Final Year Dissertation 26. April. 2016

1
DembaS. Jammeh (10027948) Northumbria University April 2016
A study exploring bacterial biodiversity in acid mine contaminated sediments
In
Adventdalen Landfill, Svalbard North of Norway
by
Demba S Jammeh
(10027948)
Supervisor: Professor David Pears
Final year project report for BSc (Hons) Biology with Forensic Biology
Applied Sciences
Faculty of Health and Life Sciences
Northumbria University
April / 2016

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Bacterial biodiversity in acid mine contaminated sediment
In
Adventdalen Landfill, Svalbard North of Norway
A project report submitted in partial fulfilment of the requirements for BSc (HONS) Biology with
Forensic Biology Degree
By
Demba S Jammeh
(10027948)
Applied Sciences
Faculty of Health and Life Sciences
Northumbria University
April / 2016
Declaration: I, Demba S Jammeh confirm that I have read and understood the University
regulations concerning plagiarism and that the work contained within this project report is my own
work within the meaning of the regulations.
Signed………………………………………………………………………

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Bacterial biodiversity in acid mine contaminated sediment in Adventdalen Landfill, Svalbard North of
Norway
ABSTRACT:
Located in Svalbard North of Norway (78° North), Adventdalen Landfill is contaminated with house whole
waste and acid mine from abandoned municipal waste and coal mine streams. Surface running water increase
contamination towards the downstream creating AMD pollution gradient with deposition of both organic and
inorganic compounds along the effluent. Sediment collected from both upstream and downstream sites were
analysed for presence of organic and inorganic compounds. Also sediments isolated for bacteria culture and
DNAs send for 16S rRNA sequence analysis for identification of existing culturable bacteria species of extreme
environmental bacteria niche. Morphological analysis of bacteria culture plates divulge high number of colonies
forming units, sticky texture, mucoid, moist and growth into the medium in the downstream site isolated in
higher pH 7.60 and this observation shows different culturable bacteria presence compare to upstream with pH
2.90. DAPI counting of sediments resulted with significant differences as upstream site of low pH 2.90 show
lower abundance of bacteria count than the downstream site higher pH 7.60. GC-MS analysis for organic
compounds also reveals a significant difference as the downstream shows more contamination than upstream
sites. Analysis using X-ray fluorescence Spectrometry (XRF) methods for inorganic compounds reveals
presence of more than 23 different elements including sulfuric, iron, uranium, sodium, barium, praseodymium,
calcium and magnesium in higher values for downstream than up streams. The article associated the
downstream pollution to contaminated run-off surface water with acidity as bacteria species that do not tolerate
or resist effect of low pH would have changed adaptation along the stream due to pollution. Moreover, the
undoubted view of the study is that pH and organic compounds analysed were factors that significantly
structured the microbial community compositions along the Adventdalen Landfill of Svalbard, North of
Norway.
Word count: 289

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Table of Contents
Contents pages
ABSTRACT………………………….…………………………..…………..…………………3
CHAPTER 1…………………………………………………..…..…………………...……….7
1. Introduction………………………………….……………………………………..…..8
1.1 Bacterial Diversity in Arctic Environment……………………………………...8-9
1.2 Adaptation in Arctic Environment…………………………………………….….9
1.3 Acid Mine…………………………………………………………..……………9-10
1.4 Landfill…………………………………………………………….…………....10-11
1.5 The Aim……………………………………………………………………….........11
1.6 Site Description:……………………………………………………………………12
CHAPTER 2………………………………………..………………………………………….13
2. Materials and Methods……………………………………………………………..…..14
2.1 Sample preparation:…………………………………………….………………….14
2.2 Gas Chromatography (GC-MS)………………………………………………..….14
2.3 Bacteria Culture……………………………………………………….……………15
2.4 DNA Extraction, (P CR) and 16s rRNA Sequencing………………………….15-16
2.5 Agarose Gel Electrophoresis………………………………………………..………16
2.6 DAPI (4',6-diamidino-2-phenylindole)…………………………………..…………17
CHAPTER 3………………………………………………………..……………………………18
3. Results……………………………………………………………………………..……….19
3.1 Organic Compounds characterization (GC-MS)………………………………..19-20
3.2 Inorganic Compounds characterization (XRF).…………………………………21-22
3.3 Bacteria Culture……………………………………………………………………….23
3.4 DAPI (4',6-diamidino-2-phenylindole)……………………………………………….24
3.5 PCR and 16S rRNA Sequencing…………..…………………………………………..25

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Table of Contents (Cont…)
Contents pages
CHAPTER 4…………………………………………………………………………………..…26
4. Discussion, Conclusion AND Future Work……………………………………………..26
4.1 Bacteria Culture…………………………………………………………………..27-28
4.2 DAPI (4',6-diamidino-2-phenylindole)………………………………………………28
4.3 Organic Compounds (GC-MS)……………………………………………….......28-29
4.4 Inorganic Compounds (XRF)……………………………………………………..29-31
4.5 PCR and 16S rRNA sequencing…………………………………………..………31-32
4.6 Conclusion………………………………………………………………………….…3.2
4.7 Future Work…………………………………………………………………………..33
CHAPTER 5………………………………………………………………………………………34
5. References……………………………………………………………………………….35-37
ACKNOWLEDGEMENT:
I would like to thank Professor David Pearce for giving me the opportunity to participate in his
research work and Professor John Dean for his support on GC-MS analytical approach and
all technicians in EBA 314, EBA 402, EBA 504 for their valuable support. I would like to thank
Central Government of the Republic of the Gambia though Gambia Police Force for financial
support and all the staff of Personal Management Office (PMO) for allowing me to study in
this prestigious Northumbria University. I would also like to thank all my family and friends for
their moral support and encouragement throughout the course of my degree.

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LEFT BLANK INTENTIONALLY

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CHAPTER 1
INTRODUCTION

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1 Introduction
The work presented here is a final year research project to investigate sediment microbial diversity in acid
mine drain contamination in Adventdalen Landfill, Svalbard North of Norway. Soil samples were
collected by Professor David Pears with the team on 09/07/2015 and stored at -200C until the start of
these experiments in October 2015 and below is the full detail of experimental methods, results,
discussion and conclusions.
1.1 Bacterial Diversity in Arctic Environment
Arctic regions are frequently inhabited by abundance of microbial communities adjusted to extreme
environment like cold, snow, humidity and fluctuating temperature. Studies reveals that Arctic soil bacterial
communities is diverge greatly in composition, richness across environmental owing to both natural and human
influence be it climate change, community impact leading to acidity or mineral contamination as mentioned by
(Blaud et al., 2015). However understanding specific factors that effect change impacted on soil
microorganisms population, diversity and the process of arctic landfill biodegradation processes across arctic
regions and landfills is limited (Song et al., 2015a). This phenomenon advance research interest in the arctic
environment which is subjected to extreme environmental conditions by climate change and acidification (Blaud
et al., 2015) especially in Spitsbergen, Adventdalen landfill. Recently studies have confirm that Alpha, beta and
gamma-proteobacteria, Cytophaga-Flavo-bacterium-Bacteroides species, Pseudomonas sp. and Spirosoma sp,
G+C Gram positive genera are the most abundant in extreme cold environments (Amaral-Zettler, 2013, McCann
et al., 2016). This means the above taxa have specific characteristics or mechanisms at both molecular and
cellular level that helps them acclimatize to extreme environments or resist the unfavourable condition which
could be biological or non-biological process related. As in previous papers, pH is one of the best predictor of
changes in soil bacterial communities due to its effects on cells molecular mechanisms which affect bacteria cell
growths and developments, including Acidobacteria and Actinobacteria as reveal in (Wan et al. 2012). Although
pH appears influencing the patterns in soil microbial diversity, the influence of other environmental factors
including nutrients availability, carbon sources, humidity, contamination due to organic or inorganic compounds
may predict soil microbial community structure across larger spatial scales. This is supported by Chu et al that

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pH may not directly alter bacterial community structure but imposes a physiological constraint on soil bacteria
such as Acidobacteria; altering competitive outcomes when soil pH falls outside range of bacteria cell (Chu et
al., 2010).
1.2 Adaptation in Arctic Environment
Lives in arctic environments depends on the organism’s ability to explore adaptation mechanisms for resistance
or acclimatized to tough environmental conditions such as, low pH, freezing temperatures, nitrogen fixation and
UV radiation properties as Cyanobacteria in cold extreme environment survive with significant growth level
(Zakhia et al., 2008, Dhakar and Pandey, 2016). This means survival in the arctic environment requires bacteria
to adapt freeze-resistant and freeze-tolerant mechanism as mentioned in (De Santi et al., 2016) and less adaptive
bacteria survival and growth rate diminished as negative environmental conditions increases. Many studies into
bacteria adaption in extreme environments has discover that microorganisms have special molecular proteins
models for modification of molecular constituents such as enzyme, lipid active functions, production of cold
shock proteins, antioxidants repair and cell protection in freezing temperature as in mesophilic bacteria
(Chattopadhyay, 2006, Dhakar and Pandey, 2016). In this process bacteria lipid membrane fluidity is either
increases or decrease to stabilize bilayer, ‘‘trans- to cis’’ monogenic fatty acids and cyclopropyl fatty acids to
their monogenic precursors and neutralize environmental stress as temperature vary or pH variations
(Watzinger, 2015, Willers et al., 2015). This modification at molecular level is crucial in membrane fluidity in
low pH, colder temperatures shockwave as mechanism of cellular processes such as transcription, translation
and protein folding is regulated and growth progress (Reed et al.,2013).
1.3 Acid Mine
Acid mine pollution is an extensive ecological problem primarily resulting from the oxidative dissolution of
pyrite (FeS2) and other sulphide minerals exposed to oxygen and water through metal ore mining or deposition
(Kuang et al., 2013a). Acidic environments is a concern as it contaminates soil, rivers, sediments due to
underground water upsurge by capillarity motion, rain water accumulations, run-off water with contaminated
chemicals which affects the growth of most microorganisms and plants taxa (Buzatu et al., 2016, Cánovas et
al., 2010). Acidification is a complex process that is induce through chain of biotic including bacteria activities

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and or abiotic reactions methods via evaporation, oxidation, hydrolysis, neutralization and acid fermentation
(Valente et al., 2013). Acidification occurs in municipal solid waste as well as coal mines, this resulted in
release of compounds as sulphide oxidation processes, metals and metalloids as accessory elements and the
acidic leachates react with the surrounding mineral matrix releasing elements such as Al, Ca, Si, Na, K and Mn
(Lee et al., 2015, Dorotan et al., 2015). Studies have shown that level of contamination depends on surface
water due to rain, snow melt, tributaries currents and other liquid flows from higher level within an acidic
environments of upstream towards downstream which makes them more acidified as surface water channels
sulfuric acid and accelerates the oxidation of sulphides (Cánovas et al., 2010, Kumanova et al., 2015).
Therefore environments with acid characteristics exerts negative pressure on microorganisms and the survival
becomes adaptation or ability to resists the effects as several studies including Zhalnina et al. reveals that
acidobacteria and firmicutes are the most abundantly in low pH even in Park Grass experiment (Zhalnina et al.,
2015). Further to correlates with that finding, Gong et al. in their study on molecular mechanisms of genes
discover a significant positive relationship between pH and presence of global distribution of sqhC genes of
Acidobacteria taxa in acidic environments (Gong et al.,2015).
1.4 Landfill
In the past, landfill is the widely employed method of disposing municipal consumable products and coal mine
waste leading to significant build-up of refuse and contamination which routinely affect growths and
developments of microorganisms as stated by (Clarke et al., 2015, Ghosh et al., 2015, Grisey and Aleya, 2016).
Landfill drainage contamination increases through surface run-off water affecting the quality of neighbouring
vegetation, soil and water. Many studies discover that depending on the composition of the leakage compounds,
this could cause cancer for the population when consumed and can also affect soil microorganisms growths and
developments except taxa which benefits on the chemicals or nutrients available in the leakage (Ghosh et al.,
2015). Municipal waste landfills is normally the accumulations of both organics and inorganics compounds of
non-biological or biological residues and the process of degradation depends on the nature and composition of
the mixture, the environmental conditions like temperature, humidity, CO2 and water. During municipal waste
degradation, rain water infiltrates surfaces, accumulates both biological and chemical substances then dissolving
organic matter as mentioned in (Grisey and Aleya, 2016, Comstock et al., 2010) and also alcohols, acids,

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carbohydrates, inorganic macro components of cations and anions in sulfur, chlorines, ammonia and heavy
metals such as iron, lead, nickel and copper. Therefore, level of degradation, composition and level of
contamination depending on various factors such as amount of rainfall, age of the landfill, waste composition,
mixture and degradation stage of the waste (Ghosh et al., 2015, Clarke et al., 2015, Watzinger, 2015, Comstock
et al., 2010). As most municipal landfills are residues of house whole consumables which contains main
biodegradable constituents of cellulose and hemicellulose, studies reveals that once fermented release
carboxylic acids, alcohols which is the main consumable constituents for acetogenic bacteria in the waste
landfills (Quadros et al., 2016). Therefore leakage potentially mineralised environments causing variation of
bacterial community structure due to adaptation to the constituent of the leakage components, temperature, pH,
humidity as mentioned by (Song et al., 2015a). Neutralisation of acidic environments normally achieved in
different forms as inflow of fresh running water that dilutes the concentrated acidic and seepages it away
through the streams or alternatively as mentioned by Sträuber et al., that methanogens reduce the carbon dioxide
and hydrogen into methane leading to neutral pH causing soluble chemicals like aluminium to become more
soluble to the environment as well as hydrogen and carbon dioxide (Sträuber et al., 2015). Furthermore this lead
to the progression from acid phase to methanogenic phase in production of enough methane, a decrease in
organic compounds and pH more neutral as methanogenic phase further stabilised in presence of cellulose or
hemicellulose for hydrolysis and fermentation (Song et al., 2015e).
1.5 The Aim
Contaminated soil sediments with coal mines and municipal waste leads to pH gradients in extreme
environments and influence the bacteria abundance or cause difficulty in culture-dependent analysis of most
bacteria taxa. Most papers reveals that significant amount of acidic-dependent bacterial are difficult to be
culturable in acid contaminated soil sediments and this project aim to investigate effect of pH on soil bacteria
growth on solid media, 16S rRNA sequencing, DAPI staining to divulge bacteria abundance and biodiversity
and secondly to analyse potential organic contamination gradient between upstream and downstream sites.

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1.6 Site Description:
The site under investigation (appendix 6.1) is an abandon solid waste landfills and previous coal mine since
1991 with a life expectancy of 75 years in arctic region of Svalbard North of Norway (78° North). Lyche
indicates that the field contain predominantly residential, commercial solid waste and unused coal mine which is
hazards and as at 2001, approximately 1000 tons of waste was deposited and in 2006, 1700 tons before
cessation of dumping in 2007 (Lyche, 2011). Upon closure of the dump site, it was use for inert masses, non-
degradable waste such as gypsum, steel, concrete, insulation, glass for a while (Lyche, 2011). However as
reveals in the articles that abandoned municipal solid waste remains long enough in the soil before a
comprehensive biodegradation (Grisey and Aleya, 2016), therefore this landfill is still believe to have presence
of significant amounts of un-degraded municipal waste deposited long before 2007.
In this study, a total of 18 soil sediment samples were collected by Professor David Pears and the team on
09/07/2015 and stored at -20o
C before analysis. Samples site were identified as upstream (U) U1-U11 and
downstream (D) D1-D7. Site D1–D4 was sampled from the floodplain downstream of the bypass stream with
flow current from the North-West bend. Site D5 - D11 were taken from a stream that flowed directly from the
landfill itself. With influence of coal mine tides, U6 has pH 3.4 with possibly potential contamination from a
possible stream originating from the North-West corner of the landfill as the smell and colour of the sediments
are not pleasant. Sample site U5 was dry on the sampling day as reported and was not affected by any bypass
streams. The map of the site indicates three streams originating from different melt sources; South-East
measured pH 5.7-6.2 and to its edge a stagnant ponds which appears to be effect of flooding from the original
streams with pH 6.5. There was a man-made embankment from the mountain to the south-west with water from
glacial melt on the mountain next to an unused coal runs down the bypass and due to the closeness runoffs water
enters the landfill leading to second stream. According to records it was sunny day with temperature at 10.4 °C
during sampling.
WORD COUNT: 1850

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CHAPTER 2
MATERIALS AND METHODS

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2. MATERIALS AND METHODS
2.1 Sample preparation:
The samples under study were sediments of an unknown microorganism and were treated as level II biohazards
which followed sterilisation, good laboratory practice and recommended laboratory guidance. Sample
preparation start with thawing of freeze soil sediments at room temperature overnight on laboratory bench and
filtered through 0.20μm filter papers using vacuum pumps. The process was setup as in appendix 6.6 and a
moisture filter paper was place on the centre of the Buchner funnel for Liquid filtration process and the filtrated
store in clean glass bottles for subsequent liquid-liquid extraction of organic compounds and run through on
GC-MS. Individual cleaning of glass ware and the instruments were done before every next sample process to
avoid contamination from previous filtration. After filtration, the soil sediments were individually place on class
plates for overnight and air dried in fume cupboard as biosafety procedures as the chemical components and
contamination level and constituents of the soil is not known. All sediments were later grinded using mortar and
pestle and finally sieved through 2mm mesh to remove roots and debris inside the fume cupboard one after the
other then sediments were stored in brown paper bags in dry place before analysis.
2.2 Gas Chromatography (GC-MS)
Weighted 0.5g of dried soil sediment were dissolve in 5ml of Dichloromethane (DCM) in a 15ml glass capped
bottle and run through sonication extraction method for 5 munities and after left on the bench for the mixture to
set and separation of organic material from soil sediments be completed. After 5 minutes, sediments were settle
down on the bottom and the top supernatant which constitutes the organic compounds were collected and
filtered using 0.22µm filters into sample vial with individual identification numbers. Liquid-liquid extraction on
liquid filtrates was done by funnel separation method by mixing 50ml of filtrate liquid first added to 5ml of
DCM and 0.5g of sodium chloride in separation funnel. Homogenously mixed and gas build in were released by
opening the exits valve 3 times and allow to separate standing on stand as in appendix 6.7. After separation the
organic compound were harvested through the valve into sample via. Both Supernatant from sonication and
funnel separation were analysed for GC-MS in EBA402.

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2.3 Bacteria Culture
Under aseptic conditions throughout bacteria culture, firstly weighted 81g of LB broth agar was dissolve in
200ml of distilled water for (10 plates) and 0.25g of D3 and U7 soil sediment combined together was also
dissolve and the pH adjusted to the following (pH 4, 6, 8 and 10) by reducing the pH with HCl or increasing the
pH with NaOH then autoclave at 150 °C for 1.5 hours and after cooling to bearable hands, the media were
poured in Petri disc to set. The culture plates were labelled accordingly and stored at 4o
C until further
inoculation. At the time of inoculation, soil sediment (1g of D3 and U7) were separately dissolved in 10 ml
sterile distilled water and spread on to solid culture media and incubated under different temperature (4 °C,
room temperature, 10 °C) for bacteria isolation. All the procedures were conducted under aseptic conditions as
bunsen burners were in use throughout the process to avoid contaminations. Culture plates were read one week
later for morphological characterisation and results recorded after which some individual growth colonies from
plates on D3 and U7 were sub-culture as of previous pH level for pure isolation and some were extracted for 16s
DNA amplification and sequencing. Subcultures of selected colonies were done by inoculating a loop size from
each strain into a new solid media of LB broth agar. The subcultures were then inoculated at 10 °C for a further
week.
2.4 DNA Extraction, Polymerase Chain Reaction (P CR) and 16s rRNA sequencing,
DNA extraction and amplification were done on selected individual colonies from D3 and U7 culture plates by
harvesting colonies in level III laboratory hood. A loop size portion of colonies were transferred into PCR
master mix reaction which was prepared in advance at level II categories laboratory and run on thermal cycler
under conditions as below and eluted DNAs stored at -20°C. Amplification of 16s rRNA were done by
amplification of DNA extracted from culture colonies in master mix reactions of final volume 50µl by adding
40.75µl of PCR water, 5µl standard reaction buffer (10X), 5µl DNTP (10µmM), 1µl Forward primer (10µmM),
5µl Reverse primer (10µmM), 0.25µl Tag DNA and finally 1µl DNA template polymers. PCR thermal cycles
conditions consist of an initial denaturation of 55o
C for 30 seconds for 1 cycle, denaturation of 72o
C for 1
minute for 30 cycle, annealing at 95o
C for 30 seconds 30 cycle, extension at 55o
C for 1minutes 30 cycle, final
extension 72o
C for 5 minutes 1 cycle and hold at 10o
C indefinite. The amplified DNAs were clean as per

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protocol in appendix 6.10 and were later send for 16S rRNA sequencing to identified the grown colonies from
the cultures. This method is choosing as (Song et al., 2015, Krishnamurthi and Chakrabarti 2013; Laloui-
Carpentier et al. 2006) mentioned that 454 pyrosequencing method have the ability to analysed complex
microbial communities in an environment with larger niches as the methods has RNA protein specific
sequencing pattern expression at certain loci which could identified closely related genera. For culture-
independent analysis of soil sediments, this project weighted 0.25g of soil sediment and follows the protocol
using MoBio PowerSoil™ DNA Isolation Kit (Carlsbad, CA, USA) as in appendix 6.9. A DNA Isolation Kit
isolate microbial genomic DNA from soil which is used for PCR and sequencing. The soil is centrifuged with
different chemical solutions being added between each spin to isolate and purify the DNA as per manufacturer
instruction. Safety procedure was followed based on manufactural instruction and the MSDS
(http://www.mobio.com/images/custom/file/msds/12888.pdf (MSDS) and Appendix 6.13-6.15 (short COSHH
record form). The principle and hazards are similar to the use of DNA extraction kits.
2.5 Agarose Gel Electrophoresis
The 1% agarose gel were made by dissolving 1g of agarose (sigma-Aldrich) in 100ml of 1 X TAE buffer into a
heatproof glassware and put it to boiling point in a microwave for 3minutes. Using heatproof gloves, the gel
placed on the bench and 5µl of syber safe stains was disolved into the liquid gel and finally poured into the gel
slab to set. The laboratory stock of TAE buffer was at concentration of 50X and to reduce to 1X concentrations,
20ml of 50X TAE (provided by the technicians) was mixed with 980ml of distilled water and stored in the
cupboard. The gel slab was then immersed in 1 X TAE buffer so that the wells submerged sufficiently to be able
to held up to the loading samples. During loading procedures, 5ul of hyper ladder was added to the first well of
the agarose gel then follow by 10µl of PCR product which was pre-added and mixed with 2 µl of loading buffer
to its corresponding wells. Typical electrophoresis conditions ran at 400Am 100 volts for 30minutes using
BioRad power Pac basic electrophoresis power supply. All the PCR reactions were run on 1% agarose gel and
pictures were taken using gel picture camera system. The safety issues in gel electrophoresis were minimal
except the use of sybre safe stains which requires proper laboratory practices and safety procedures for disposal
of the used gel.

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2.6 DAPI (4', 6-diamidino-2-phenylindole)
DAPI staining was done to count the total population density, biodiversity of bacteria in samples by using
epifluorescence microscope, using the DAPI staining technique. Weighed 0.5g of soil sediment and dissolve
each in different volume of 1ml sterile distilled water and stand to set for 10minutes. Then transfer 0.5ml of
supernatant onto the centre of sterile filtered fluorochrome DAPI filter 0.2µm in the vacuum filter, fixed and
stains with a drop of DAPI staining solution (4', 6-diamidino-2-phenylindole) for 5 minutes at a concentration of
5μg/ml, then incubated at room temperature for 5munites. Fixed samples were filtered onto 0.2 μm black
polycarbonate membranes (Poretics, Livermore, CA, USA) with 8μm backing filter to improve cell distribution,
under a low vacuum (<50 mm Hg). Using Vacuum-filtration (~30 kPa), samples were wash four times with
sterilized wash buffer to remove excess stains. A pair of forceps was used to transfer filters throughout the
procedures to avoid contamination and not to destroy the filter papers. After the final wash, the filters were
transferred on to clean microscopy slide, a drop of immersion oil was added and covered with a cover slip.
Filters were not mounted but stained bacteria cells were counted using Leitz Labalux epifluorescence
microscope at 40X lens area of ~ 380.25µm2
equipped with a DAPI filter of 22mm (22000µm). The study uses
the ratio of 380.25/39940000 for calculation of the number of stained bacteria on a given slide read using the
formula (106
X cell count / sediment (g)) whiles the result were recorded in mean progressive method for 30
fields. That is average mean was calculated as reading progress for each sample.
WORD COUNT: 1493

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CHAPTER 3
RESULTS

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3. Results
The following section below outline results obtained from various experimental techniques carried out
to explore the biodiversity of sediment bacterial and organic compounds in acid mine pollution throughout the
research project.
3.1 Organic Compounds characterization
GC-MS was done to analyse sediments for presence of organic compounds and determine the level of acid
mines contamination and what their presence means for the environment. The observation in both upstream and
downstream sites reveals similarity of compounds found and analyse as most of them were long chain acid,
cyclic hydrocarbon, ring-hydrocarbon, long chain alcohol, long chain ester, phenol, methyl benzoate, phthalic
acid, boryl hexylester, fatty acid, methyl ester, hexaredioc acid, diocryl ester, methylene chloride. However, the
actual compound names were not analysed due to limited time to identify the different elements presences. The
number of compounds analysed in downstream were significantly higher than those analysed in the upstream,
meaning downstream sites were more contaminated than upstream. Retention time at 20.80 minutes was
persistently analysed in all sample and this means the identity of that sample is important to note as the highly
frequent abundance organic compound analysed in both sites. Threshold were set for relative abundance at <20,
20, >20<30, 30 and >30 for separation of all samples and the highest number of compound recorded for a single
threshold was U7 for RA above 30. Site D3 have compound analysed in all the five threshold followed by D2
with four thresholds, D1, D4, D5, D6 with three threshold , D8 and D10 analysed two threshold while the rest of
upstream sites recorded only one compound at one threshold each as can be seen in Figure 3.1.1 In order to
compare the upstream and downstream for level of contamination, we use the compound that was analysed in
all the sites at retention time 20.80 minutes using peak area (AA) and divide it by ratio of 1000. Base on that
scales, a triangular plots with different colour depiction was use to demonstrate the level of contamination at
20.80 RT as can be seen on appendix 6.1. In the result, downstream sites have the highest level of
contamination starting from the D1, D3, and D4 in that deceasing order to the last point of D11. Upstream from
site U1 to U6 all have equal level of contaminations, however U7 which was close to downstream sites reveals

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the lowest contamination so far although this could be attributed to its shifts of location to the right and none
closer to the stream exoduses as can be seen in appendix 6.1.
Figure 3.1.1: Number of compounds analysed for selected threshold at <20, 20, >20<30, 30 and >30
relative abundance. D7 shows the highest number of compounds at threshold >30 relative abundance and
none recorded for other thresholds below that level. D3 have compounds at all five thresholds and D2
have four compounds threshold results but less than 4 compounds analysed for each of them. All the
upstream sites indicate single compounds observation with one compound per threshold at each
individual different threshold indicating a less contamination in the upstream ofthe landfill.
Figure 3.1.2: The peak area at 20.80 (RT) was analysed in lmost all the 18 samples and there indicates a clear
sleepy increase of peak area from upstream towards downsstream upto D3 were a sweep shifts increase for
D2 and D1. This means compounds (AA) increases as the site becomes more contiminated and more
compounds analysed in the study. D1 – D6 were closest to upstream and exit point of streams with
significant values of contamination while D7 – D10 stand away from streams exits and almost the same
valueswih upstream. UpstreamU2 – U7 shows lesssignificantRA values.
0
1
2
3
4
5
6
7
8
D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 U1 U2 U3 U4 U5 U6 U7
numberofcompounds
sample ID
Amount of Compounds and relative abundance (RA) at different threshold
no. compounds <20 RA
no. compounds @ 20 RA
no. compounds>20 <30 RA
no. compounds @ 30 RA
no. compounds >30 RA
Key:
0
100000
200000
300000
400000
500000
600000
700000
D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 U2 U5 U6 U7
Peakarea(AA)
Sample ID
Peak Area (AA) at 20.80 Retention Time (RT)

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3.2 Inorganic Compounds characterization.
Contamination is a common phenomenon in water bodies and soil sediments in arctic regions due to domestic
activities, biological activities, tourism, and industrial discharge. In this study, eighteen samples were collected
from different sites (D1-D11 and U1- U7), 11 samples were selected and analysed by Martin (MSc student) in
2015 for 23 different elements using XRF methods. The total soluble Fe in the AMD-contaminated in U7 was
much higher than in D3. As in appendix 6.5 (analysed by Martin, MSc student), the chemical parameters of the
sediments analysed were differed significantly between upstream and downstream environments. D3 have
higher significant values of the following chemicals contaminations presence; uranium, stondium, barium,
praseodymium, calcium and magnesium far more than recorded in U7 site. Interestingly there is presence of
aluminium in all the sites tested.
From this data, there appear to be a number of potential variances as there are unexpected spikes in
concentrations of all the elements, only to reoccurrence to normal trend in later especially in D2. There is also a
noisy rise in concentrations of phosphorous and sulfur concentrations in downstream sites unlike the upstream
samples as U2 has a very low sulfur concentration. Change in this nature would be a direct effect from the acid
mine drainage in downstream, whereas upstream unaffected by the mine. It can also be observed that
concentration levels declines as the sampling site becomes far from the landfill stream although site D11
represent sometimes much higher than other sample locations for some elements, such as Manganese, Iron and
Zinc due to deposition accumulation.

22
Fig 3.2.1 Inorganic Compounds characterization of sediments
Figure 3.2.1 showing the concentration in parts per million (ppm) of 23 different elements detected by
XRF with high values of silicon, potassium, Cobalt and sulphur for all sample analysed from U2 –U7 and
D1- D11. U7 has higher value of aluminium than D3 and D3 also has significant higher value of
Strontium, sulfur than U7.
0
50
100
150
U2 U6 U7 D1 D2 D3 D4 D5 D6 D9 D10 D11
Concentration(ppm)
Sample Site
Co
As
Pr
Pt
Pb
U
0
1000
2000
3000
4000
5000
U2 U6 U7 D1 D2 D3 D4 D5 D6 D9 D10 D11
Concentration(ppm)
Sample Site
P
Cl
Cr
Mn
Zn
Sr
Ba
0
50000
100000
150000
200000
250000
300000
U2 U6 U7 D1 D2 D3 D4 D5 D6 D9 D10 D11
Concentration(ppm)
Sample Site
Si
Al
Fe
Ca
0
5000
10000
15000
20000
25000
30000
35000
U2 U6 U7 D1 D2 D3 D4 D5 D6 D9 D10 D11
Concentration(ppm)
Sample Site
Mg
S
Ti
K

23
The appearance of colony plate’s characteristics represents individual bacteria strains as shown in figure 3.3.1.
The study use morphological characterisation of culture colonies to analysed and observed the differences
between the two sites and significant differences were found as upstream sites which was isolated in more acidic
(pH 4) media has less number of bacteria growth or colonies forming unit with irregular shape and a dry texture
with a clear surface area than downstream isolated in relatively higher pH 8. From the culture agar plates, the
visible characteristics of different colonies noted differ in appearance as they were typically different bacterial
strains, species or genera. Morphology differences include shape, the margins or edges of the colony, the
colony’s opacity and surface features. The characteristic also include raise colonies with undulated margins,
circular and umbonate shape of upstream site samples. Downstream sample of D3 was sticky, mucoid, moist
and grow into the medium with a strong smell and have no definitive size as the colonies covered the whole
plate and opaque.
Figure 3.3.1: Culture plates of D3 (A and C) and U7 (B and D) shows differences in bacteria colony growth. A and B
represent (U7 and D3) as primary culture colonies while C and D were subcultures for U7 and D3 respectively. The
two colony plates have different texture as U7 was dry while D3 was sticky, mucoid, moist and growth into the
medium. The size of U7 was medium to large and D3 have no definitive size as the colonies covered the whole plate.
U7 is raised with undulated margin, circular and umbonate shape while D3 was flat, irregular in shape with lobate
margin. U7 was clear and D3 opaque.
A B
DC
Fig 3.3.1 Culture plate of D3 and U7 with bacteria coloniesaftera week

24
3.4 DAPI
After DAPI staining, microscopy and counting for D3 and U7 the stained bacteria with progressive mean
calculation show inconsistent for bacteria stain counting as seen below. Although counting were fluctuating for
both sites, bacteria abundance shows differences as upstream site records highest bacteria cells count of 54
billion/g of sediment compare to the downstream with highest record of 38 billion/g and the differences stand at
6 billion/g of sediment. Both sites correlate each other with patterns of bacteria abundance as the field count
progresses. Downstream (D3) have the lowest count of 16 billion cells while the upstream (U7) records its
lowest of 20 billion cells. However, the methodology for counting DAPI stain bacteria was difficult as this
process requires good experience microscopy. This indicates that acidity and contamination has effect on
bacteria abundance in acid mine exits sites.
Figure 3.4.1: Bacteria count of D3 and U7 showing difference in abundance as upstream records with
highest bacteria cells of 46 billion and downstream record highest of 38 billion have bacteria counts. D3
records lowest of 16 billoin whle U7 has 20 billion cells. This indicates that acidity and contamination has
negative effect on bacteria abundance in acid mine exits sites.
24 26
20
28
32
20
16 18
26
36
28
24
18 20 22
16
32 34
38
32
22
28
22
34
28
24
30
38
28
22
0
5
10
15
20
25
30
35
40
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Bacteriacount(inBillion)
Fieldcount 1-30
D3: DAPI stain bacteria count
44
22
36
54
48
30
24
32
36 38
44
22
26
36 34
30
40
26 28
34 36
26
22 20
26
32
46
40
32
24
0
10
20
30
40
50
60
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Bacteriacounts(in
Billion)
Field count 1-30
U7: DAPI stain bacteria count
B
A

25
3.5 Polymerase Chain Reaction (PCR) and 16s rRNA sequencing.
Colonies that successfully grown on D3 and U7 were labelled as from 1-21 and directly extracted in a master
mix for amplification of 16S DNA and run on gel electrophoresis for band separation as seen in below picture.
Figure 3.5.1 displays the amplicon bands on 1% agarose electrophoresis gel of the PCR product using 16s DNA
template. As the gel picture showing presences of bacteria species within sample sites analysed, number 1-11
identified as sample site D3 cultured under pH 8 and 12 and 13 identified as sample site U7 cultured under pH 4
and 18-21 identified site U7 under pH 10. The amplified 16s DNA were then cleaned up to remove any
unwanted excess leftover DNAs and reagent used in the procedure and were finally send for identification using
16s rRNA sequencing method. However at the time of this write up, the result of 16s RNA sequencing are yet
to be received and therefore appropriate identification of colonies could not be included in this report.
Figure 3.5.1. Gel picture of D3 and U7 with clear molecular bands based on size. Sample 1- 10 show
multiple bands including 13, 16,18,20 and 21 while 11, 12, 15, 17 and 19 shows single band. This indicates
significant difference between and within sites analysed. Number 1-11 identified as sample site D3
cultured under pH 8 and 12 and 13 identified as sample site U7 cultured under pH 4 and 18-21 identified
site U7 under pH 10
WORD COUNT: 1151

26
CHAPTER 4
DISCUSION
CONCLUSION
AND
FUTURE WORK

27
4. DISCUSION:
The following sections below outline the discussions of the project results to better understand the
scientific meanings of the findings in the project in relation to microbial diversity in acid mine sediment
contamination.
Studies have reveals that some bacteria taxa have intracellular pH levels close to neutral and therefore extreme
pH may impose significant stress at cellular level, however some bacteria tolerate better as Acidithiobacillus,
thioooxidans and Acidithiobacillus ferroxidase were isolated from acid mine drains and the authors believed
that is due to the bacteria’s adaptive ability to do best in low pH <4 environments (Valente et al., 2013). As
studies shown that bacterial community abundance and composition is strongly influenced by pH, this study
correlates with those results as the culture plates of D3 which was cultured on pH 8 shows significant higher
number of bacteria colonies growth than U7 isolated on pH 4. This means acidity has negative effect on the
growth and survival of bacteria in acid contaminated soils although acidithiobacillus ferrooxidans and
leptospirillum ferrooxidans as iron-oxidizing agents were isolated from such environments as in (Kuang et al.,
2013a). Therefore, our results strongly agree that soil bacterial community composition and diversity in arctic
environment is pH dependent but could also be determined by variation to other factors. In previous research
including (Baath and Kritzberg, 2015), environmental gradients of acid contamination have been observed in
landfill and coal mine sites and that structural variation and diversity of soil bacterial communities correlated
significantly with pH level. Therefore, bacteria abundance in extreme soil environmental is limited to selective
disadvantage of adaptation as soil characteristics, e.g., nutrient availability, cationic metal solubility, organic
characteristics, soil moisture and salinity are often directly or indirectly related to soil pH. Some bacteria and
other macro-elements do influence solubility of cations and increase soil acidity or neutralise soil. These
dependable outcomes were apparently supported by Kuang et al as bacterial in extreme environment survive
due to the resilient selective pressures in tremendously acidic soil that mostly determine which lineages can
survive leading to a situation of equilibrium pH level for growth among acidophilic species or even between

28
phylogenetically highly similar taxa as evidenced by 16S rRNA sequence comparison microorganisms isolated
from different acidic mining environments in ecological study (Kuang et al., 2013a).
4.2 DAPI Counting ofStain Bacteria
Parallel relationship between pH and bacteria abundance and richness is established in many studies and this
present study did correlate with those findings as seen on the DAPI count of higher bacteria count in
downstream sites of D3 with higher pH (neutral) compared to upstream U7 with lower pH (acidic). The
upstream U7 with pH 2.60 achieved less bacteria count in DAPI staining than D3 with pH 7.90, this strongly
support previous findings that pH influence bacteria growth, abundance in acidic environments irrespective of
geographical distance or regardless of distinct substrate types of sites as stated by (Kuang et al., 2013a). The
prime importance of soil pH as best predictor for control of soil bacterial community structure has been
demonstrated in papers including (Kuang et al., 2013f) and in particular recent studies have shown that bacterial
communities in soils from a broad range of ecosystems including China are strongly structured according to
variation in soil pH (Gong et al., 2015). These areas accommodate significant abundance of acidobacter phyla
as they are the predominantly phyla found in those acid environments (Gong et al., 2015). In Labuber, it was
mention that differences in other soil characteristics are as poor predictors of bacterial community structure
(Lauber et al., 2009), proposing that variation in soil organic matter chemistry, vegetation type and
environmental factors other than soil pH have relatively small impacts on the phylogenetic composition of soil
bacterial communities. However, (Tamames et al., 2010) reveals that salinity shape the ecological distribution
of prokaryotic taxa and therefore bacteria observed in D3 of this study could also constitute prokaryotic species
of bacteria. Nevertheless in the present study, the specific nature of the relationship may differ slightly between
upstream and downstream soils as the downstream D3 was dried of running surface water during sampling
which could have cause high pH level or neutralization.
4.3 Organic Compounds (GC-MS)
As mentioned in Song et al that the abundances of Bacteroidetes, Betaproteobacteria, and Acidobacteria were
also related to carbon availability in acidic soil (Song et al., 2015a), our study could have correlated with Song
et al when sequencing result had been received and analysed in relation to organic compounds identified. As

29
this study reveals that downstream have less bacteria count compare to upstream which correlate with high
organic compounds contaminations as in figure 3.1.1 above where the downstream show higher pollution. The
low bacteria presences in downstream could have been as a result of presence of organic compound especially
phenol contamination which are harmful for the environment, toxic to microorganisms and recognized as
carcinogenic compounds (Chen et al., 2016) or less carbon presence in downstream or selective advantage of
acidobacteria taxa and disadvantage of other phyla. As the apparent influence of pH makes it best predictor of
soil bacterial communities structure for acidobacteria and actinobacteria as reveal in Sait et al., however, the
abundances of bacteroidetes, betaproteobacteria, and acidobacteria were related to carbon availability as
firmicutes is dominant taxa for cellulose decomposition in landfills irrespective of location as reported in (Song
et al., 2015a) and this could be supported in this study when full 16s rRNA analysed. This is further supported
in other papers as proteobacterial taxa are not well correlated with pH, suggesting that the abundances of these
groups are predominantly influenced by factors other than pH. Although that was mention, our study reveal
significant different in contamination level when downstream compare to upstream as GC-MS results show a
very few number of analyzed compounds with low peak values among the upstream sites than downstream.
4.4 Inorganic Compounds
To a large extend, inorganic compound contaminated soil influence microorganism abundance and richness and
impact the soluble elements bioavailability to plants roots absorption and bacteria growth. The current study
shows presence of significant amount of inorganic elements that would affect both plant and microorganism’s
survival and adaptation in extreme environments. The paper reveal a significant difference in bacterial
abundance as inorganic compounds contamination shifts from upstream towards downstream with increase in
acidity. Similar to this study, landfill and other acidic environments unveils a shift in microbial richness and
abundance from the upstream to the downstream in relation to soil inorganic chemical abundance and
composition (Kabata-Pendias 2011). Presence of calcium is essential as bacteria use calcium for cell signalling,
interaction of cell wall, and normalising Ca2+
uptake and in this study, the X-Ray Fluorescence analysis show
calcium as the largest contaminant which may be due to low surface water to flush out the calcium further
downstream sites. Also calcium in bacteria cells are associated with a number of key cellular process, gene
expression, differentiation regulations and most importantly for stress signals like cold shock responses for

30
arctic bacteria (Gray et al., 2014). Therefore presence of calcium in current samples sites reveals it utility for
bacteria in the arctic region of extreme environment, however it is maintain that high level of calcium
contamination affect other bacteria species growth as mentioned in (Dang et al.,2014).
As reported in (Gray et al., 2014) that magnesium plays a vital role in bacterial cell replication and is normally
transported into cells by MgtA/B and MgtE transport proteins. It is also important in other metabolic functions
like cofactor in numerous enzymatic functions, influence on membrane stability, therefore low availability of
magnesium would lead to reduction in microbial growth. The present study shows an increase level of
magnesium largely in the downstream. The level of potassium is significantly dropped in downstream compare
to upstream, however it is apparent that greater percentage of soil potassium is unusable mineral or not available
for absorption (Zhang and Kong, 2014). As potassium in the downstream, it plays an essential role in bacterial
cells physiology including regulating cytoplasm pH and transmembrane electrical potential, therefore is vital for
internal pH regulation under acidic conditions.
Iron plays a very significant role in bacterial cell functions, such as DNA replication, oxygen transport and
oxidative stress protection (Skaar, 2010), however it can vary depending on environment nutrition. This is
correlated in this result, as downstream site iron levels fall significantly and this may be due to presence of iron
chelating agents in the landfill such as deferoxamine, ethylenediaminetetraacetic acid (EDTA) which retrieve
iron and makes them less biologically available to bacteria that exhibited iron oxidase and oxygen reductase
activities (Roger et al., 2012). Normally Iron levels in Landfill site with coal mine contaminations are high due
to strong influence of iron dissolution, oxidation and movement of surface running water. Therefore, inadequate
iron in an environment would also cause the bacteria to acclimatized itself to integrate more iron into the cell as
soluble ferric iron (Fe2+
) or ferric oxides (Fe3+
). (Cheng et al., 2011) reveals that rapid oxidation of Fe(II) and
subsequent precipitation of Fe(III) at neutral pH removed dissolved Fe from the water body which is correlated
in this result as downstream has lower Fe level and can consequently influence the bacteria ecosystem. Metal
bioavailability in acidic environments sometimes depends on interactions between various elements in soil as
reported in Kabata that calcium (Ca), phosphorus (P) and magnesium (Mg) are the main elements affecting
absorption and metabolism of several trace elements (Kabata-Pendias 2011) and also reveals that aluminium can
interfere with nutrient uptake (Goron and Raizada, 2014).

31
This paper reveals high values of silicon, potassium, Cobalt and sulfur for all sample analysed, although U7 has
higher value of aluminium than D3, but D3 has significant higher value of strontium, sulfur than U7. This
means there is high contamination and active biodegradation process taken place on the landfill as much of the
sulphur contents were runoff from upstream towards downstream within effluent of surface water. Studies
reveals that pH neutralised with distance downstream due to the influx of alkaline groundwater and tributary
flows (Williams et al., 2015) and the current data concord with that finding. Although aluminium metal can be
toxic at higher levels as reported by (Gadd, 2010), however it does not show usage in molecular activity in cells.
It is also a key gauge on soil acidity level as it causes drop in soil pH and Al3+
ions become more soluble leading
to aluminium toxicity in the environments with binding effect to the bacterial cell wall which cause inhibition of
growth in low pH and cause inhibition of electron transport chain (Carrero et al., 2015). Studies reveals that
mobility of aluminium in low-temperature environments is generally very limited due low solubility (Acero et
al., 2015). Presence of carboxylic acids in this study means anaerobic degradation, acid fermentation and
decreasing pH which makes the overall environment more acidic.
4.5 PCR and 16S rRNA sequencing
Extreme environment accommodate significant diversities of microorganism based on adaptation mechanism
(Dhakar and Pandey, 2016), however not much is understood about their pattern of distribution and factors that
causes distribution scales. Generally, it would be hypothesized that the bacteria biodiversity in the soil
sediments would be the same regardless of the distances between locations. Many research including (Kuang et
al., 2013a) explore bacteria biodiversity using 16S rRNA pyrosequencing technology on samples of different
physical and geochemically affected acid mine contaminations and end up with astonishing result as
environmental factors like pH being the main predictor for community differences. This means microbial
diversity assessments, as well as phylogenetic diversity and richness were chiefly associated with pH gradient.
Likewise, pH further strongly correlate with relative lineage abundance as Betaproteobacteria habitually
associated with (Ferrovum genus) were explicitly surviving taxa under moderate pH (neutral) conditions, while
acidophilic microorganisms, Alphaproteobacteria, Euryarchaeota, Gammaproteobacteria and Nitrospira
unveiled a strong adaptation to more acidic environments, regardless of the distance and the distinct substrate

32
types. To establish those facts, we applied a massively parallel tag pyrosequencing of the V4 region of the 16S
rRNA gene to examine in-depth microbial communities from acid mine sites of upstream and downstream by
amplifying, purifying 18 different culture colonies from mainly two plates of D3 and U7 for 16s DNA PCR
products and send them for sequencing to identify individual strains. Due to time factor, the result of sequencing
result were not received and therefore not analysed in this project, however the paper believe that bacteria
richness and abundance will be highly reliant on soil pH.
Word Count: 2075
4.6 CONCLUSION
The findings in this study shows organic compound concentrations notably increasing as the sampling sites
shifts from mid-upstream towards the central downstream. The author concluded that contamination from both
organic and inorganic compounds discovered were higher in the downstreams than the upstreams and could be a
factor that gauge for bacteria biodiversity, abundance and growth in extreme environments. However, as both
DAPI and culture isolation show correlation of signifance bacteria abundance in high pH and less bacteria count
in low pH, therefore the paper concludes that pH is strong a predictor dynamic for bacteria abundance and
species biodiversity in ecosystem. Although this study did not investigated the overall microbial diversity and
did not received the 16S rRNA sequencing for species identification of selected samples, it is presumed that the
bacteria communities would be of those that are mostly acid-responding, hydrocarbon-responding, benzoate-
utilizing, denitrifying bacteria, phenanthrenedegrading bacteria, naphthalene-degrading bacteria and
sulfatereducing bacteria as those were the compounds found in the sediments analysed. Collectively, this results
suggested that microbial diversity and species richness patterns are better predicted by soil pH levels or
variation due to organic or inorganic compounds rather than physical distance in extreme acid mine
contamination in existing environment.
WORD COUNT: 198

33
4. 7 FUTURE WORK
The project certainly widen my knowledge in laboratory research and analytical skills, however if given the
opportunity, I would further analyse both the organic and inorganic compounds to identify individual compound
and quantified their concentration per gram of sediments. That will expose me to new different procedural and
analytical approach and interpretations. Also I would continue different bacterial isolation approaches using
diverse nutrients media at various pH levels under different temperature. Further to that I would do liquid media
isolation in serial dilution techniques and expand more culture-independent methods to fully phyla-structure all
acquired samples for bacteria identification and establish best experimentation method for culturing sediments
from extreme environment. As the samples analysed here were small in size and were subjected to freeze and
thawed on several occasion, I would love to analysed a bigger sample size to invesigate effect of intermittent
freezing and thawing on bacterial cells living in extreme environment of arctic cold regions. This will help in
understanding the general effect of global warming on the lives in Polar Regions and globally in general.
WORD COUNT: 177
FINAL WORD COUNT: 7232

34
CHAPTER 5
REFERENCES

35
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Final Year Dissertation 26. April. 2016

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