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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
4.9. Determination of biosorption potential of indigenous HMT bacterial
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
collected effluent samples
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
26. Optimum growth conditions for bacterial strain AMIC2
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
27. (b) Group x pH interaction Means ±SE 88
27. (c) Group x Temperature x pH interaction Means ±SE 89
28. Optimum growth conditions for bacterial strain AMIC3
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
29. (b) Group x pH interaction Means ±SE 92
29. (c) Group x Temperature x pH interaction Means ±SE 93
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
42. Percentage reduction of Nickel (Ni) and Cobalt (Co) by AMIC2
(Bacillus spp.) through (ICP-OES)
115
43. Percentage reduction of Nickel (Ni) and Cobalt (Co) by AMIC3
(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
2. Regression line showing relation between Ni concentration and
number of bacteria for effluent sample RgrDP3
71
3. Regression line showing relation between Ni concentration and
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
12. Graph showing optimum growth conditions for AMIC2
(Bacillus spp.) without and with metals
90
13. Graph showing optimum growth conditions for AMIC3
(Bacillus spp.) without and with metals
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
17. Graph showing effect of Ni on the growth rate of AMIC2
(Bacillus spp.) 100
18. Graph showing effect of Co on the growth rate of AMIC2
(Bacillus spp.)
101
19. Graph showing effect of Ni vs. Co on the growth rate of AMIC2
(Bacillus spp.)
102
20. Graph showing effect of Ni on the growth rate of AMIC3
(Bacillus spp.)
103
21. Graph showing effect of Co on the growth rate of AMIC3
(Bacillus spp.)
104
22. Graph showing effect of Ni vs. Co on the growth rate of AMIC3
(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
29. FT-IR spectra of AMIC2 biomass without metal loading 120
30. FT-IR spectra of AMIC2 biomass loaded with Ni 121
31. FT-IR spectra of AMIC2 biomass loaded with Co 121
32. FT-IR spectra of AMIC3 biomass without metal loading 122
33. FT-IR spectra of AMIC3 biomass loaded with Ni 122
34. FT-IR spectra of AMIC3 biomass loaded with Co 123
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
bioremediation of heavy metals.
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
bioremediation of heavy metals.
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
characterization of the isolates was done through 16s rRNA technique. The isolates were
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
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 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
ii. MW= 290.79 g/mol
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).
Formula for calculating working solutions
Vi = Vf×Cf
𝐶𝑖
Where,
Initial concentration of stock solution (Ci) = 1000 ppm
Initial volume of stock solution taken (Vi) = 100 ml
Final media volume required (Vf) = 200 ml
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
ii. MW= 237.93 g/mol
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.
Formula for calculating working solutions
Vi = Vf×Cf
𝐶𝑖
Where,
Initial concentration of stock solution (Ci) = 100 mM
Initial volume of stock solution taken (Vi) = 02 ml
Final media volume required (Vf) = 200 ml
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
ii. MW= 237.93 g/mol
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).
Formula for calculating working solutions
Vi = Vf×Cf
𝐶𝑖
Initial concentration of stock solution (Ci) = 1000 ppm
Initial volume of stock solution taken (Vi) = 100 ml
Final media volume required (Vf) = 200 ml
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).
3.11. Determination of biosorption potential of indigenous HMT bacterial
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
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 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
Figure 2: Regression line showing relation between Ni concentration and number
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
Figure 3: Regression line showing relation between Ni concentration and number
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
Ni concentration (mM)
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
Ni concentration (mM)
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
Without with Ni With Co
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
Without with Ni With Co
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
Table 26: Optimum growth conditions for bacterial strain AMIC2 identified
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
(a) Group x Temperature interaction Means ±SE
Temp Metal Mean
Without with Ni With Co
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
(b) Group x pH interaction Means ±SE
pH Metal Mean
Without with Ni With Co
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
(c) Group x Temperature x pH interaction Means ±SE
Temp pH Metal Mean
Without with Ni With Co
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
Figure 12: Graph showing optimum growth conditions for AMIC2
(Bacillus spp.) without and with metals
25oC 30oC 37oC 40oC
Temperature & pH
91
Table 28: Optimum growth conditions for bacterial strain AMIC3 identified
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
(a) Group x Temperature interaction Means ±SE
Temp Metal Mean
Without with Ni With Co
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
(b) Group x pH interaction Means ±SE
pH Metal Mean
Without with Ni With Co
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
(c) Group x Temperature x pH interaction Means ±SE
Temp pH Metal Mean
Without with Ni With Co
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
Figure 13: Graph showing optimum growth conditions for AMIC3
(Bacillus spp.) without and with metals
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
NS = Non-significant (P>0.05); * = Significant (P<0.05); ** = Highly significant (P<0.01)
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
0hour 04hours 08hours 12hours 16hours 20hours 24hours 28hours
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
0hour 04hours 08hours 12hours 16hours 20hours 24hours 28hours
0.004 0.007 0.18 0.29 0.34 0.38 0.406 0.457
Growth
without Co
Reading intervals
0hour 04hours 08hours 12hours 16hours 20hours 24hours 28hours
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
0hour 04hours 08hours 12hours 16hours 20hours 24hours 28hours
0.0042 0.006 0.10 0.21 0.34 0.443 0.521 0.534
Growth
without Ni
Reading intervals
0hour 04hours 08hours 12hours 16hours 20hours 24hours 28hours
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
0hour 04hours 08hours 12hours 16hours 20hours 24hours 28hours
0.004 0.0075 0.15 0.2 0.28 0.34 0.37 0.40
Growth
without Co
Reading intervals
0hour 04hours 08hours 12hours 16hours 20hours 24hours 28hours
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
0hour 04hours 08hours 12hours 16hours 20hours 24hours 28hours
0.004 0.009 0.123 0.257 0.358 0.489 0.549 0.61
Growth
without Ni
Reading intervals
0hour 04hours 08hours 12hours 16hours 20hours 24hours 28hours
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
0hour 04hours 08hours 12hours 16hours 20hours 24hours 28hours
0.004 0.008 0.11 0.235 0.337 0.39 0.455 0.523
Growth
without Co
Reading intervals
0hour 04hours 08hours 12hours 16hours 20hours 24hours 28hours
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.
No. Antibiotics Abbreviation
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
R*: Resistant, S*: Sensitive, I*: Intermediate
109
Table 39: Antibiotic susceptibility pattern of AMIC3 (Bacillus spp.)
Sr.
No. Antibiotics Abbreviation
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
R*: Resistant, S*: Sensitive, I*: Intermediate
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
4.9. Determination of biosorption potential of indigenous HMT bacterial
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.
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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
Initial Final % age Initial Final % age S1 vs. S2
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**
NS = Non-significant (P>0.05); * = Significant (P<0.05); ** = Highly significant (P<0.01)
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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
Initial Final % age Initial Final % age S1 vs. S2
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
I F % age I F % age S1 vs. S2
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
I F % age I F % age S1 vs. S2
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*
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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
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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
120
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
121
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
122
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
123
Figure 34: FT-IR spectra of AMIC3 (Bacillus cereus) biomass loaded with Co
124
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
126
Figure 37: Electron micrograph showing the effect of Co on Klebsiella variicola
Figure 38: Electron micrograph of Bacillus cereus grown without metal stress
(control)
127
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
134
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
135
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
136
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
138
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,
139
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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