the main polluter in

industrial sector. Therefore it was need of the time to analyze these wastes to find out

some native strains of HMT bacteria and to explore their potential in bioremediation of

common heavy metals founds in such effluents.

As a matter of interest and need of time, present study was conducted. Six main

drains present in and around Faisalabad, receiving the textile effluents and surrounding

different textile units were selected. From each drain, 05 effluent samples were collected

at the distance of about 1000 meter between two points. In this way, total 30 samples

were collected and subjected to the analysis for the presence of heavy metals like Ni, Co,

Cr, Zn and Pb. It was found that Ni and Co were the most frequent metals present in all

samples, on the basis of the results these two metals were selected for the further study.

The physico-chemical properties like pH, EC, DO, COD, BOD, TDS, TSS and TS were

measured. The overall values of different physico-chemical parameters in effluent

samples collected from all locations were on the higher side when compared to the limits

of NEQS, which provides evidence that all the collected samples were highly polluted.

Then the isolation and identification of HMT bacteria was done by growing the

bacterial isolates on selective growth media having different concentrations of metal

salts.After initial screening, it was observed that 13 out of total 30 effluent samples

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exhibited bacterial growth on Nutrient agar incorporated with 0.5mM of Ni. After

determination of their MTC, it was observed that 03 samples i.e. SarDP2, RgrDP3 and

SarDP5 found have some novel bacterial strains which were able to grow on Nutrient agar

incorporated with 08mM of Ni. Then pure cultures of bacteria from these samples were

obtained through streak plate method and single colonies were cultured for further

studies. Then these three samples were screened for tolerance to Co & Cr and MMR

against Ni, Co and Cr. It was evident from the results that bacteria from sample SarDP2

were able to tolerate Co up to 06mM & Cr up to 7.5mM separately and also exhibited

MMR to Ni, Co and Cr (1:1:1) up to 5.5mM. Isolate from RgrDP3 was able to tolerate Co

up to 07mM, Cr up to 07mM and showed MMR to Ni, Co and Cr (1:1:1) up to 4.5mM.

Similarly, isolate from SarDP5 was able to tolerate Co up to 6.5mM, Cr up to 07mM and

exhibited MMR to Ni, Co and Cr (1:1:1) up to 4.5mM.

These aforementioned bacterial strains which were able to tolerate the maximum

concentration of heavy metals isolated from effluent samples RgrDP3, SarDP2 and

SarDP5 were named as AMIC1, AMIC2 and AMIC3, respectively. After Gram’s staining

of these strains, it was observed that bacterial strains AMIC2 and AMIC3 were Gram +ve

rods whereas bacterial strain AMIC1 was Gram -ve rods. After examination of colony

characteristics on selective & differential media, biochemical and sugar fermentation

tests results, it was confirmed that bacterial strain AMIC1 isolated from effluent sample

RgrDP3 was Klebsiella spp. whereas AMIC2 and AMIC3 isolated from SarDP2 and

SarDP5 were Bacillus spp.

Molecular characterization and phylogenetic analysis was done through PCR

and sequencing. It was confirmed that bacterial strain AMIC1 was Klebsiella variicola

(accession number LT838344); whereas bacterial strains AMIC2 and AMIC3 were

Bacillus cereus (accession numbers LT838345 and LT838346). Antibiotic susceptibility

pattern of HMT bacteria was determined through disc diffusion method. It was evident

from the results that strain AMIC1 (Klebsiella variicola) was found resistant to AMC and

AMP whereas sensitive to remaining antibiotics used showing overall 22% resistance.

AMIC2 (Bacillus cereus) was found resistant to ATM and MET whereas it was sensitive

to remaining antibiotics used for the test showing an overall 18.18% resistance. Similarly,

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AMIC3 (Bacillus cereus) was resistant to CAZ, FOX and MET whereas it was sensitive

to remaining antibiotics showing overall 30% resistance.

Biosorption potential of isolated HMT indigenous bacterial strains was evaluated

by inductively coupled plasma optical emission spectroscopy (ICP-OES). Percentage

reduction in metal concentrations after 24 and 48hours were determined. The results

showed that AMIC1 (Klebsiella variicola) reduced Nickel (Ni) 49 and 50% whereas

reduction of Cobalt (Co) was 68.6 and 71% after 24 and 48hours respectively. AMIC2

(Bacillus cereus) reduced Nickel (Ni) 48.4 and 49% whereas reduction of Cobalt (Co)

was 70.6and 73.6% after 24 and 48hours. Similarly, AMIC3 (Bacillus cereus) reduced

Nickel (Ni) 50.6and 51.8% whereas reduction of Cobalt (Co) was 71.8 and 73.2 after 24

and 48hours respectively. Reduction pattern for Ni was found as

AMIC3>AMIC1>AMIC2 and pattern for Co was found as AMIC2>AMIC3>AMIC1

FT-IR study was carried out to confirm the difference between functional groups

in relation to biosorption of metal (Ni and Co) using metal-loaded (Ni or Co) biomass in

comparison to control (bacteria grown in normal conditions). After the evaluation of

AMIC1 (Klebsiella variicola) spectra it was observed that there was a change in peak at

3500–3200 cm-1 region in spectrum of Ni and Co and it was considered as the binding of

Ni and Co with amino and hydroxyl group. Similarly a change in peak at 1500-1750 cm-1

region in spectrum of Ni and Co was observed which indicated the binding of Ni and Co

with carboxyl group. While the spectra evaluation of AMIC2 and AMIC3 (Bacillus

cereus) it was observed that there was a change in peak at 3500–3200 cm-1 regions in

spectrum of Ni and Co and was considered as the binding site of Ni and Co with amino

and hydroxyl group. Similarly a change in peak at 2900-3000 cm−1 regions in spectrum

of Ni and Co was considered as the binding of Ni and Co with -CH2 groups combined

with that of the CH3 groups. A similar change in peak at 1300–1067 cm−1 regions was

considered as the binding of Ni and Co with carboxyl and phosphate groups.

Finally, scanning electron microscopy (SEM) was done to observe any surface

morphological changes developed in HMT bacteria due to metal stress. It was evident

from the results that both metals (Ni & Co) affected the Gram +ve bacterial cell wall

more adversely as compared to Gram -ve bacterial cell wall. Metals adsorbed with the

140

cell wall and created pores in it. It was observed that damaging effects of Ni were more

prominent than Co on both types of bacteria (Gram +ve & Gram –ve).

Based on overall results it was concluded that three indigenous bacterial strains

i.e. AMIC1 (Klebsiella variicola), AMIC2 and AMIC3 (Bacillus cereus) isolated from

industrial effluents of Faisalabad Pakistan tolerated heavy metals (Ni & Co) very well.

Furthermore, they possessed a significant bioremediation potential against these metals

and may be highly useful as a bioremediation tool to detoxify textile effluents at

industrial surroundings within natural environments in the country in future. It is

suggested that further studies should be conducted based on the findings of the present

study as it will provide a way forward in this field.

141

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