Final Biological Science Research Project BHS012-3 (1)

Biological Science Research Project: BHS012-3 Benjamin Cordner

The Laboratory Report

Investigating the Effect of Temperature on the Assembly of Microbial Communities.

Abstract:

The purpose of this research was to see how temperature effects different organisms at 5 degree Celsius (°C) intervals. It examines bacteria by microscopically viewing and recording changes to population density in a microcosm that has been held for a period of time at a constant temperature (15, 20, 25°C). There were two groups of researchers looking at a variety of monocultures and bacterial communities. Measurements were notated using their sizes and movements for identification. As the eukaryotes differed in size, a variety of methods were employed to observe and record results, serial dilution, spectrophotometer and PCR. The results were tabulated and compared. The results from this study were considered in the context of the literature available within this scientific field. This study asks the question: what is the effect of temperature on organisms such as pseudomonas fluorescens? Is it possible to discover their optimum temperature and to note how, in bacterial communities, they react to one another? Pseudomonas fluorescens results were inconclusive due to being out compete by other organisms in the community. Results still showed a major change in population size due to temperature variation. In conclusion the change in environmental temperature will have a impact on the ecosystem.

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Introduction:

There have been progressive evidence suggesting the need to move towards further research investigating the impact of environmental warming. Climate changes effects ecosystems in many ways that are only beginning to be understood. The rise in temperature is particularly worrying, not just because it forces species migration to aid survival, but because of the impact it is having on every level of species, including micro-organisms such as the commonly found Pseudomonas fluorescens. It is important to understand how temperature changes might effect such organisms and thus effect the humans. Studies such as those which will be considered in the discussion to this research highlight how Pseudomonas fluorescens may be changing in how it reacts to the human respiratory system. It will be noted how it is particularly responsive to temperature changes and thus research is necessary to look, not only at how it responses as a monoculture, but how it may react as part of a bacterial community.

Climate changes and environmental warming impact the entire biological community therefore it is important to consider changes with one part of the system in relation to how this also impacts the whole system. Evidence of this is shown in a study by Naidu et al (2015) which notes that in addition to the decrease in rainfall over the last decade in India, there has also been an increase in temperature and wind, all of which have worked together to dramatically decrease the moisture of the soil. This in turn has an impact on the ecosystem which depends on the soil and thus all that survives in the area will be effected. In a similar fashion studies such as those by Ferrarini et al (2014) have noted that climate change may be causing more complex issues within the plant kingdom than has previously been considered. Evidence such as that provided from studies into climate changes and environmental warming would suggest that research into the ways in which temperature increases impact organisms is of vital importance to understanding what may be expected in the future.

This study examines a variety of organisms, but focuses mainly on Pseudomonas fluorescens, which will be shown to be reactive to temperature changes (see results and discussion). Pseudomonas fluorescens are rod-shaped bacteria commonly found in soil and water, but also present in air, dust and vegetables. It is common to also find it in food products such as meat, fish, eggs, and particularly milk products. Its optimum temperature for growth is 25-30 degrees Celsius and it proves to have a low generation time at low temperatures and spoils at 2-5 degrees. This is important for considering how to treat and store water, vegetables and food products. For example, although milk is sterilised at high temperatures which degenerate bacterial including Pseudomonas fluorescens, they can be re-introduced after the processing and lead to the spoiling of the milk or milk-based product particularly if it is not stored continuously at a temperature just above freezing (Decoin, 2015).

Pseudomonas fluorescens is an obligate aerobe which can use oxygen rather than nitrate during its cellular respiration. It is a nonsaccarolytic bacteria that can produce heat stable lipase and protase, It can break down casein in milk and coagulate proteins, which therefore make it useful in the production of yogurts. Pseudomonas fluorescens is not usually found to cause infections in humans however, as opportunistic pathogens, it can cause infections in individuals with a debilitated or

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compromised immune system and recent reports have found Pseudomonas fluorescens in pneumonia cases. It has also however been found to protect plant roots against fungus and can be cultured to help with the treatment of skin and eye disorders. Pseudomonas fluorescens is the target organism used in this study therefore monocultures have been used throughout this experiment in temperatures varying 15-25°C over the course of the research period.

Polymerase chain reaction (PCR) is a technique that is used to amplify trace amounts of DNA located in or on almost any liquid or surface. As every human, animal, plant, parasite, bacterium, or virus contains genetic material such as DNA sequences that are unique to their species. PCR is a method used to amplify (make many more identical copies) these unique sequences so they can then be used to determine with a very high probability the identity of the source (a specific person, animal, or pathogenic organism) of the trace DNA or RNA found in or on almost any sample of material. (Bartlett et al).

Gel Electrophoresis is a method used to separate and analyse macromolecules (DNA, RNA and proteins) and their fragments, due to their size and charge. This is because DNA has a negative charge and the gel uses positive charge to attract the fragments. Smaller fragments will move further as there is less friction from the gel and that they have a lighter weight than larger fragments. It utilises a matrix of agarose or other substances (Nicholas and Nelson, 2013).

The aim of this experiment is to consider the growth of bacterial communities and how they compete and interact over a prolonged period. Results will be analysed according to markers such as the size of the populations, and how they may respond in a pre-predator relationship according to environmental influences such as temperature and how it responds over time.

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Method:

Six species of bacteria and five protists (3 ciliates and 2 flagellates) were cultured from a variety of sources. Microcosms were created using 50mL centrifuge Falcon tubes. Each tube was developed into a microcosm by adding 0.5g of freeze-dried alga or Chlorella powder to 1 litre of mineral water, which was then sterilised by autoclaving at 121 Celsius. Tubes were sequentially labelled for individual identification with the follow information: temperature, name (or initials of researcher), protist community, bacterial community (or bacteria monoculture) and replicate number, e.g. 15-NW-PC-1.Bacterial cultures were added to create two communities, A and B. Group A included Bacillus Subtilis, E-Coli and micrococcus luteus. Group B had Pseudomonas fluorescens, Serratia marcescens and Bacillus Cereus. Either A or B were added to 9 microcosms depending on which mixture the target species was present in. One half of the group made 3 falcon tubes with a monoculture of their organism. The other half of the group created a bacterial community of their group in 3 falcon tubes.

This experiment created 9 microcosms by adding 20mL of Pseudomonas fluorescens (a monoculture) from Group B using a serological pipette. The chosen protists were then also added to microcosms using a serological pipette: 10ml of Chilomonas, 100ml of Colpidium and 200ml of P. caudatum. Different amounts were added due to the difference in the population size; those with a smaller population required a larger amount. (See Figure 1) These 3 were chosen because they compete with each other and can be more easily measured due to their difference in size. Chilomonas is small but with a very large population which is visible under the dissecting microscope. Colpidium are also small but have a small population so more was added to give a similar population as Chilomonas. P. caudatum is a larger organism but has a smaller population than the other organisms per volume, therefore a larger volume was needed to match the population levels of the other organisms.

Bacteria mixture Protists (ul) Pseudomonas fluorescens 20,000 Serratia marcescens 20,000 Bacillus cereus 20,000 Chilomonas 10 Colpidium 100 P. caudatum 200 Figure 1: showing the population sizes

All 12 tubes were then placed into a polystyrene rack which was labelled with a specific temperature and put for 3 days into an incubator that had been set at the required temperature. In this case the Pseudomonas fluorescens was tested at 15, 20 and 25 degrees Celsius. The expectation was that Pseudomonas fluorescens would develop different levels of growth at different temperatures depending on its optimum temperature for growth.

Other members of the group who had bacterial communities looked at how the communities of 3 bacteria (A or B) reacted at the 3 different temperatures. The results were measured according to the competition of resources or even consumption of

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other bacteria. Those at an optimum temperature could be seen to thrive and out-compete the others at different temperatures. However the expectation was also that they could all have an ideal temperature and co-exist together.

Populations of species were sampled over four different sessions using a variety of techniques appropriate to the different sizes of the species, which reached different population abundance in their microcosms. Depending on size the bacteria was sampled using serial dilution, spectrophotometry and PCR. The eukaryotes (ciliates and flagellates) were sampled using different powered microscopic lens. The four parts to the sampling involved: counting the number of eukaryotes in a specific volume of liquid; calculating the bacterial absorbency of light to estimate bacterial abundance; preparing the sample for the following week and serial dilution of the bacteria.

The volume of the sample was variable depending on the species as there had to be between 20-100 individual eukaryotes to be able to make an accurate result. To avoid effecting the temperature of the microcosms, sampling was done as quickly as possible. This involved placing 1 ml sample in a curette, leaving for 15 minutes to settle, then viewing under the dissecting microscope to estimate the number of the species. Large numbers required taking a smaller sample to reach below 100 per count. The media was then mixed to ensure a representative sample of perhaps 0.2 ml of the original sample, which was mixed with 6-9 droplets of water (depending on size) on a Petri dish.

Sample Number

Temperature (°C)

Replica Number or culture

1 15 12 15 23 15 34 15 monoculture5 20 16 20 27 20 38 20 monoculture9 25 110 25 211 25 312 25 monoculture

Figure 2: Order of Samples. Showing how they were pipetted into the curette. A blank of 1 ml water was also used.

There were 12 curettes and 12 measurements in total (see Figure 2 for labelling system). Measurements were taken using a blank spectrophotometer (with the clear side, arrow pointing left to right, used for correct absorbency levels) against the water and measuring at 6000nm. After these results had been recorded 1ml of each sample was pipetted into an eppendorf tube and labelled with initials and sample number.

Next the samples were put into a centrifugal tube and spun at 14,800rpm for 1 minute to remove all the bacteria, and leaving a pellet in the bottom. The sample liquid was then pipetted back into the curette leaving the pellet behind in the tube. This gave

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optical density before and after. After the sample settled (15mins) absorbency levels were measured as before. Measurements were calculated to 1 ml. A record was made of the volume of the sample against the number of individuals in each species. For the smaller organisms a haemocytometer was used for counting under a powerful microscope. The haemocytometer grid was divided into counting squares and live cells in one corner square (0.1x0.1x0.01cm) were counted and added to obtain a cell count between 20-100.

Next a set of serial dilutions were created by adding 180ul of water into a 12x6 microtiterplate. The samples were pipetted onto agar plates beginning with number 1 through to 12 (see Figure 3). An X was marked on each plate on the same place or grid. Each agar was labelled with name, date and plate number. Serial solutions make it possible to see how many bacteria there are in a sample.

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Results:

The results for this experiment are calculated by counting the number of eukaryotes of each microcosm. After viewing under a dissecting microscope to find an appropriate volume depending on population size. A haemocytometer was used for high populations to calculate the amount that would be in 1 ml.The results from the experiments are shown in the following tables. The tables were created from results taken over the course of the experiment using sampling and PCR. Note that day 1 was mainly setting up the sample and preparation.When measuring the samples, notes were taken of changes to colour as this was an indicator of the changes to the different cultures. The colours of the different cultures were checked after mixing in the falcon tube and all were a cloudy green. The 3 monocultures however were clearer than the 9 other tubes. This suggested that there had been less growth in the monocultures when compared to the 9 mixtures of organisms. Tables numbered 1 to 3 shows the absorbency levels of all 12 samples which was obtained using a spectrophotometer. There are two sets of results for absorbency levels; before centrifuging and after centrifuging. The results taken before centrifuging showed the light absorbed by everything present in each sample. By centrifuging some of each sample, the larger organisms and debris were removed.The reason for taking two different sample absorbance levels is to give a clearer accuracy in the end results by taking the after results away from the before. Table 4 complies the results across the 3 days, (shown in Tables 1-3). It shows the calculated absorbance levels, which were obtained by taking away the result after centrifuging from the result before centrifuging. This allows for easier comparisons between the 3 days of results and will give a calculated absorbency level that is more precise.The sample numbers shown throughout the experiment (e.g. in Table 1) refer to the cultures that were created using the micro-organisms and bacteria shown in Figure 1. The breakdown of this is shown in Figure 2.

Absorbance levels

Sample number

Before centrifuge

After centrifuge

1 0.168 0.0422 0.168 0.0233 0.153 0.0234 0.369 0.045 0.229 0.046 0.268 0.0347 0.233 0.0248 0.215 0.0299 0.186 0.03

10 0.304 0.02211 0.261 0.02712 0.154 0.02

Table 1: Absorbance levels from day 1 taken before and after centrifuging.

Absorbance levels

Sample number

Before centrifuge

After centrifuge

1 0.23 0.042 0.163 0.0243 0.143 0.0374 0.358 0.0295 0.138 0.036 0.183 0.037 0.114 0.0148 0.17 0.0259 0.075 0.025

10 0.085 0.02511 0.065 0.02612 0.185 0.026


Absorbance levels

Sample number

Before centrifuge

After centrifuge

1 0.24 0.0712 0.164 0.0763 0.152 0.074 0.428 0.0995 0.124 0.0576 0.213 0.057 0.136 0.0688 0.226 0.0159 0.129 0.01

10 0.14 0.06611 0.127 0.0312 0.333 0.046


Table 4 below shows the calculations for all 3 of the different sets of above results. Note that day 1 calculations are shown in the first column beside their sample number. This demonstrates how the calculations were obtained. The end result is obtained by minus-ing the results of the absorbency level after centrifuging from the absorbency level before centrifuging. The results of this are shown in the remaining 3 columns.By creating this table it is possible to have a more accessible comparison of the 3 sets of results. This can be seen more clearly in the graph created from table 4 data (graph 1).

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Calculated Absorbance levels

Sample number

Day 1 calculation

Day 1 results

Day 2 results

Day 3 results

1 0.168 - 0.042 = 0.126 0.19 0.1692 0.168 - 0.023 = 0.145 0.139 0.0933 0.053 - 0.023 = 0.145 0.106 0.0824 0.369 - 0.04 = 0.329 0.329 0.3295 0.229 - 0.04 = 0.189 0.108 0.0676 0.268 - 0.034 = 0.234 0.153 0.1637 0.233 - 0.024 = 0.209 0.1 0.0688 0.215 - 0.029 = 0.186 0.145 0.2119 0.186 - 0.013 = 0.156 0.05 0.119

10 0.304 - 0.022 = 0.282 0.06 0.13411 0.261 - 0.027 = 0.234 0.039 0.09712 0.154 -0.02 -= 0.134 0.059 0.287

Table 4: Calculated Absorbance levels from days 1-3 including calculations from day 1 absorbance level data using before centrifuge minus after centrifuge.

Graph showing calculated absorbance of all data

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0.05

0.1

0.15

0.2

0.25

0.3

0.35

1 2 3 4 5 6 7 8 9 10 11 12

Sample number

Calcu

late

d ab

sorb

ance

leve

ls

Day 1 results

Day 2 results

Day 3 results

Graph 1: Calculated Absorbance Levels of all 12 samples from days 1-3.

The data in graph 1 give a clear visual comparison of the difference in results over the 3 days of absorbance levels. The difference in the polycultures and the monocultures can be noted when reviewing sample number 4, 8 and 12.

To enable a more reliable result, the average calculated absorbance levels of the 3 replica samples (not the monoculture) from each temperature on days 1-3, were used (as seen below in tables 5).

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Average calculated Absorbance levelsTemperature (°C)

Day 1 results

Day 2 results

Day 3 results

15 0.138666667 0.145 0.11466666720 0.210666667 0.120333333 0.09933333325 0.224 0.049666667 0.116666667

Table 5: The average calculated Absorbance levels of each temperature on days 1-3.

The data below in table 6 shows the standard deviations of the average calculated absorbance levels (shown in table 5).

Standard deviation of the average calculated absorbance levels

Temperature (°C)

Day 1 results

Day 2 results

Day 3 results

15 0.010969655 0.042320208 0.04737439520 0.022546249 0.028571548 0.05513921825 0.063592452 0.010503968 0.018610033

Table 6: The Standard deviation of each average calculated absorbance level.

Using both table 5 and 6 a graph can be made to give a more clear representation of the results and demonstrate the standard deviation using error bars. This can be seen in graph 2 which also can be useful when comparing the increase and decrease of average absorbance over time.

Graph 2: Average calculated absorbance levels of each temperature on days 1-3 including standard deviation error bars.

Tables 7 through to 10 below are the results from all 4 days of sampling. They show the effect of the different temperatures (15, 20, 25°C), on 3 different species (P. caudatum, Colpidium, Chilomonas).

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On Day 1 of the experiment samples containing each organism were viewed under a microscope to allow for familiarity in shape, movement, size and colour. Notes were taken so that descriptions were available of each eukaryote. This enabled the recognition of the various organisms in subsequent microscopic analysis.

The next stage of the experiment involved counting the eukaryotes (P. caudatum, Colpidium, Chilomonas) using a stage microscopes and a dissecting microscope. The bacteria could not be counted this was as they were too small to be seen using these microscopes. In order to do this a 1000 ul sample was taken from each falcon tube and viewed microscopically and the number of each organism were counted. Some of the 1000 ul samples had too many to count so a smaller volume had to be taken until the number was low enough to count. This number was then calculated to the estimated number present in 1000uls as shown below in Tables 7-10.

Date: 12.01.15

Temperature(°C)

Sample No. Species

Volume Sampled (ul)

Number Counted

Number Calculated to Vol. of 1000 ul

15 1 P. caudatum 1000 10 1015 2 P. caudatum 1000 0 015 3 P. caudatum 1000 1 120 1 P. caudatum 1000 24 2420 2 P. caudatum 1000 3 320 3 P. caudatum 1000 8 825 1 P. caudatum 1000 50 5025 2 P. caudatum 1000 3 325 3 P. caudatum 1000 4 415 1 Colpidium 10 26 260015 2 Colpidium 10 26 260015 3 Colpidium 10 22 220020 1 Colpidium 5 30 600020 2 Colpidium 5 32 640020 3 Colpidium 5 25 500025 1 Colpidium 5 20 400025 2 Colpidium 5 40 800025 3 Colpidium 5 32 640015 1 Chilomonas 20 20 100015 2 Chilomonas 20 25 125015 3 Chilomonas 20 22 110020 1 Chilomonas 10 21 210020 2 Chilomonas 10 23 230020 3 Chilomonas 10 26 260025 1 Chilomonas 5 31 6200

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25 2 Chilomonas 5 36 720025 3 Chilomonas 5 42 8400

Table 7: Cell count results on day 1 calculated to 1000ul.

As you can see in the above table there weren’t as many P. caudatum in the first sampling, at each of the different temperatures, but many more in the other replicates at 1000ul.

All of the above microcosm populations are seen to increase at a higher temperature suggesting that their ideal temperature is 25°C or higher.

Date: 14.01.15

Temperature(°C)

Sample No. Species

Volume Sampled (ul)

Number Counted

Number Calculatedto Vol. of 1000ul

15 1 P. caudatum 1000 12 1215 1 Colpidium 2 35 1750015 1 Chilomonas 50 21 42015 2 P. caudatum 1000 8 815 2 Colpidium 2 16 800015 2 Chilomonas 50 26 52015 3 P. caudatum 1000 6 615 3 Colpidium 2 18 900015 3 Chilomonas 20 21 105020 1 P. caudatum 200 10 5020 1 Colpidium 2 19 950020 1 Chilomonas 2 25 125020 2 P. caudatum 1000 9 920 2 Colpidium 2 19 950020 2 Chilomonas 20 25 125020 3 P. caudatum 1000 5 520 3 Colpidium 2 12 600020 3 Chilomonas 1000 0 025 1 P. caudatum 200 11 1125 1 Colpidium 2 36 1800025 1 Chilomonas 10 29 290025 2 P. caudatum 1000 0 025 2 Colpidium 2 24 1200025 2 Chilomonas 2 31 1550025 3 P. caudatum 1000 0 025 3 Colpidium 10 19 190025 3 Chilomonas 2 33 16500


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Date: 16.01.15

Temperature (°C)

Sample No. Species

Volume sampled (ul)

Number Counted

Number Calculated to Vol. of 1000ul

15 1 P. caudatum 1000 68 6815 1 Colpidium 1 36 3600015 1 Chilomonas 2 14 700015 2 P. caudatum 1000 22 2215 2 Colpidium 2 14 700015 2 Chilomonas 10 8 80015 3 P. caudatum 1000 9 915 3 Colpidium 1 14 1400015 3 Chilomonas 10 7 70020 1 P. caudatum 1000 32 3220 1 Colpidium 1 11 1100020 1 Chilomonas 10 7 70020 2 P. caudatum 1000 43 4320 2 Colpidium 1 15 1500020 2 Chilomonas 1000 0 020 3 P. caudatum 1000 12 1220 3 Colpidium 1 28 2800020 3 Chilomonas 1000 0 025 1 P. caudatum 1000 37 3725 1 Colpidium 10 35 350025 1 Chilomonas 2 24 1200025 2 P. caudatum 1000 0 025 2 Colpidium 2 8 400025 2 Chilomonas 2 11 550025 3 P. caudatum 1000 0 025 3 Colpidium 10 28 280025 3 Chilomonas 1 15 15000


The above Tables 5-7 show a variety of results which would suggest there may be some anomalies. The data shown below in Table 8 does not include many samples but focuses instead on the specific samples to view their differentiation.

Date: 19.01.15

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Temperature (°C)

Sample No. Species

Volume sampled (ul)

Number Counted

Number Calculatedto Vol. of 1000ul

15 1 P. caudatum 1000 1615 1 Colpidium 15 1 Chilomonas 15 2 P. caudatum 1000 1615 2 Colpidium 15 2 Chilomonas 15 3 P. caudatum 1000 815 3 Colpidium 15 3 Chilomonas 20 1 P. caudatum 20 1 Colpidium 20 1 Chilomonas 20 2 P. caudatum 20 2 Colpidium 20 2 Chilomonas 1000 020 3 P. caudatum 1000 920 3 Colpidium 20 3 Chilomonas 1000 025 1 P. caudatum 25 1 Colpidium 25 1 Chilomonas 25 2 P. caudatum 1000 025 2 Colpidium 25 2 Chilomonas 25 3 P. caudatum 1000 025 3 Colpidium 25 3 Chilomonas


Below are the tables showing results taken from the Petri dishes all of which were kept at 30°C for 16 hours (these can be seen in the appendix, image 1-3, with related information in figure 4-5). The time between sampling and recording results explains why they have different dates, one being the date they were sampled and the other the date they were counted. Before the results were recorded the samples were examined and growth could be seen by the red and white cultures, which showed a smaller colony count for each dilution.

Tables 11 to 13, in a similar to fashion to the above tables, show the results taken over 3 days from samples kept at 3 different temperatures and how these effect the 3 different samples and the monoculture (sampling as from Figure 2). Each sample was recorded from 6 different dilutions ranging from strong (1in 10) to weak (1 in 1,000 000).

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Date:12.01.15

Serial dilution

Temp. (°C)

Sample No.

Strong - 1 (1/10)

2 (1/100)

3 (1/1000)

4 (1/100000)

5 (1/100000)

Weak - 6 (1/1000000)

15 PC - 1 TMTC TMTC 11 4 4 315 PC - 2 TMTC TMTC 10 5 5 315 PC - 3 TMTC TMTC 5 3 7 315 MC - 1 TMTC TMTC 55 2 0 020 PC - 1 TMTC 6 0 2 2 020 PC - 2 TMTC TMTC 2 2 0 120 PC - 3 TMTC 14 2 2 1 020 MC - 1 TMTC 0 0 0 0 025 PC - 1 TMTC 12 0 0 1 025 PC - 2 TMTC 9 0 0 2 025 PC - 3 TMTC 12 2 0 0 225 MC - 1 TMTC 0 0 0 0 0

Table 11: Culture colony results from Petri dish counted on day 2(sampled on day 1).

Date:14.01.15

Serial dilution

Temp.(°C )

Sample No.

Strong - 1 (1/10)

2(1/100)

3 (1/1000)

4 (1/100000)

5 (1/100000)

Weak - 6(1/1000000)

15 PC - 1 TMTC 24 6 3 1 015 PC - 2 TMTC 6 2 1 0 015 PC - 3 TMTC 5 1 0 0 115 MC - 1 TMTC TMTC TMTC 28 14 920 PC - 1 TMTC 14 3 1 0 020 PC - 2 TMTC 6 4 0 0 020 PC - 3 TMTC 6 6 1 0 020 MC - 1 TMTC TMTC TMTC 34 12 825 PC - 1 TMTC 8 3 0 0 025 PC - 2 TMTC 6 3 1 0 025 PC - 3 TMTC 9 1 0 1 025 MC - 1 TMTC TMTC TMTC 22 6 4


Date:16.01.15

Serial dilution

Temp. Sample Strong - 1 2 3 4 5 Weak - 6

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(°C) No. (1/10) (1/100)

(1/1000)

(1/100000) (1/100000) (1/1000000)

15 PC - 1 TMTC TMTC 45 2 1 015 PC - 2 TMTC TMTC 18 2 1 015 PC - 3 TMTC TMTC 11 1 0 015 MC - 1 TMTC TMTC TMTC 21 2 020 PC - 1 TMTC 10 1 0 0 020 PC - 2 TMTC 19 2 0 0 020 PC - 3 TMTC 17 2 0 0 020 MC - 1 TMTC TMTC TMTC 8 1 025 PC - 1 TMTC 10 0 1 0 025 PC - 2 TMTC 9 4 0 0 025 PC - 3 TMTC 18 5 0 0 025 MC - 1 TMTC 29 3 0 0 0


Polymerised Chain Reaction (PCR) was used during week 2 to determine the micro-organisms present in each sample. This was done using primers that were designed at a previous bioinformatics session. In order to collect data from PCR reactions using the cultures from this experiment it was necessary to first test if the primers worked with the target organism. This was done by testing the primers with a control sample known to contain the target organism. This was done using gel electrophoresis after PCR and viewing the gel under UV light to see the florescent markers as bands that had moved due to the charge,This data can be seen in image 4 which showed bands for the second primer that was developed during bioinformatics. the band was around 700kb which is correct as the target size that was provided stated it to be 650kb.The results also showed that there were no other bands for the other organisms in the mix used (serratia or B.subtilus), thus no cross reactivity will occur for primer pair 2.

Primer pair 2 was then used in the PCR and electrophoresis with a control these samples:

Sample Tempurature (°C) Weight of supernatent (mg

1 15 412 15 273 15 381 20 102 20 553 20 56Table 14: PCR samples used with the weight of the supernatant.

A gel electrophoresis was used and the results are shown on image 5 in the appendix. The control had worked suggesting the sample and procedure had been performed correctly however no P.flurecence was detected in any of the sample. This was tested for a second time with the same outcome suggesting that most or all of the

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P.flurecence has been eaten or out compete by the other organisms on day 3 at temperatures 15 and 20 degrees Celsius.

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Discussion:

The above results suggest that temperature variations had a marked effect on the organisms viewed in this study over the duration of the study. This effect has been particularly pronounced for Pseudomonas fluorescens, other researched from studies shown below have considered how it might respond to temperature changes.

An early study by Gill (1975) considered how environmental factors such as chemical changes and physical properties could effect the growth of Pseudomonas fluorescens. Gill suggested that batch cultures were an important method for measuring variations in the organism as they allowed for several parameters to be changed simultaneously. When Pseudomonas fluorescens was subjected to various temperatures it was proven that this had a marked effect on its growth. It was also noted that the degree of saturation was not a continuous curve over the scale of the temperatures. At 10 degrees Celsius Pseudomonas fluorescens saturation variations decreased, which was supposed to be due to a decrease in the ability to control fatty acids. Once the temperature was lowered to below 10 degrees however there were few further changes. Gill concluded that Pseudomonas fluorescens controlled its fatty acid composition in the lower third of the temperature range (i.e. below 10°C) to allow for a constant saturation. Gill also noted that other factors, such as changing the growth-limiting substrate from carbon to nitrogen, had a marked enhancement to these changes. Fouchard et al (2013) study on Phospholipid fatty acids (PLFA) considers how experiments which measure fatty acid changes are particularly useful ways of noting bacterial growth. PLFA are found in cell membranes, which make direct contact with the cells environment and therefore signal changes to variants such as pH and temperature changes. Fouchard et al notes how Pseudomonas fluorescens is highly versatile as it uses a variety of nutrients, therefore it can be used in a broad range of growth conditions. In this experiment 2 different strains of Pseudomonas fluorescens (SF1 and DSM 7155) were grown at 3 different temperatures (16, 26 and 36°C) before optical density was measured (using similar techniques to this research) and cell multiplication results were analysed. In the discussion of their results they note how certain Pseudomonas fluorescens strains ( in this case DSM 7155) did not produce UV visible spectra and therefore could not be measured for light absorbency. This is an important point to consider when looking at some of the anomalies in the above results which were mainly gained from a similar experimental use of counting population density using a spectrophotometer.

Arana et al (2010) compare how environmental conditions (temperature variation and nutritional deprivation) effect 2 different bacteria, Pseudomonas fluorescens and Escherichia Coli. They note that when nutrients were removed the temperature variations did not create a common pattern. When Pseudomonas fluorescens was subjected to temperatures between 5-15°C it responded differently than it did at higher temperatures irrelevant to the nutritional composition, which suggested that temperature was an important factor for the organism. This makes it an ideal subject for experiments which are measuring the effects of variations In temperature.

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Recent studies on Pseudomonas fluorescens show it has become increasingly problematic as a bacteria that is found infecting the human body. Donnarumma et al (2010) study on Pseudomonas fluorescens suggest there is a need to research into the ways in which this bacteria exists at different temperatures. They discovered that this micro-organism could grow at 28 and 37 degrees Celsius. At the lower temperatures Pseudomonas fluorescens induced proinflammatory cytokines and a bio-film was formed at 37 degrees Celsius. This suggests it performs as an opportunistic pathogen and further research needs to be done to discover how it responds to temperature changes in different environments.

The data shown in table 7 - 10 show a result of 0 P.caudatum for sample 2 at 15°C on day 1. This is because the falcon tube was not mixed before the 1000ul sample was taken and view through a dissecting microscope. This will have effected all of the results for 15°C on day 1 P.cardatum but the falcon tubes were mixed after this first sample for all of the other results. As they were not mixed for the first results all of the organisms will have been closer to the bottom of the tube this is why the result is lower for the first 3 shown in the table and even 0 counted for sample 2. Evidence of this can be seen on tables 8-10 that do have a population counted for all of the P.cardatum at 15°C. In relation to this when looking at p.caudatum on these tables it can be seen that the number is reduced each day at the higher temperatures but increases at the lower temperature. It can be seen that P.cardatum is not present in any samples at 25°C after day 2. It also shows that there is a higher population of p.caudatum in the first replicate of each temperature and when looking at the agar plates shown in image 1-3 you can see the large red colonies. The monocultures however show a much larger growth with each dilution having more colonies.

Another eukaryote that had a number count of 0 at 1000ul was Chilomonas at 20°C on day 2 sample 2. On day 3 and 4 there was also a count of 0 for sample 2 and 3. This would suggest that another organisms ideal temperature was around 20°C and out compete Chilomonas. The date shown in table 11 provides evidence that Chilomonas is eating the bacteria at the higher temperature, which is why there is a larger count under a microscope of the microcosm. This is also why there is a higher count at lower temperature on the petri dish. Chilomonas is eating the bacteria allowing for more growth of the red Serratia at 15°C as less has been eaten. The Petri dishes on image 1-3 do show some growth at the more diluted samples. This is most likely down to bad pipetting but there is less of this on the later days.

The absorbance levels for day 1 (table 1) support the results seen on the agar plate count (image 1) with more growth of the monoculture at 15°C but less at 20°C and 25°C. As there was some contamination with the first 3 samples on the plate it has given a larger growth for these first 3 but this is not consistent with the data shown from day 1 absorbance levels. Day 2 absorbance levels also support day 2 agar plate count. There was more growth at the lower temperatures and less at the higher. This includes the monoculture although these seem to be a small absorbance at 25°C for the monoculture but still a larger amount of growth on the agar plate compared to the communities. Day 3 has similar data to day 2 in that there is more growth at the lower temperature and less growth at the higher. Although the 20°C monoculture has less absorbance than the 25°C monoculture but no by a large amount. This does not support previous days or the data from the agar plate which follows the lower temperature having more and lower having less.

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As previously mentioned one of the reasons for these changes in population is that the added organisms that were chosen out compete at the higher temperature. This meant there was less bacteria which can be seen when looking at the agar plate (image 1-3) and absorbance levels (table 1-6, graph 1-2) which had removed he larger eukaryotes by centrifuge. This is supported by the evidence provided by the microcosm plate counts done on each day that shows more eukaryotes at the higher temperatures and less at the lower temperatures. Alternative methods could be used instead of polymerase chain reaction in the study. A recent scientific journal by Fakruddin et al (2013) gives supporting evidence in the use of nucleic acid amplification.

Some errors were seen throughout this experiment due to contamination and human error. In order to get a more accurate results this experiment should be repeated and each sample should be replicated more than 3 times in order to get a more reliable result and remove any anomalies. Further research should be done into the growth factors of different organisms and bacteria at a larger range of temperature and over a longer period of time to give clearer evidence of the impact of environmental temperature change. There could also be experiments using animals to see the impact of temperature change on a larger organism. Ethical impact should be considered when performing animal testing especially involving experimental changes that could cause pain and death. Environmental impacts by global warming are shown by temperature variation in this study. All living organisms have a ideal temperature that they will thrive at and temperature that they will be out compete or die at. This is shown by the data provided in this experiment and as there is evidence of climate change the ecosystem will be effected.

In conclusion the evidence provided by this study suggests that there is a major impact on the eco-system due to temperature changes. The original aim of this study was to analyse the impact of temperature on Pseudomonas fluorescens. However, due to evidence that can be seen by the results of the PCR experiment on the target organism, the Pseudomonas fluorescens was out compete at all temperatures by the other organisms and bacteria which were present in the community. The impact of temperature could still be analysed on the community. It was seen that, at lower temperatures, certain bacteria thrived and at higher temperature other bacteria thrived. This gives supporting evidence towards the major impacts of environmental change in connection to changes in the eco-system. The data provided by this research highlights the need to examine temperature change on organisms as they exist, not in isolation, but within a community.

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Appendix:

An important part of the study was identifying the eukaryotes by learning the differences between their size, shape and movement. Below is a table of the notations taken from close observation of the eukaryotes used in this experiment.

-------------------------------------------------------------------------------------------------------Euglena:

- on a dissecting microscope (x10) small oblong rods black (some dark green) abundant and clustered together slow movement with some turns- on a stage microscope (x400) small, round, green with dark green circles and some light green colouring

Colpidium:- on a dissecting microscope (x10) small oblong rods clear with a black outline abundant fast movement and multiple turns

Blepharisma: - on a dissecting microscope (x10) large oblong rods red with white inside sparse numbers sporadic movements (some fast, others slow)- on a stage microscope (x100) small, oblong rod, red with red circles inside

Chilomonas: - on a dissecting microscope (x10) small round white sparse circular or spinning movements along with up and down- on a stage microscope (x400) small, round, clear with some clear circles inside

Paramecium caudatum: - on a dissecting microscope (x10) large oblong red and white medium numbers

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fast movement, straight with some turns- on a stage microscope (x400) small, oblong, red with white cloudy inside

-------------------------------------------------------------------------------------------------------Figure 3: Observable differences between Eukaryotes as viewed under dissecting microscope and stage microscope.

Agar dish Sample

4 1 2 3 5 6 Dilution* * * * * ** * * * * ** * * * * ** * * * * ** * * * * *

Agar dish Sample

7 8 9 10 11 12 Dilution* * * * * ** * * * * ** * * * * ** * * * * ** * * * * *

Figure 4: A serial dilution of and its position on each agar plate.

Solutions were diluted by adding samples from numbers 1 to 12. The above diagrams show the position of each sample and the dilution on the agar plate. 2ul were pipette for each and as you can see the first petri dish placed sample 4 first. This figure relates to the agar plate shown below in Image 1.

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Image 1: Day 1 agar plates.

Agar dish Sample

1 2 3 4 5 6 Dilution* * * * * ** * * * * ** * * * * ** * * * * ** * * * * *

Agar dish Sample

7 8 9 10 11 12 Dilution* * * * * ** * * * * ** * * * * ** * * * * ** * * * * *

Figure 5: A serial dilution of and its position on each agar plate.

Figure 5 relates to the agar plate shown in Image 2 and image 3.

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Image 4: primer 2 analyses on electrophoresis gel viewed under UV light, the data used in this experiment was on the top left.

Image 5: day 3 sample 1-3 of 20 and 25°C on electrophoresis gel viewed under UV light, the data used in this experiment was on the top left.

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References:

Arana, I. Muela, A. Orruno, M. Seco, C. Garaizabal, I. Barcim, I. (2010) Effect of Temperature and Starvation upon survival strategies of Pseudomonas fluorescens CHAO: Comparison with Escherichia Coli. FEMS Microbiology Letters. 1: 1-11.

Bartlett JM, and Stirling D. (2003). A Short History of the Polymerase Chain Reaction. PCR Protocols. Methods in Molecular Biology. 226(2): 3–6.

Decoin, V. et al. (2015). A Pseudomonas fluorescens type 6 secretion system is related to mucoidy, motility and bacterial competition. BMC Microbiology. 15(1): 1-12.

Donnarumma, G. Buommino, E. Fusco, A. Paoletti, I, Auricchio, L. Tufano, M.A. (2010) Effect of temperature on the shift of Pseudomonas fluorescens from an environmental microorganism to a potential human pathogen. International Journal of Immunopathology and Pharmacology. Jan-Mar; 23(1): 227-34.

Ellis, M. (1998) Infectious Diseases of the Respiratory Tract. Canmbridge U P.

Fakruddin, Md. et al. (2013). Nucleic acid amplification: alternative methods of polymerase chain reaction. Journal of Pharmacy and BioAllied sciences. 5(4): 245-252

Ferrarini, A. Rossi, G. Mondoni, A. Orsenigo, S. (2014) Prediction of climate warming impacts on plant species could be more complex than expected: Evidence from a case study in the Himalaya. Elsevier. 120: 307

Fouchard, S. Abdellaoui-Maane, Z. Boulanger, A. Llopiz, P. Neunlist, S. (2005) Influence of growth conditions on Pseudomonas fluorescens strains: A link between Metabolite production and the PLFA profile. FEMS Microbiology Letters. 251: 211-218.

Gill, C.O. (1975) Effect of Growth Temperature on Lipids of Pseudomonas fluorescens. Journal of General Microbiology. 89: 293-298.

Naidu, C.V. Raju, A.D. Satyanarayana, G.CH. Kumar, P.V. Chiranjeevi, G. Suchitra, P. (2015) An observational evidence of decrease in Indian Summer monsoon rainfall in the recent three decades of global warming era. Elsevier. April 127. pp 91-102.

Naseby, D.C. Lynch, J.M. (2002) Enzymes and Microorganisms in Rhizosphere. Enzymes in the Environment. 1:109-124.

Nicholas M, and Nelson K. (2013). Blotting Techniques. Journal of Investigative Dermatology. 133(7): 10

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