UNIVERSITY OF MIAMI

THE NATURE OF EXTRACELLULAR VESICLES SHED BY DAMSELFISH CELLS IN VITRO

By

Molly R. Schuld

A THESIS

Submitted to the Faculty of the Rosenstiel School of Marine and Atmospheric Science

Coral Gables, Florida

May 2014

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UNIVERSITY OF MIAMI

A thesis submitted in partial fulfillment of the requirements for Departmental Honors in Marine and Atmospheric Science

The Nature of Extracellular Vesicles Shed by Damselfish Cells in Vitro

Molly R. Schuld

Approved: __________________________________ _________________________________ Dr. Michael C. Schmale Dr. Lynne A Fieber Chair of Thesis Committee Associate Professor Professor Marine Biology and Fisheries Marine Biology and Fisheries

__________________________________ Dr.  Gary  Hitchcock Director of Undergraduate Marine and Atmospheric Science Program Marine  Biology  and  Fisheries

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The Nature of Extracellular Vesicles Shed by Damselfish Cells in Vitro

Molly R. Schuld

ABSTRACT: Damselfish neurofibromatosis (DNF) is a cancer affecting bicolor damselfish on the reefs of Florida. It is a transmissible disease caused by the Damselfish virus-like agent (DVLA). The means by which the DVLA is transmitted are still unknown. One possible way the agent could be transferred from cell to cell is via extracellular vesicles. This research focuses on extracellular vesicles that are shed by damselfish cells in vitro from tumor-derived cell lines and healthy cell lines. These cell lines are observed in a normal state and after being exposed to UV to induce apoptosis. Apoptosis is induced with the intent of increasing the number of extracellular vesicles being shed. Then, using fluorescence and oil immersion microscopy, vesicles are analyzed. Focus is placed on the organelles within the extracellular vesicles to study the material being transported.

KEY WORDS: Damselfish; Neurofibromatosis; DVLA; Extracellular Vesicles; UV; Apoptosis; Oil Immersion

INTRODUCTION Von Recklinghausen neurofibromatosis, (NF1) is a common genetic disorder occurring in approximately 1 out of 3000 people (Crowe et al. 1956). This makes it the most common neoplastic disease dealing with Schwann cells in humans (Bollag & McCormick 1991). Little is known about the development of NF1 due to a lack of suitable animal models (Schmale et al. 1996). Schwann cell tumors have been studied in mammalian species, but none of the tumors appear regularly or often enough, and they are not comparable to those of NF1 (Riccardi 1981). Neoplastic diseases, especially peripheral nerve sheath tumors, are common in fish (Mawdesly-Thomas 1975). Certain neoplastic diseases in fish are comparable to human neurofibromatosis. In particular, the bicolor damselfish, Stegastes partitus, serves as an animal model for NF1 (Schmale et al. 1986). Damselfish neurofibromatosis is a transmissible cancer affecting bicolor damselfish on South Florida reefs. Damselfish neurofibromatosis was actually named based on its similarities to von Reckinghausen neurofibromatosis (Schmale & Hensley 1988). Damselfish neurofibromatosis (DNF) is a unique disease because it is the first discovered naturally occurring, transmissible cancer originating in the nervous system or chromatophores (Schmale 1995). It is also the only current example of a transmissible

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tumor dealing with Schwann cells (Schmale et al. 2002). This neoplastic disease consists of malignant peripheral nerve sheath tumors (Schmale 1991). These tumors share similar pathology with NF1 in humans (McKinney & Schmale 1997). The main difference between DNF and NF1 in man is that DNF is transmissible, whereas NF1 is an autosomal dominant mutation (Schmale & Hensley 1988). DNF has been successfully injected into healthy fish, which means the disease is caused by a subcellular agent (Schmale et al. 1996). At present, the causative agent of DNF has been discovered. It has been named the damselfish virus-like agent, or DVLA. The current hypothesis is that DVLA is the etiologic agent of DNF, which is encoded in extrachromosomal DNA (Schmale et al. 2002). Damselfish virus-like agent replicates in the mitochondria of infected cells. However, the tumorigenisis mechanisms of DVLA are unknown (Rahn et al. 2004). Thus, a key goal of this research is to understand how DVLA is transmitted outside of the cell. One possibility is that DVLA travels between cells via extracellular vesicles. From here further study would be needed to understand how DVLA then infects the mitochondria, and how this leads to tumor formation. This research is focusing on exploring the extracellular vesicles that are shed by damselfish cells while in vitro and investigating the possibility that these vesicles may play a role in the transport various cell components. DVLA causes this disease, but the means by which the DVLA spreads is still unknown (Rahn et al. 2004). If evidence suggests that DNA is indeed transported via extracellular vesicles in damselfish cells, a possible answer may be at hand. Currently the gene responsible for NF1 has been found, but the means by which the gene causes the disease to develop are unknown (Gutmann & Collins 1993). Likewise DVLA has been discovered for DNF, but the means by which it is transferred and eventually causes tumor formation is still unknown. Further experimental studies of the latter may provide clues to discovering the former. In fact, understanding the agent responsible for DNF might be directly applicable to understanding the pathogenesis of NF1 in humans (Schmale & Hensley 1988). MATERIALS AND METHODS Cell Cultures. Cultures were derived from four tumor cell lines, 88-503, 96-24, FX96-24, and 77B. These are immortal cell lines from neoplastic Schwann cells in bicolor damselfish. 88-503 originates from experimentally induced tumors (Schmale 1995). This line derives from a healthy fish injected with tumor homogenate (Schmale 1995). 96-24, however, originates from naturally occurring tumors (Schmale et al. 2002). Likewise, FX96-24 is a version of 96-24, but the DVLA has been removed. 77B is a DVLA-free cell line that was derived from healthy fish. Thus, 88-503 and 96-24 have DVLA while FX96-24 and 77B do not. Also, a retrovirus was isolated from DNF tumor cell lines and is known as the damselfish neurofibromatosis virus, or DNFV (Schmale et al. 1996). DNFV is one of about eleven retroviruses that are being researched for involvement in various fish diseases (Pinto et al.

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1995). The retrovirus was incorporated into 88-503 and 77B to immortalize the lines (Schmale 1995). 96-24 and FX96-24 immortalized without the addition of the retrovirus (Schmale et al. 2002). The media used for the cultures was Leibovitz’s L-15 with additions including 5 M NaCl, 10% foetal bovine serum, 100 units/ml of penicillin, streptomycin, and fungizone, distilled water for dilution (Schmale 1994). Before a new media bottle was put into use, 6 mL of 10 mg/ml Ampicillin, or AMP 100, was added. Cultures were incubated at 28 degrees Celsius (Schmale 1994). Feeding. Cells were fed weekly using sterile procedures. Cells were fed under the hood. The old media in the cultures was emptied into a waste bottle. Then the media was replaced using room temperature media. Afterwards the cultures were returned to the incubator. Cell Passaging. Cells were passaged whenever new cultures were required for staining. Each cell passage was recorded on a count sheet. This procedure was done using sterile techniques. Cell passaging began by completely emptying the media from a T75 flask in use. It was then rinsed three times with 10 mL of Hanks’ Balanced Salty Solution (HBSS), to get rid of dead cells. Note that 88-503 was only rinsed twice. On the last rinse, 1 mL of trypsin was added to the HBSS to initiate cell detachment. The culture was then placed on the shaker at a low speed for ten minutes. The flask was then brought back under the hood where any cells that remained attached were removed using a scraper. The HBSS and cells in the flask were then emptied into a 50 mL Bluemax tube. Finally, the flask was rinsed with 10 mL of L-15 to inhibit the trypsin activity (Schmale 1995). This also was added to the Bluemax tube. Next, 50 µL was taken out of this tube to do a cell count. The cells were counted using a hemocytometer and Trypan blue. While counting the cells, the Bluemax tube was centrifuged at 1675 rpm for ten minutes. Afterward the supernatant was poured into the waste, and the pellet was quickly re-suspended in L-15. The volume of L-15 added depended on calculations from the cell count. The amount accounted for a cell concentration of 10,000 cells/mL. Then the appropriate amount of this well-mixed solution, followed by media, was transferred to start a new culture to either a T25 flask or a 35 mm glass bottom dishes. The amount of the re-suspended solution added to each culture depended on the desired concentration of cells, as T25 flasks were plated at a much higher concentration than 35 mm glass bottom dishes. Note that there were some difficulties using the glass bottom dishes. This was because the cells prefer the sealed environment of the glass and struggled with the more oxygenated and open dish environment. Also, cells seemed to prefer the plastic base over the glass base. When plating on dishes time was required to pipet the mixed media and cells up and down to encourage even dispersal. Once these new cultures were plated, they were returned to the incubator. Finally the passage was documented including the cell line and passage number. Inducing apoptosis. As mentioned, a focus of this research was studying extracellular vesicles. One type of extracellular vesicle is an apoptotic vesicle. Apoptosis was induced in cultures to

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encourage vesicle shedding to enhance the study. This method was beneficial to expand data collection, but it must be noted that this was a forced situation and thus represents an atypical death. To induce apoptosis, cultures were exposed to ultraviolet radiation by placing them on a UV exposure box. Dishes were placed on the box with the cover removed for 1 minute and then cultures were stained and imaged 24 hours later. This had to be altered slightly when working with 77B, because all of the cells died within the 24hours period. 77B was redone with 1 minute on the UV and a 12 minute sit time, which was more successful. Staining. Cell staining was a key procedure in collecting quantitative data throughout this research. Staining occurred both for cell cultures in T25 flasks and in 35 mm dishes with coverslip bottoms. Seven different stains and combinations of these stains were used (Table 1). The various stains labeled different components of the cells. One of the stains used was MitoTracker Red, which stains the total mitochondria red. Also used was MitoTracker Green, which stains the total mitochondria green. The SYBR Gold stain was also used, which stained the nucleus and other nucleoids throughout the cell in green. Hoechst stained just the nucleus or nuclei blue. Another stain was JC-1, which stains based on the membrane potential of the mitochondria. It stains areas with high membrane potential as red, and mitochondrial areas with lower membrane potential in green. The Nile Red probe was also used, which stains lipids in both green and red. It stains polar lipids red, causing a faint red stain of the cell membrane area. The stain also emits in green in the presence of nonpolar lipid droplets seen throughout the cell (Greenspan et al. 1985). Lastly, the Quinacrine stain was used, which stains in green and is thought to label ATP. To stain cultures, the appropriate amounts of the working solutions for the desired stains were added and swirled into each flask or dish. Then the cultures were left to sit in darkness at room temperature for one hour. Once this hour was up, the cultures were rinsed with serum-free media. Then they were observed under the inverted microscope using a mercury lamp. This procedure remained constant for both the T25 flasks and the 35 mm glass bottom dishes. The dishes, however, varied in the volume of working stock added. This difference was essential due to the difference in cell magnitude and media volume between the two culture devices. For instance, a typical T25 flask was plated at 250,000 cells, whereas a typical 35 mm glass bottom dish was plated at 75,000 cells. Also, the volume of working solution added to the T25 flask is based on a 7 mL volume of media. The dishes, however, only had a media volume of 2 mL. The amount was calculated from the amount used in the T25 flasks, taking into account the change in media volume. Listed below are the various fluorescent stains used and the measurement details (Table 1).

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Table 1. Fluorescent stains used throughout research. This table lists the details on how the stain solutions were prepared. Note the stain abbreviations, which will be used throughout this thesis paper.

Microscopy. Cells were observed using a Olympus IX70 inverted microscope. This included phase contrast as well as fluorescence illumination. When dealing with fluorescence, a mercury lamp and a digital shutter were used. Images were taken using a high-sensitivity Retiga EXi camera and the imaging program QCapture. To take pictures, the camera was turned on, the software was opened, and the microscope light was switched to sideport. Pictures were taken both in phase contrast and using the mercury light, under different wavelengths to express different fluorescence. When multiple pictures were taken of one cell or area, the color channels were merged together using Fiji to create one composite RGB image. Images for general cell data collection were taken using the 40x objective. When working with the T25 flasks, this objective was used along with the additional 1.5x magnifier. Thus, images were mostly taken at 600x magnification. However, when working with the coverslip dishes, the 60x objective was used in some cases. Often to increase magnification and quality of images, oil immersion was used. Oil immersion. Oil immersion was used with the 35 mm glass bottom dishes. This was done for data collection on vesicles. A drop of low viscosity oil was added to the 100x OIL objective. Note that phase contrast was not possible with this objective. The 1.5x magnifier was not used as it led to a loss of quality. Thus, most oil immersion pictures were taken at 1000x magnification. Once the oil was in place, the dish was placed on top of it to immerse the glass bottom. Then microscopy techniques proceeded as they did with the flasks. The use of oil immersion was ideal when looking for vesicles because of the high magnification and because the immersion allowed for increased image resolution. Quantitative analysis. In order to gather quantitative data to understand the research results, Fiji, or ImajeJ was used, along with Microsoft Excel. This data collection occurred by taking data from individual cells. First a scale was set on Fiji using millimeter measurements from micrometer images at the respective magnifications. After this scale was set globally, a composite image was opened. From here quantitative data could be collected.

Fluorescent Stain

Stain Abbreviation

Used to Make Standing Stock

Concentration from Stock

Working Solution added toT25’s

MitoGreen MG 1mg/mL in DMSO 10:1 5 µL MitoRed MR 1mg/mL in DMSO 10:1 5 µL

SYBR Gold SG 1mg/mL in dH2O 10:1 20 µL Hoechst H 1mg/mL in dH2O 10:1 20 µL

JC-1 JC1 1mg/mL in DMSO 10:1 28 µL Nile Red NR N/A (Use stock) 7 µL

Quinacrine Q N/A (Use stock) 35 µL

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When collecting data on general cellular trends and compositions, mostly images from the flasks taken at 600x magnification were used. After an image was opened, the desired cell was first outlined and the total cell area was measured. Then the color channels were split. This allowed for the nucleus area to then be taken, again by outlining and measuring it. Next, the individual fluorescent stains were analyzed. This was done on individual color channels by adjusting the auto local threshold of a channel using the Bernsen method. Then the particles within the cell area were analyzed. These data provided information on the total area of the various cell components along with further details. For instance, it outlined and gave the area of the specific particles for each stain. Several stains required additional steps. For example, when using SG, the stained nucleus area had to be accounted for and removed. This was done by taking the area of the particles within the nucleus area, and subtracting it from the total analyzed SG area. Also, when working with JC1, extra steps were required to find the total stained area. This was done by again splitting the channels and using the Bernsen auto local threshold method. These images were then overlapped using the pairwise stitching function. They were merged using the fusion method linear blending. This presented an image where the two channels could be differentiated. Then the Bernsen auto local threshold was taken again, creating a merged stain. These particles were then analyzed giving the total stain area. When collecting on vesicles, specifically from the oil immersion pictures, quantitative data collection was more limited. This is because at 1000x magnification, most images did not include a whole cell. Thus data were collected on items such as vesicles and nucleus number and area. Not being able to account for the whole cell was limiting, but a necessary loss to gain the magnification to image vesicles. The data collected from Fiji were then recorded in Excel. In Excel, data were analyzed to provide information and to look for patterns. Some analysis key points included the ratio of fluorescent stains, the cell area compared to the nucleus, the various stain areas in relation to each other and the cell, different percentages, vesicle number and so on. This numerical data were then represented visually in bar graphs and scatter plots. RESULTS The main cell lines worked with originally were 88-503 and 96-24, both of which are cell lines from neoplastic Schwann cells in bicolor damselfish. Both cells were similar in that they had variable morphology. Both cell lines had mostly elongated mitochondria, with the highest density around the nucleus. There were, however, some distinctions between the two cell lines. They ranged in size and amount of branches. For instance, they differed in overall shape. 88-503 cells tended to be more rounded, with many branches going out in all directions away from the center. 96-24, on the other hand, tended to be more elongated and tubular, with few branches usually just at the ends. These basic differences between 88-503 and 96-24 cells can be seen using the Diff-Quick stain in Figure 1.

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A while into research, two more cell lines were added, FX96-24 and 77B. FX96-24 was similar in resemblance to 96-24. More quantitative data on various cellular organelles in FX96-24 should be conducted for better comparisons. 77B was worked with more extensively than FX96-24. 77B has characteristics of both 88-503 and 96-24. Most 77B cells were elongated in general, but many also had additional elongated branches. 77B cells were also on average larger than 88-503, 96-24, and FX96-24. A common trait between all of the cell lines analyzed was that many were multinucleated. These cells were presumably about to divide, or beginning apoptosis. The percentage of cells with more than one nucleus out of the total cells analyzed was relatively constant between the 88-503, 96-24, and 77B as can be seen in Table 2. FX96-24 was not worked with for overall cell analysis, so this information could not be collected. Overall an average of 36.28% of multinucleated cells was observed between 88-503, 96-24, and 77B. There was little deviation between the cell lines. This could suggest a high percentage of cells dividing, or cells beginning to die. To explore this the multinucleated cells from 88-503, 96-24, and 77B were split into two groups. Cells with two nuclei of roughly equal size were presumed to be undergoing mitosis and were labeled as dividing. All of the other multinucleated cells, either with many nuclei or disproportionately sized nuclei, were labeled as other. These are unhealthy cells, which includes cells undergoing apoptosis or those in a pathological state. Note that this was subjective and there may be slight inaccuracies. The results of this can be seen in Figure 2. This graph shows that of all the multinucleated cells, most were in an unhealthy state (Figure 2). Calculations found an average of 43% of the multinucleated cells were dividing or undergoing mitosis, whereas 57% were in another multinucleated state. There was no significant variation between the three cell lines (Figure 2). Future research could involve trying to further differentiate between cells undergoing mitosis vs. cells undergoing apoptosis. For instance, they can be sorted according to different cellular components, number of vesicles shedding, and so forth. Also, cells undergoing mitosis can be further segregated into the various stages of mitosis. From there the stages can correlate with cell size, amount of nucleoids, and many other cell features.

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Fig 1. Diff-Quick stain showing basic morphology of cells. The nucleus is stained a dark blue, while the cytoplasm is a pink/purple. a 88-503 cell that is rounded with branches. b 96-24 cell that is elongated and has less branching.

Table 2. Percentage of cells that were multinucleated out of the total cells analyzed for 88-503, 96-24, and 77B.

Cell Line Cells with more than 1 nucleus/total cells 88-503 31.91% 96-24 37.80% 77B 39.13%

A  

B  

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Fig 2. Percentage of total multinucleated cells in each cell line undergoing mitosis vs. those in an ‘Other’ state. Other includes cells in apoptotic or pathological states.

STAINING SYBR Gold and MitoRed. 88-503

• MR Area and Total Cell Area correlated with average slope of .093 mm2 MR/Cell Area (Figure 2).

• SG Area and MR Area do not show a clear correlation. SG area shows little variation (Figure 3).

• SG Area and Total Cell Area seem to have a slight correlation, but there is much variation (Figure 4).

• As MR and Total Cell Area increase together, SG Area also increases but with much more deviation.

• The lack of exact correlation between SG and the MR/Total Cell Area means that SG is likely dependent on another factor as well.

96-24 • Again MR Area and Total Cell Area are correlated with a slope of about .083

mm2 MR/Total Cell Area. This is more difficult to tell because most cells fall within a small Cell Area range (Figure 2).

• Again little correlation between SG Area and either Total Cell or MR Area. • Many cells with very small SG Area. However, removing these points did not

change the overall trend. 77B

• MR Area and Total Cell Area correlated with a slope of about .082 mm2 MR/Total Cell Area (Figure 2).

0%  

10%  

20%  

30%  

40%  

50%  

60%  

70%  

Mitosis   Other  

%  Total  Multinucleated  Cells  

Phase  of  Multinucleated  Cell  

Percentage  Mitotic  vs.  Non-­‐Mitotic  Multinucleated  per  Cell  Line    

88-­‐503  

96-­‐24  

77B  

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• Seems to be a vague increase of SG Area with both Total Cell and MR Area, but individual points are vast in range.

• The SG seems to be more fixed and to increase at a slower rate than in 88-503 or 96-24.

Overall, the slopes of MR Area to Total Cell Area for three lines are similar and give an average of .86 mm MR/Total Cell Area (Figure 3). The most conclusive data are seen between the MR Area and Total Cell Area, with MR tracking the cell size. The SG to MR Area data do not show much correlation. Very small cells have much less SG. Overall there is only a slight relation between SG and MR or cell size (Figure 4). This is confirmed by the SG and Total Cell Area data, which show little correlation (Figure 5). When comparing SG values with 88-503 and 77B, it is clear that 96-24 has many more extremely small cells This is likely due to an error in the staining procedure as most of these points were collected on the same day. However, even once these small values are removed, there is only vague correlation. Further analysis of 96-24 cells may produce more conclusive results. The general trend was that MR and Total Cell Area are more correlated than SG is to either. The SG data are variable, implying that external factors may be at play. One hypothesis is that the amount of SG in the cell may be related to the stage of cell’s life cycle it is in. For instance, the amount of SG might be highest right when a cell is going to divide and low again as it begins to grow. This requires further data collection and analysis to examine, as well as method improvement for such sorting. A relationship between the nucleoids in a cell and the number of nuclei was examined but proved inconclusive as can be seen in Figure 6. This was tested by taking the percent of SG out of the cell area minus the nucleus. There does not seem to be a trend between the number of nuclei and the SG percent. However, Figure 6 is inconclusive, and more multinucleated cell data can help prove this. To further examine possible relationships between SG and nuclei, the data in Figure 6 were further sorted. All cells with two or more nuclei from Figure 6 were sorted into mitosis or unhealthy in the same manner as was explained before. These data were then graphed using the SG Area and MR Area, to see if there was a pattern in the case of mitotic of unhealthy cells. Figure 7 shows the SG versus MR area of cells undergoing mitosis. This actually does show some correlation, with SG for the most part increasing as MR increases. All three cell lines follow a similar slope. However, this is not true in Figure 8, which shows SG versus MR area for the multinucleated cells that are not dividing. In other words, these multinucleated cells are unhealthy. Unhealthy multinucleated cells of the various cell lines do not correlated with each other. However, each individual cell line seems to have a slight correlation in SG and MR area. This is hard to define because there are few cells and because 88-503 and 96-24 seem to be increasing in SG area per MR area much slower than 77B. More cells must be imaged and then analyzed to confirm this trend. If the trend holds true, there may actually be correlation between SG area and MR area, and thus cell area. Figure 4 and Figure 5 may be deceiving because of the inclusion of every cell type. Further collection of both mitotic and other multinucleated cells should be conducted to clarify this.

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Figure 9 shows that the SG:MR ratio is highest for 77B. It is lowest for 96-24. Also there was large standard deviation. Still, if 77B does have a significantly higher ratio of SG to MR, it will be interesting to explore, as 77B is the only DVLA-negative cell line. However these results must be looked at in the context of Figure 10. This is because Figure 20 shows the percentage of SG and MR out of the total cell area for each cell line. The percentage of SG in the cell stays relatively constant. However, the percent of SG for 96-24 is slightly smaller, which is likely due to the many cells with low SG. For the percent of MR out of the total cell area, there is a clear difference. 96-24 has the most, followed by 88-503, and then 77B. This variation likely had the most effect on the variation. For example, 77B had the highest SG:MR ratio. Judging by Figure 10, this is because 77B had a significantly smaller percentage of MR in the cell. 96-24, on the other had, had the smallest SG:MR value. This is because it had the greatest amount of MR in the cell, and also the smallest amount of SG. There is again a wide standard deviation. Regardless, examining these ratio differences, especially when comparing 77B to 88-503 and 96-24, may provide clues to patterns leading to tumor formation.

Fig 3. MR Area vs. Total Cell Area shows a clear correlation in all three cell lines.

0.00E+00  

2.00E-­‐04  

4.00E-­‐04  

6.00E-­‐04  

8.00E-­‐04  

1.00E-­‐03  

1.20E-­‐03  

0   0.002   0.004   0.006   0.008   0.01  

MR  Area  (m

m^2)  

Cell  Area  (mm^2)  

MR  Area  vs.  Cell  Area  

88-­‐503  

96-­‐24  

77B  

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Fig 4. SG Area and MR Area show slight correlation, but there is much variation. Notice the many small SG Area values for 96-24 [Note: In this figure, one extremely large 88-503 value and one extremely large 96-24 value were removed].

Fig 5. There is vague correlation between the SG and Total Cell Area, but no distinct relationship for any cell line [Note: In this figure, one extremely large 88-503 value and one extremely large 96-24 value were removed].

0.00E+00  

5.00E-­‐05  

1.00E-­‐04  

1.50E-­‐04  

2.00E-­‐04  

2.50E-­‐04  

3.00E-­‐04  

0.00E+00   2.00E-­‐04   4.00E-­‐04   6.00E-­‐04   8.00E-­‐04  

SG  Area  (mm^2)  

MR  Area  (mm^2)  

SG  vs.  MR  Area  

88-­‐503  

96-­‐24  

77B  

0.00E+00  

5.00E-­‐05  

1.00E-­‐04  

1.50E-­‐04  

2.00E-­‐04  

2.50E-­‐04  

3.00E-­‐04  

0   0.001   0.002   0.003   0.004   0.005   0.006   0.007   0.008   0.009  

SG  Area  (mm^2)  

Cell  Area  (mm^2)  

SG  Area  vs.  Cell  Area  

88-­‐503  

96-­‐24  

77B  

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Figure 6. Shows the percent of SG stain out of the cell area minus the nucleus plotted against the # of nuclei. [Note: In this figure, any points below 1% SG in the cell area (minus nucleus) were removed].

Figure 7. This graph shows the SG area versus the MR area in mitotic cells. Few cells were collected to be plotted, but the few shown seem to show correlation.

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2.00%  

4.00%  

6.00%  

8.00%  

10.00%  

12.00%  

14.00%  

0   1   2   3   4   5   6  

%  SG  in  Cell  Area  

#  Nuclei  

%  SG  in  Cell  Area  vs.  #  nuclei  

77b  

88-­‐503  

96-­‐24  

0.00E+00  

6.00E-­‐05  

1.20E-­‐04  

1.80E-­‐04  

2.40E-­‐04  

3.00E-­‐04  

0.00E+00   2.00E-­‐04   4.00E-­‐04   6.00E-­‐04   8.00E-­‐04  

SG  Area  

MR  Area  

MR  vs.  SG  Area  in  Mitotic  Cells  

88-­‐503  

77B  

96-­‐24  

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Figure 8. This graph shows the area of SG versus the area of MR for apoptotic cells. Again few cells were collected, but there are still some trends. The three cell lines do not show an similar trend, however each individual cell lines seems to represent a slight correlation of SG versus MR area.

Figure 9. This graph shows the average SG to MR ratio for all three cell lines. Notice that there is large standard deviation.

0.00E+00  

8.00E-­‐05  

1.60E-­‐04  

2.40E-­‐04  

3.20E-­‐04  

4.00E-­‐04  

0.00E+00   2.00E-­‐04   4.00E-­‐04   6.00E-­‐04   8.00E-­‐04  

SG  Area  

MR  Area  

MR  vs.  SG  Area  in  Apoptotic  Cells  

88-­‐503  

77B  

96-­‐24  

0.00  

0.05  

0.10  

0.15  

0.20  

0.25  

0.30  

0.35  

0.40  

0.45  

SG:MR  

Cell  Line  

SG:MR  

88-­‐503  

96-­‐24  

77B  

  14  

Figure 10. Shows the average SG and MR percentages from the total cell for all three cell lines. Quinacrine and MitoRed (and Hoechst). 88-503

• MR Area and Cell Area are correlated (Figure 11). • Q Area and MR Area seem to show correlation (Figure 12). • Q Area and Cell Area correlated as well (Figure 13).

96-24 • MR Area and Cell Area are correlated (Figure 11). • Q Area and MR Area seem to show correlation as well, but there is one extreme

point that is helping the pattern appear linear (Figure 12). • There is correlation between Q Area and Cell Area, but there is much variation

(Figure 13). Overall, more correlation is seen in 88-503 than in 96-24. The clearest linear correlation is seen between MR Area and Cell Area. Figure 11 shows this in combination with data from Figure 3. There is a distinct correlation between mitochondria area and cell area in 88-503, 96-24, and 77B (Figure 11). The Nucleus and Cell area increase in a positive, linear fashion. For 88-503, the relationship has a slope of about .022 mm2 Nucleus/Cell Area (Figure 14). The increase in nucleus area per cell area is greater in 96-24, with a slope of about .075 mm2 Nucleus/Cell Area (Figure 14). This difference is interesting and is worth investigating further, especially with 77B. Figure 15 shows that the Q Area and Nucleus Area are also correlated. This makes sense as there is a strong correlation between the Nucleus Area and Cell Area, and there is also

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5.00%  

10.00%  

15.00%  

20.00%  

25.00%  

30.00%  

SG  IN  CELL   MR  IN  CELL  

Percentage  

SG  and  MR  Percents  in  Cell  Lines  

88-­‐503  

96-­‐24  

77B  

  15  

correlation between the Q Area and Cell Area. However, it would be interesting to discover if Q is increasing because of the increase in cell size, or if it is highly dependent on the nucleus. This requires further investigation into what quinacrine is actually staining. Lastly the MR to Q ratio was observed (Figure 16). This was fairly constant between the two cell lines, with an average of 4.15 times as much MR as Q. Further observation reveals that this does not mean the values are the same in each cell line. As can be seen in Figure 17, 96-24 has a higher percentage of both MR and SG in its cells. Since both increase, the ratio remains relatively constant. This consistency in the ratio suggests that the amount of quinacrine stained is directly related to the amount of mitochondria in a cell. Figure 12 hints at this trend as well. This should also be investigated further with more data collection and further sorting.

Fig 11. MR Area vs. Cell Area in both cell lines seems to show correlation [Note: In this figure, one extremely large 96-24 value was removed].

0  

0.0002  

0.0004  

0.0006  

0.0008  

0.001  

0.0012  

0   0.002   0.004   0.006   0.008   0.01  

MR  Area  (m

m^2)  

Cell  Area  (mm^2)  

MR  Area  vs.  Cell  Area  

88-­‐503  

96-­‐24  

77B  

  16  

Fig 12. MR Area and Q Area seem correlated for both cell lines, although not perfectly.

Fig 13. There is slight correlation between the Q and Cell Area, especially in 88-503. [Note: In this figure, one extremely large 96-24 value was removed].

0.00E+00  

5.00E-­‐05  

1.00E-­‐04  

1.50E-­‐04  

2.00E-­‐04  

2.50E-­‐04  

3.00E-­‐04  

0.00E+00   2.00E-­‐04   4.00E-­‐04   6.00E-­‐04   8.00E-­‐04   1.00E-­‐03  

Q  Area  (mm^2)  

MR  Area  (mm^2)  

Q  Area  vs  MR  Area  

88-­‐503  

96-­‐24  

0.00E+00  

2.00E-­‐05  

4.00E-­‐05  

6.00E-­‐05  

8.00E-­‐05  

1.00E-­‐04  

1.20E-­‐04  

1.40E-­‐04  

1.60E-­‐04  

1.80E-­‐04  

0   0.001   0.002   0.003   0.004   0.005   0.006   0.007  

Q  Area  (mm^2)  

Cell  Area  (mm^2)  

Q  Area  vs.  Cell  Area  

88-­‐503  

96-­‐24  

  17  

Figure 14. This represents a positive correlation between the nucleus and cell area in both cell lines [Note: In this figure, one extremely large 96-24 value was removed].

Figure 15. This graph shows that the Q Area and Nucleus Area are also correlated [Note: In this figure, one extremely large 96-24 value was removed].

0.00E+00  

5.00E-­‐05  

1.00E-­‐04  

1.50E-­‐04  

2.00E-­‐04  

2.50E-­‐04  

3.00E-­‐04  

3.50E-­‐04  

4.00E-­‐04  

0   0.001   0.002   0.003   0.004   0.005   0.006   0.007  

Nucleus  Area  

Cell  Area  

Nucleus  vs.  Cell  Area  

88-­‐503  

96-­‐24  

0.00E+00  

2.00E-­‐05  

4.00E-­‐05  

6.00E-­‐05  

8.00E-­‐05  

1.00E-­‐04  

1.20E-­‐04  

1.40E-­‐04  

1.60E-­‐04  

1.80E-­‐04  

0.00E+00   7.00E-­‐05   1.40E-­‐04   2.10E-­‐04   2.80E-­‐04   3.50E-­‐04   4.20E-­‐04  

Q  Area  

Nucleus  Area  

Q  vs.  Nuclear  Area  

88-­‐503  

96-­‐24  

  18  

Figure 16. This graph shows the average MR:Q ratio for 88-503 and 96-24.

Figure 17. Shows the average MR and Q percentages out of the total cell for both cell lines. JC1 & MG (and Hoechst). 88-503

• JC1 Green/MG and Cell Area comparison shows correlation (Figure 18). • JC1 Green/MG and JC1 Red are very correlated, with an R2 value of about .81.

The linear relation has a slope of about .94 mm2 Green/Red Area (Figure 19).

0.00  

1.00  

2.00  

3.00  

4.00  

5.00  

6.00  

7.00  

MR:Q  

Cell  Line  

MR:Q  

88-­‐503  

96-­‐24  

0.00%  

5.00%  

10.00%  

15.00%  

20.00%  

25.00%  

30.00%  

MR  in  Cell   Q  in  cell  

Percentage  

MR  &  Q  Percents  in  Cell  Lines  

88-­‐503  

96-­‐24  

  19  

• JC1 Red vs. Cell Area data seems to be generally correlated (Figure 20). 96-24

• JC1 Green and Cell Area show slight correlation as well (Figure 18). • JC1 Green/MG and JC1 Red show fair correlation. Linear relation has a slope of

about 1.26 mm2 Green/Red Area with and R2 value of about .59 (Figure 19). • JC1 Red vs. Cell Area shows slight correlation, although there is quite a bit of

variance per cell area (Figure 20). In general, 88-503 shows more correlation with cell area than 96-24. All of the graphs do seem to show at least a vague positive correlation for both cell lines. Every cell had a JC1 RED:GREEN ratio of less than one. Another measurement taken for the JC1 data were the total stained area. The total stained area basically measured the total mitochondrial area. This was done by merging the red and green JC1 images to create one mitochondrial stain. Then this was compared to the green and red stained areas. Figure 21 shows the green stained area, including JC1 Green and MG, vs. the total stained area. As can be expected there is extreme correlation. The 88-503 data has an R2 value of about .92, and the 96-24 data has an R2 value that is nearly perfect and rounds up to 1. This makes sense because the green area of the JC1 stains the mitochondria with low membrane potential, and recent data includes MG, which stains the total mitochondria area. Thus it should be directly correlated to, if not the same as, the total mitochondrial area stained by JC1. The ratio of JC1 RED out of the total stain area was also taken. This ratio was also always less than one. For 88-503 the ratio was .67 ± .15 and for 96-24 it was .66 ±.24. Thus the ratio of high potential mitochondria out of the total mitochondria was similar between the two cells lines. The standard deviation accounts for variations between individual cells that may be under different stresses or in different parts of the life cycle. Figure 22 graphs the red area stained versus the total stained area for individual cells. As expected, there is correlation. However, much more variance is seen than in Figure 20, especially in 96-24. Figure 23 shows the ratio of red to green stain. This appears constant between the two cell lines, with the Red:Green ratio in 88-503 being .72 ± .16, and the value for 96-24 being .71 ± .27. Much more variance was seen in 96-24, which seems to be an ongoing trend. The similarity suggests that the amount of red stain, or the amount of mitochondrial area with high membrane potential, is constant per amount of mitochondria. Figure 24 confirms this constant ratio by showing the average percentages of green and red stain out of the total cell area for both cell lines. There was always more green that red. There was also a higher percentage of both for 88-503. 96-24 had a smaller percentage of both red and green stain, but it held a constant ratio. Figure 25 provides a visual on the distribution of the Red:Total mitochondrial area variation. Note that many cells are close to 100% red, or high membrane potential, mitochondria. On the other hand, some are very low (Figure 25). This would be interesting to further investigate and to attempt to subgroup.

  20  

In general this ratio of Red:Green stain for both 88-503 and 96-24, at about .71, seems fairly high. The red stain labels mitochondria with a high membrane potential. Having a membrane potential means the mitochondria is healthy and active because it means there is enzyme activity and the metabolic pathway is at work. Mitochondrial membrane potential is the driving force for ATP production (Pires da Neves et al. 2010). A lack of membrane potential may even correspond with apoptosis. High membrane potential, rather, corresponds to a high transcription rate (Pires da Neves et al. 2010). This also correlates with a high level of ATP. Future study could involve looking for a possible relationship between ATP and high membrane potential. The current stain used in lab for ATP is quinacrine. As mentioned above, the idea that quinacrine is staining only ATP is questionable. It also cannot be easily used with JC1, as both emit in green. Thus, a stain that labels ATP using different wavelengths would be ideal for this study. It would also be ideal to overlap with quinacrine to test quinacrine’s reliability.

Fig 18. Seems like there may be correlation between the JC1 Green/MG and Cell Area in both cells, but more so in 88-503 [Note: In this figure, one extreme 96-24 value was removed].

0.00E+00  

1.00E-­‐04  

2.00E-­‐04  

3.00E-­‐04  

4.00E-­‐04  

5.00E-­‐04  

6.00E-­‐04  

0   0.001   0.002   0.003   0.004   0.005   0.006   0.007   0.008  

JC1  GREEN/M

G  Area  (m

m^2)  

Cell  Area  (mm^2)  

JC1  GREEN/MG  Area  vs.  Cell  Area  

88-­‐503  

96-­‐24  

  21  

Fig 19. There is definite correlation between JC1 Green combined with MG versus JC1 Red. This is especially true in 88-503 but applies to 96-24 as well [Note: In this figure, one extreme 96-24 value was removed].

Fig 20. There is slight correlation between JC1 Red and the Cell Area in both cell lines. However, there is much variation around points and the relationship is not perfectly linear [Note: In this figure, one extreme 96-24 value was removed].

0.00E+00  

1.00E-­‐04  

2.00E-­‐04  

3.00E-­‐04  

4.00E-­‐04  

5.00E-­‐04  

6.00E-­‐04  

0.00E+00   8.00E-­‐05   1.60E-­‐04   2.40E-­‐04   3.20E-­‐04   4.00E-­‐04   4.80E-­‐04  

JC1  GREEN/M

G  Atea  (m

m^2)  

JC1  RED  Area  (mm^2)  

JC1  Green  with  MG  vs.  JC1  Red  Area  

88-­‐503  

96-­‐24  

0.00E+00  

5.00E-­‐05  

1.00E-­‐04  

1.50E-­‐04  

2.00E-­‐04  

2.50E-­‐04  

3.00E-­‐04  

3.50E-­‐04  

4.00E-­‐04  

4.50E-­‐04  

0   0.001   0.002   0.003   0.004   0.005   0.006   0.007   0.008  

JC1  RED  Area  (mm^2)  

Cell  Area  (mm^2)  

JC1  RED  Area  vs.  Cell  Area  

88-­‐503  

96-­‐24  

  22  

Figure 21. Shows the green JC1 Green and MG stained area vs. the total mitochondrial area [Note: In this figure, one extreme 96-24 value and one extreme 88-503 values were removed].

Figure 22. This graphs shows the red stained area vs. the total stained area [Note: In this figure, one extreme 96-24 value and one extreme 88-503 values were removed].

0.00E+00  

1.00E-­‐04  

2.00E-­‐04  

3.00E-­‐04  

4.00E-­‐04  

5.00E-­‐04  

6.00E-­‐04  

0.00E+00   1.00E-­‐04   2.00E-­‐04   3.00E-­‐04   4.00E-­‐04   5.00E-­‐04  

JC1  GREEN/M

G  Area  (m

m^2)  

Total  Stain  Area  (mm^2)  

JC1  GREEN  with  MG  Area  vs.  Total  Mitochondrial  Area  

88-­‐503  

96-­‐24  

0.00E+00  

5.00E-­‐05  

1.00E-­‐04  

1.50E-­‐04  

2.00E-­‐04  

2.50E-­‐04  

3.00E-­‐04  

3.50E-­‐04  

4.00E-­‐04  

4.50E-­‐04  

0.00E+00   1.00E-­‐04   2.00E-­‐04   3.00E-­‐04   4.00E-­‐04   5.00E-­‐04  

JC1  RED  Area  (mm^2)  

Total  Stain  Area  (mm^2)  

JC1  RED  vs.  Total  Mitochondrial  Area    

88-­‐503  

96-­‐24  

  23  

Figure 23. Shows the average red to green stain ratio for both cell lines.

Figure 24. Shows the average percentages of green stain and red stain out of the total cell area for both 88-503 and 96-24.

0.00  

0.20  

0.40  

0.60  

0.80  

1.00  

1.20  RED:GREEN  

Cell  Line  

JC1  RED:JC1  GREEN/MG  

88-­‐503  

96-­‐24  

0.00%  

2.00%  

4.00%  

6.00%  

8.00%  

10.00%  

12.00%  

14.00%  

16.00%  

18.00%  

20.00%  

 JC1  GREEN/MG   JC1  RED  

Percents  

JC1  GREEN/MG  &  JC1  RED  Percents  

88-­‐503  

96-­‐24  

  24  

Figure 25. Shows the ratio of the red area of the mitochondria to the area of the total mitochondria vs. the total cell area. Note that there is much variation in both 88-503 and 96-24. Nile Red (and Hoechst). 88-503

• NR Red and Cell Area are slightly correlated, although there is some variation per cell area (Figure 26). There must be some error in the staining or some other factor at play, because NR Red stains the cell membrane so this should be almost perfect correlation.

• NR Green and NR Red are definitely correlated, although there are some outliers (Figure 27).

• NR Green and Cell Area show a mutual increase, but there is much variation and no exact linear path can be traced (Figure 28).

96-24 • NR Red and Cell Area are correlated, but more data points from larger cells are

needed to confirm (Figure 26). • NR Green and NR Red are correlated, although there are few data points to

determine a definite pattern (Figure 27). • NR Green and Cell Area show vague correlation and look like they will increase

together, but again more data from larger cells is needed (Figure 28). Overall, the most correlation is seen in NR Green vs. NR Red Area in Figure 27. No exact correlation is seen between either fluorescence emission and cell area. However, the most correlation is always seen with 88-503. This may just be due to the fact that there are far less data points for 96-24. Further collection must be done here. Nonetheless, all graphs seem to show at least a vague positive correlation.

0  0.1  0.2  0.3  0.4  0.5  0.6  0.7  0.8  0.9  1  

0   0.001   0.002   0.003   0.004   0.005   0.006   0.007   0.008  

Red:Total  

Cell  Area  (mm^2)  

Red:Total  Stain  Area    vs.  Cell  Area  

88-­‐503  

96-­‐24  

  25  

Error was possible in this data set because some NR had additional MR stain. This staining protocol was being used at the beginning. However, the use of MR on top of NR was stopped because the two stains are labeling different things, making quantitative analysis difficult. This probably produced little error because comparison of cells with MR and without MR showed high correlation. Also, there may simply be error in the stain. For instance, often the NR Red stain was so diffuse that it was difficult to quantify. The concentration of stain used can be increased for future studies to improve data collection.

Fig 26. There is slight correlation between NR Red and the Cell Area in both cell lines [Note: In this figure, three extreme 88-503 values was removed].

0.00E+00  

1.00E-­‐04  

2.00E-­‐04  

3.00E-­‐04  

4.00E-­‐04  

5.00E-­‐04  

6.00E-­‐04  

7.00E-­‐04  

8.00E-­‐04  

0   0.001   0.002   0.003   0.004   0.005   0.006  

NR  Red  Area  (m

m^2)  

Cell  Area  (mm^2)  

NR  Red  vs.  Cell  Area  

88-­‐503  

96-­‐24  

  26  

Fig 27. There is a correlation between NR Green and NR Red Area in both cell lines. [Note: In this figure, three extreme 88-503 values was removed].

Fig 28. There is slight correlation between NR Green and the Cell Area in both cell lines. However, there is much variation around points [Note: In this figure, three extreme 88-503 values was removed]

0.00E+00  

2.00E-­‐05  

4.00E-­‐05  

6.00E-­‐05  

8.00E-­‐05  

1.00E-­‐04  

1.20E-­‐04  

1.40E-­‐04  

0.00E+00   2.00E-­‐04   4.00E-­‐04   6.00E-­‐04   8.00E-­‐04   1.00E-­‐03  

NR  Red  Area  (m

m^2)  

NR  Green  Area  (mm^2)  

NR  Green  vs.  Red  Area  

88-­‐503  

96-­‐24  

0.00E+00  

2.00E-­‐05  

4.00E-­‐05  

6.00E-­‐05  

8.00E-­‐05  

1.00E-­‐04  

1.20E-­‐04  

1.40E-­‐04  

0   0.001   0.002   0.003   0.004   0.005   0.006  

NR  Green  Area  (m

m^2)  

Cell  Area  (mm^2)  

NR  Green  vs.  Cell  Area  

88-­‐503  

96-­‐24  

  27  

Nucleus (Hoechst/SYBR Gold) Throughout analysis the nucleus (or nuclei) area was taken for every cell analyzed. Figure 29 displays a graph of these data versus the cell area for each individual cell. A clear trend is visible of a positive relationship between the nucleus and cell area for all cell lines. There is much variation, which could be due to error or random factors such as extra nuclei when a cell is about to split or an unhealthy cell curling in that has an unusually large nucleus are per cell area, etcetera. Again, finding a way to accurately differentiate between cells in different parts of the cell cycle may lead to further discoveries. Note also that 96-24 seems to be increasing at the fastest rate. Also, 77B seems to be remaining fairly constant, although there is still correlation. This may just be because less 77B cells have been analyzed, so the data set is not complete. It may also be due to the fact that 77B is DVLA-negative, whereas 88-503 and 96-24 are DVLA-positive. In other words, tumor cells may increase their nuclear area per cell area at a faster rate. Tumor cells may increase their nuclear composition to a greater extent as they grow.

Fig 29. The Nucleus Area vs. Cell Area for 96-24, 88-503, and 77B. All three cells show a positive increasing relationship. Cell Vesicles. One of the main focuses of this thesis was to research the extracellular vesicles that damselfish cells in vitro in order to explore the possibility that they play a role in the transport of vital organelles. This could lead to answers on how DVLA is transported between cells, an important step in understanding the mechanisms of infection of DVLA.

0  

0.00005  

0.0001  

0.00015  

0.0002  

0.00025  

0.0003  

0.00035  

0.0004  

0   0.002   0.004   0.006   0.008   0.01  

Nucleus  Area  (mm^2)  

Cell  Area  (mm^2)  

Nucleus  vs.  Cell  Area  

96-­‐24  

88-­‐503  

77b  

  28  

The main stain combinations worked with when looking for extracellular vesicles were: MitoRed and SYBR Gold; Quinacrine, MitoRed, and Hoechst; Nile Red and Hoechst, and JC1 and Hoechst. These stains were chosen because if such fluorescence is expressed in an extracellular area, it is viable and likely a vesicle. Thus, it eliminates uncertainty and the possibility that the cell fragment is merely debris. Also, large shed vesicles often “Contain mitochondria and lipid droplets together with ATP” (Falchi et al. 2012). Using stains that label mitochondria, lipid, and ATP, can thus highlight extracellular vesicles. Although staining is promising, further research must be conducted to determine definite means of determining when an image displays a vesicle. Several figures below show possibilities of extracellular vesicles being shed (Figure 30, 31, 32 & 33).

Fig 30. An 88-503 cell stained with Q & MR & H. Arrows indicate two possible vesicles. The presence of quinacrine suggests that they are active vesicles rather than just cell fragments.

  29  

Fig 31. An 88-503 cell stained with NR & MR & H. Arrow indicates possible vesicle. The green spots in the ‘vesicle’ are nonpolar lipids.

Fig 32. A 96-24 cell stained with JC1 & H. Arrows indicates possible vesicles. Close observation shows red spots in these ‘vesicles’, labeling high membrane potential.

  30  

Fig 33. A 96-24 cell stained with Q & MR & H. Arrow indicates a possible extracellular vesicle. This vesicle is disconnected from the cell, yet still displays some ATP, labeled in green. In order to study cell vesicles, certain adjustments were made to the previous methods. After the above possible vesicles and many others were spotted in flasks at 600x, a switch was made to higher magnification and resolution. This was done in two ways. One of these includes plating on a 35 mm glass bottom dish and the other was using oil immersion microscopy. These alterations allowed for more clear, high-intensity imaging. This was essential to obtain useful data on vesicles from images. Images were taken with these improvements using cell lines 88-503, 96-24, FX96-24, and 77B. However, finding vesicles in healthy cells was a slow process. To enhance data collection, another adjustment was made. In order to move forward in this research, an increase in vesicles was needed. This was accomplished by inducing apoptosis in cells by exposing cultures to UV. As cells are placed under stress, they often release extracellular vesicles. In fact, according to Falchi et al. release of microvesicles is thought to be a sign of apoptosis (2012). Vesicle shedding does occur from resting cells, but the rate increases greatly when the cell is stimulated (Cocucci et al. 2009). Thus, forced apoptosis presented an opportunity for further observation of shedding of extracellular vesicles. It should be again noted that this apoptosis was forced, and thus the data collected are from an atypical state. Images were taken of cells from cell lines 88-503, 96-24, FX96-24, and 77B in cultures that were not exposed to UV and cultures that were. These various cultures were stained with MR&SG, NR&H, JC1&H, and Q&MR&H. Data on the analyzed cells can be found bellow. Of the cells analyzed, the majority had one nucleus, as can be seen in Figure 34. The maximum number of nuclei in a cell was 6 nuclei (Figure 34). Of the many uninucleated cells, there was a range of number of vesicles coming off each cell. A clear representation of this can be seen in Figure 35. Cells with one nucleus were likely to

  31  

have 1 vesicle, less likely to have 2 vesicles, even less likely to have three vesicles, and so on (Figure 35).

Fig 34. Graph showing the number of cells having each number of nuclei.

Fig 35. Graph showing the range of the number of vesicles uninucleated cells can have. Figure 36 represents the average number of nuclei per cell for each cell line with and without UV exposure. The average number of nuclei per cell noticeably increased after UV exposure for each cell line (Figure 36). At first glace Figure 37 seems to match Figure 36. This is because Figure 37 graphs the average number of vesicle per cell, which follows the same trend as nuclei in that is increases with UV exposure. This holds true for every cell line (Figure 27).

0  20  40  60  80  100  120  140  160  180  

1   2   3   4   5   6  

#  Cells  

#  Nuclei  

Number  of  Cells  with  Different  Numbers  of  Nuclei  

0  10  20  30  40  50  60  70  80  90  

1   2   3   4   5   6   7  

#  Uninucleated  Cells  

#  Vesicles  

Number  of  Uninucleated  Cells  with  Various  Number  of  Vesicles  

  32  

Fig 36. Average number of nuclei per cell in each cell line with and without UV exposure.

Fig 37. Average number of vesicles per cell in each cell line with and without UV exposure. One observation that is quickly noticed when observing stained mitochondria in any of these cell lines is that mitochondria is not always elongated. In fact, combining all of the cell lines and the UV exposed and no UV cultures gives about a 50:50 divide on rounded versus elongated mitochondria (Figure 38). But this graph is deceiving because doesn’t take into account to variation seen in Figure 39. Figure 39 demonstrates that there is actually much variance from cell line to cell line and between unexposed and UV-

0.00  

1.00  

2.00  

3.00  

4.00  

5.00  

88-­‐503   96-­‐24   FX96-­‐24   77B  

Average  #  Nuclei  

Cell  Line  

Number  of  NUCLEI  in  Cell  Lines  with  and  without  UV  Exposure  

No  UV  

UV  

0.00  0.50  1.00  1.50  2.00  2.50  3.00  3.50  4.00  4.50  

88-­‐503   96-­‐24   FX96-­‐24   77B  

Average  Num

ber  of  Vesicles  

Cell  Line  

Number  of  VESICLES  in  Cell  Lines  with  and  without  UV  Exposure  

No  UV  

UV  

  33  

exposed cells. For instance, 88-503 was also the only cell like that decreased the percent of cells with elongated mitochondria after being exposed to UV, although only slightly (Figure 39). 96-24, FX96-24, and 77B all saw an increase in percent of cells with elongated mitochondria with UV (Figure 39). FX96-24 is the only cell line that makes a noticeable jump, and that is a large increase in percentage of cells with elongated mitochondria after exposure to UV (Figure 39). This is unusual because healthy mitochondria is usually thought to be elongated, whereas unhealthy mitochondria is more likely to become balled up. It is possible that the FX96-24 that was not exposed to the UV was unhappy for other reasons such as low confluency. Further data collection should be done in this area to see if these trends continue. If they do factors such as certain cell lines lack of DVLA or the retrovirus could be at play.

Fig 38. Percentage of total cells with rounded and elongated mitochondrial patterns.

Fig 39. Percentage of cells in various cell lines and under different conditions (Not exposed to UV or UV-exposed) that have elongated mitochondria. The remaining percentage would be rounded or balled-up mitochondria.

0%  

20%  

40%  

60%  

80%  

100%  

%  Cells  

Rounded    Elongated  

Percent  of  Cells  with  Elongated  and  Rounded  Mitochondria  

0.00%  

20.00%  

40.00%  

60.00%  

80.00%  

88-­‐503   96-­‐24   FX96-­‐24   77B  

%  of  Elongated  Cells  

Cell  Line  

Percentage  of  Cells  with  Elongated  Mitochondria  

No  UV  

UV  

  34  

After splitting various cells into elongated versus rounded mitochondrial patterns, it was necessary to explore the possibility of a relationship to the number of vesicles shed per cell. This can be seen in Figure 40. As can be seen, there is little difference except for a slightly higher average number of vesicles coming off of cells with elongated mitochondria (Figure 40). However, this difference is not significant. It must also be noted that a major source of error here is that often an entire cell could not fit in an image. Thus it is possible that vesicles were missed and that these numbers are not precise.

Fig 40. Average number of vesicles per cell with elongated or rounded mitochondria of various cell lines. The next item explored was the relationship between the total area of all the vesicles coming off one cell in comparison to the total area of the nuclei of that cell. A scatter plot of this including all cell lines and cells both exposed and not exposed to UV can be seen in Figure 41. On average all of the cell lines seemed to see and increase in vesicle area with an increase in nuclear area. In fact, slope analysis shows the four cell lines following a similar rate of mutual vesicle and nuclei area increase (Figure 41). Regardless an exact correlation between the two does not exist.

0.00  0.50  1.00  1.50  2.00  2.50  3.00  3.50  4.00  

Elongated   Rounded  

Average  #  Vesicles  

Mitochondrial  Pattern  

Number  of  Vesicles  per  Cell  with  Elongated  and  Rounded  Mitochondria  

88-­‐503  

96-­‐24  

FX96-­‐24  

77B  

  35  

Fig 41. Total area of all vesicles shedding from a cell versus the area of the nuclei of that cell. Not that 1 extreme FX96-24 outlier was removed as well as 4 extreme 96-24 outliers. Next the composition of vesicles was observed in detail. For instance, the presence of SYBR Gold in vesicles was studied. This is important because if the vesicles are transporting nucleoids to other cells, they could indeed be transporting mitochondrial DNA, leading to a possible answer of how DVLA is transferred. It was found an average of 57% of all vesicles shed have SYBR Gold. Figure 42 details the variation from cell line to cell line and between UV versus non-UV exposed cell lines. Overall, this percentage is slightly higher after being exposed to UV. Cells under stressful conditions may be more likely to shed vesicles with nucleoids to preserve nuclear information. The percentage of vesicles with SG increases after UV exposure for every cell line except 88-503 (Figure 42). This is similar to what happened with the elongated mitochondria. Every cell line except 88-503 increased the percentage of cells with elongated mitochondria after UV exposure (Figure 39). Likewise, FX96-24 again made the biggest increase after exposure to UV. Looking at Figure 39 and 42 together emphasizes how similar these trends are. This makes it seem like the percentage of cells with elongated mitochondria maybe be related to the percentage of vesicles shed containing SG. Without UV exposure, vesicles with SG came 73% from rounded cells and 27% from elongated. With UV exposure, 34% of vesicles with SG came from rounded and 66% came from elongated. Despite these data, it needs to be acknowledged that there are many factors that could be causing this to occur, and elongated mitochondria and vesicles with SG may not be directly correlated.

0.00E+00  

1.00E-­‐05  

2.00E-­‐05  

3.00E-­‐05  

4.00E-­‐05  

5.00E-­‐05  

6.00E-­‐05  

7.00E-­‐05  

0.00E+00   8.00E-­‐05   1.60E-­‐04   2.40E-­‐04   3.20E-­‐04   4.00E-­‐04  

Total  Area  of  Vesicles  (mm^2)  

Total  Area  of  Nuclei  (mm^2)  

Total  Area  of  Vesicles  vs.  the  Total  Area  of  Nuclei    

FX96-­‐24  

77B  

88-­‐503  

96-­‐24  

  36  

Fig 42. Percentage of the vesicles shed both with UV exposure and without that have SG.

Fig 43. Percentage of the vesicles shed both with UV exposure and without that have Nile Red stain, or nonpolar lipids. Another interesting observation was made when studying the percentage of vesicles with nonpolar lipids in them, which is stained green by Nile Red. The most noticeable difference between cells exposed and not exposed to UV is seen in 77B, which experienced a significant decrease in the percentage of vesicles with nonpolar lipids after UV exposure (Figure 43).

0%  

10%  

20%  

30%  

40%  

50%  

60%  

70%  

80%  

88-­‐503   96-­‐24   FX96-­‐24   77B  

%  Vesicles  with  SG  

Cell  Line  

Percentage  of  Vesicles  with  SYBR  Gold  with  and  without  UV  

No  UV  

UV  

0%  10%  20%  30%  40%  50%  60%  70%  80%  90%  100%  

88-­‐503   96-­‐24   FX96-­‐24   77B  

%  Vesicles  with  NR  Green  

Cell  Line  

Percent  of  Vesicles  with  NR  Green  with  and  without  UV  Exposure  

No  UV  

UV  

  37  

These data were used again but in more specific counts. Figure 44 graphs the average number of nonpolar lipids per vesicle per each cell line with and without UV exposure. With UV exposure, every cell line sees a slight increase in the number of nonpolar lipids per vesicle except 77B. Oddly, 88-503 and 96-24 remain fairly constant, whereas FX96-24 has the largest change with a significant increase, and 77B actually has a decrease in the number of nonpolar lipids per vesicle (Figure 44). This is likely because 77B is the furthest from a tumor cell and thus the least resilient to the stressful conditions of UV radiation. As apoptosis is induced in some of the cells of 77B, the nonpolar lipids decrease. As previously noted, 77B has been surprisingly resilient in terms of mitochondria health and nucleoid abundance in vesicles, but perhaps lipids are the first to notice a significant decrease with the induction of apoptosis.

Fig 44. Average number of nonpolar lipids in each vesicle per cell line with and without UV exposure. Next JC1 was examined. JC1 labels regular mitochondria green and mitochondria with high membrane potential red. Thus, red JC1 staining in vesicles means active mitochondria is being transferred. When working with JC1 with and without UV exposure for all of the cell lines, red staining was imaged in many vesicles. Data for this can be seen in Figures 45 and 46. Figure 45 shows the percentage of vesicles for various cell lines that were not exposed to UV with a majority JC1 red or JC1 green. Figure 46 does the same except for cells that have been exposed to UV. A point to be noted is that the majority of vesicles are dominated by the green stain of JC1, as was expected (Figure 45&46). Note that just because a vesicle is dominated by a color does not mean the other color is not there. In fact, the vast majority of vesicles had both JC1 green and red staining as can be seen in Figure 47. Without UV exposure almost every vesicle had both stains, and with UV there was just a slight decrease in the amount of 88-503 and 96-24 vesicles that had both. Also, some vesicles had an equal amount of JC1 red and green staining so they were excluded from this graph.

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88-­‐503   96-­‐24   FX96-­‐24   77B  

#  Nonpolar  Lipids  

Cell  Line  

Average  #  Nonpolar  Lipids  per  Vesicle    

No  UV  

UV  

  38  

Another point to note is that with UV exposure, 77B was greatly altered and saw a significant increase in red staining in vesicles after exposure to UV (Figure 46). This may be because 77B is the most sensitive to UV exposure and began apoptotic steps earlier, leading to shedding of many vesicles of active mitochondria that the cell needs to get rid of. The transportation of active material like high membrane potential mitochondria is vital to the research question of what the vesicles are transporting.

Fig 45. Percentage of vesicles with mostly JC1 red staining and with mostly JC1 green staining for various cell lines with no UV exposure.

Fig 46. Percentage of vesicles with mostly JC1 red staining and with mostly JC1 green staining for various cell lines with UV exposure.

 

0%  

20%  

40%  

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100%  

JC1  Red   JC1  Green  

%  Vesicles    

Dominant  Stain  in  Vesicle  

Percentage  of  Vesicles  Dominated  by  Each  Stain  with  No  UV  Exposure  

88-­‐503  

96-­‐24  

FX96-­‐24  

77B  

0%  

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60%  

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JC1  Red   JC1  Green  

%  Vesicles  

Dominant  Stain  in  Vesicle  

Percentage  of  Vesicles  Dominated  by  Each  Stain  with  UV  Exposure  

88-­‐503  

96-­‐24  

FX96-­‐24  

77B  

  39  

Fig 47. Percentage of vesicles with both JC1 green and red staining present in various cell lines with and without UV exposure. Note that no significant data was found using the quinacrine stain in terms of vesicles. Quinacrine was stained with MitoRed and Hoechst. Many vesicles were observed, but few with quinacrine and no trend was observed. There were, however, some interesting observations about the actual staining pattern. Firstly, quinacrine mostly stained along the edges of the cell. This could be expected because ATP is associated with polarized mitochondria (Falchi 2013). However, quinacrine also stained vacuoles within cells. The amount of vacuoles increased with UV exposure, usually leading increases in quinacrine in the central cell. It has been noted that "Quinacrine has been shown to bind to a variety of polyanions, not only ATP, and to accumulate within acidic intracellular compartments" (Akopova et al. 2012). This explains why Quinacrine was often found staining entire cell vacuoles, which are slightly acidic. This can be observed in Figure 48.

Fig 48. Image of 96-24 cells. (Note these cells were exposed to UV for 1 min 1 day before this picture) a Quinacrine pattern is normal in central cell. b Notice the vacuoles where the arrow is pointing. These vacuoles were precisely filled by quinacrine in figure 48a.

0%  

20%  

40%  

60%  

80%  

100%  

88-­‐503   96-­‐24   FX96-­‐24   77B  

%  Vesicles  with  Both  Stains  

Cell  Line  

Percentage  of  Vesicles  with  both  JC1  Red  and  Green  Staining  

No  UV  

UV  

A   B  

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Cells with modified Mitochondria. Additional work was done on cells with modified mitochondria using MU1 and MR2. MU1 and MR2 include a DNA fragment that codes for a fluorescent protein transfected into their genome. As a result, they express fluorescence without staining. This fluorescent mutation is a breakthrough technology that could open up future research possibilities. First, however, the cell lines must be corrected so they properly express fluorescence in the appropriate cell area. MU1 and MR2 are meant to express fluorescence wherever there is mitochondria, in green and red respectively. MU1 codes for a green fluorescent protein. Where it stains the mitochondria, it appears similar to the stain MitoGreen. This mutation has successfully been applied to 96-24. An example of this can be seen in Figure 49 below. The MU1 mutation has also been attempted in the 77B cell line. The correlation between the expression of MU1 in 77B and the actual mitochondrial area was studied. To test 77B MU1, the cultures were stained with MitoRed and Hoechst. On first observations, the MU1 appeared fairly correlated. However, there were some slight discrepancies. Correlation was seen anywhere where the green from the MU1 mutation and the red from the MR stain lined up, or where the image was yellow. For most cells, an overlap was visible, especially in the center close to the nucleus. However, the MU1 green fluorescence was often overexpressed in the center cell body and lacking where the cell and mitochondria were elongated. An example of this can be seen in Figure 50. Another trend was that not all of the 77B cells successfully incorporated the MU1 gene, so they lacked expression of the green fluorescent (Figure 51). There was also a combination of cells with normal, elongated mitochondria and some with balled-up mitochondria (Figure 52). This variation was on a cell-to-cell basis. Further observations to distinguish between these cells with varying mitochondrial morphologies should be made. Quantitative analysis was also for 77B MU1 was also done using Excel. The average ratio of green fluorescence to red, or MU1:MR, was 0.73 ± .14. Every analyzed cell expressed more red than green fluorescence. This suggests that although there is much overlap, and although the images appear correlated, the MU1 in 77B is not causing all of the mitochondria to express the green fluorescence. There is also the possibility, however, that the MR stain is overexpressing or leaking, and that the MU1 green expression is actually a better representation of the mitochondria area. More data needs to be collected and analyzed to reduce the standard deviation and to get more absolute results.

  41  

Fig 49. Shows a 96-24 cell with the MU1 DNA incorporated. a RGB image of a 96-24 MU1 cell stained with MitoRed and Hoechst. Yellow area demonstrates a correlation between the MU1 expression and the MitoRed stain. There is great correlation. There are a couple of small discrepancies, but this is likely due to MR stain error. Not also that the MU1 mutation is not fully incorporated into the bottom cell, so it appears mostly red. b The MU1 mutation expressing the green fluorescent in the 96-24 cell. c The MitoRed stain, expressed in red fluorescence.

A  

B   C  

  42  

Fig 50. Shows a 77B cell with the MU1 DNA incorporated. a RGB image of a 77B MU1 cell stained with MitoRed and Hoechst. Yellow area demonstrates a correlation between the MU1 expression and the MitoRed stain. There is correlation, especially in the center, with slight discrepancies on the cell extensions. b The MU1 mutation expressing the green fluorescent in the 77B cell. Note the heavy expression in the central cell body. c The MitoRed stain, expressed in red fluorescence.

A  

B   C  

  43  

Fig 51. 77B MU1 cells stained with MitoRed and Hoechst. Image shows that some cells, but not all, received and integrated the fragment of DNA coding for the green fluorescent. These are the cells that appear yellow, due to overlap with the MitoRed. A couple of cells have mitochondria that only show the red fluorescence. This proves that not all of 77B cells in this culture are MU1.

Fig 52. 77B MU1 cells stained with MitoRed and Hoechst. Image shows the variation in mitochondria morphology from cell to cell. Some show elongated mitochondria that appear normal. Other cells have small balls of mitochondria.

  44  

This research also dealt with MR2, which includes a DNA fragment insertion that codes for a red fluorescent protein. If MR2 was successful integrated into a cells genome, all of the cell’s mitochondria would express the red fluorescence. Thus, it would overlap with MitoGreen, again resulting in yellow. MR2 was inserted into both 77B and 96-24. To test 77B and 96-24 MR2, the cell lines were stained with MitoGreen and Hoechst. For the 77B MR2, a lack of correlation was seen. Whenever overlap, or yellow, was visible, it was in the central cell. The MR2 mutation, or the red fluorescence expression, rarely spread to the branches. The red was heavily concentrated in the center, and often appeared in balled-up patterns, not following the elongated patterns of the MitoGreen stain. Examples of this can be seen in Figures 53 and 54. Quantitative analysis reveled a MR1:MG ratio of 0.91 ± .33. Theoretically, if the red was being expressed everywhere where mitochondria is present, or everywhere where the MitoGreen is staining, these should match up perfectly, with a 1:1 ratio. Thus, .91 seems fairly accurate. However, there is a large standard deviation and much variance from cell to cell. For instance, in one cell there was about double the amount of green expressed as red, with 16.67% MR2 and 33.33% MG. In another cell there was much more red than green, with 37.18% MR2 and 23.44% MG. In summary, there is a wide range of results in 77B MR2 that must be narrowed down with further data collection and analysis, as well as by distinguishing between variations in cells.

Fig 53. Shows a 77B cell with the MR2 DNA incorporated. a RGB image of a 77B MR2 cell stained with MitoGreen and Hoechst. Yellow area demonstrates a correlation

A  

B   C    

  45  

between the MR expression and the MitoGreen stain. There is only correlation in the center. b The MR2 mutation expressing the red fluorescent. It is only expressed in the central cell body and does not extend into the branches. c The MitoGreen stain, expressed in green fluorescence.

Fig 54. Another 77B cell with the MR2 DNA incorporated. a RGB image of a 77B MR2 cell stained with MitoGreen and Hoechst. Yellow area demonstrates a correlation between the MR expression and the MitoGreen stain. There is an overexpression of red fluorescence in the center that does not extend to the mitochondria in the branches, which Mito Green stains. b The MR mutation expressing the red fluorescent. It is essentially just expressed in the cell center. Note that much of this staining appeared to be in little balls. c The MitoGreen stain. For 96-24 MR2, there was again little correlation. There were some areas of overlap where yellow was seen. However, there were also cells where red and green were expressed in opposite places. An example of this can be seen in Figure 55. Figure 55 shows MR2 expressing red in balled-up patterns. This pattern of red circular fluorescence was seen in multiple 96-24 MR2 cells. This at first seemed to represent balled-up mitochondria, but it did not correlate with the elongated MitoGreen patterns.

A  

B   C  

  46  

Thus, the circular pattern found in some 96-24 MR2 cells is likely not due to mitochondrial pattern as the MitoGreen still stained elongated mitochondria. Also, in 96-24 MR2, the red fluorescence often seemed to extend beyond the mitochondria, seeping into other areas (Figure 56). For instance, a faint red could often be seen where the nucleus was located. An example of this can be seen in Figure 56b. Again, quantitative analysis was done for 96-24 MR2. The MR2:MG ratio found was 1.34 ± .51. This demonstrates an extremely large standard deviation, but there was also limited data to work with. More data analysis on 96-24 MR2 cells is necessary.

Fig 55. A 96-24 cell with the MR2 DNA incorporated. A RGB image of a 96-24 MR2 cell stained with MitoGreen and Hoechst. Yellow area demonstrates a correlation between the MR2 expression and the MitoGreen stain. There is some overlap in the center of the cell. b The MR2 mutation expressing the red fluorescent. Note the circular shaped heavy expression of red. c The MitoGreen stain. Note that where there are gaps in the MitoGreen stain lines up perfectly with where there is heavy red expression. In other words, there is little correlation, and in some places there is actually opposite expression.

A  

B   C  

  47  

Fig 56. 96-24 cells with the MR2 DNA incorporated. a RGB image of 96-24 MR2 cells stained with MitoGreen and Hoechst. Yellow area demonstrates a correlation between the MR2 expression and the MitoGreen stain. There is some overlap in the center of the cell, but it is minimal. The majority of green and red are located in different areas of the cell. b The MR2 mutation expressing the red fluorescent. Note the faintness of the red, and also how it seems to blend outside of the mitochondria. In fact, some red fluorescence appears in the spot for the nucleus in both cells. c The MitoGreen stain. Again, there is very little correlation.

A  

B   C  

  48  

In summary, the most correlation is visible in 96-24 MU1. The majority of images merged appeared in yellow, representing a precise overlap between the green mutation and MR stain. There were a fair amount of cells, however, that did not express the mutation. The second most correlation was seen in 77B MU1. It is fairly precise, with the majority of merged images appearing yellow, representing an overlap of the green fluorescence from the protein and the MitoRed stain. To accurately quantify these data, it must be compared to 96-24 MU1. Further analysis must be done between these two cell lines. In contrast to the 77B MU1, both cell lines with the MR2 mutation showed less correlation and more variability amongst data. In 77B MR2, there is fair correlation in the center of most cells, which appear yellow due to an overlap of the red fluorescence from the protein and MitoGreen. However, this red is highly centralized and does not extend to the mitochondria branching away from the nucleus. For 96-24 MR2, there is some yellow, but overall there is even less correlation than in the previous two cases. In fact, in many cases the red fluorescence from the protein appears exactly where the MitoGreen does not stain. The quantitative analysis found that in the 77B cell line, for both MU1 and MR2, there was more of the stain than of the mutation expressed. In other words there was a MU1:MR or MR2:MG ratio of less than one. Analysis of 96-24 MR2, found however, that on average there was more of the transfected gene expressed than the stain, or MG. Thus, the average MR2:MG ratio was greater than one. These results, however, included large standard deviations and were calculated from limited data. Thus, more data collection is necessary to find significant results. As a side note, several other stains, such as Nile Red and Quinacrine, were attempted on the various cultures with modified mitochondria to test the possibility that the fluorescence may be imbedded in something other than the mitochondria. These results did not show correlation. Further studies in this area may be conducted to collect conclusive data. Further research must be done on all of these modified cell lines to perfect them before they can contribute to the overall research project. This includes more data collection and analysis. For instance, in the near-future attempts may be made to differentiate between cells with balled-up mitochondria and cells with elongated mitochondria. Also, cell lines may be purified to strive for all cells to express the transfected DNA, and to eliminate cells that do not express the fluorescence.

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DISCUSSION There are several cellular trends of various healthy and tumor-derived cell lines from bicolor damselfish worth noting. Three cell lines were analyzed for general cellular patterns: 88-503, 96-24, and 77B. They differ slightly phenotypically, but their general cellular trends are similar. Firstly, for all cells analyzed except for those exposed to UV, and average of about 1/3 were multinucleated. Of the multinucleated cells, a little under a half were undergoing mitosis or had two nuclei of approximately equal size. The other multinucleated cells were unhealthy either because they were apoptotic or pathological. Various organelle patterns were also studied for these three cell lines, and wherever there was correlation it applied to all of them. For example, mitochondria area and cell area are strongly correlated in all three. Nucleus and cell area are also strongly correlated. Other organelles such as nucleoids and high membrane potential mitochondria maybe correlated to cell area as well, but the results were too inconclusive to know. After general cell analysis FX96-24, another cell line, was also used. FX96-24 was used along with 96-24, 88-503, and 77b for studying vesicles. Vesicles were challenging to study for many reasons. First, it is difficult to define what is and what is not a vesicle, making much of the data collection subjective. Also, working with the oil immersion objective made phase contrast not an option, which further limited defining vesicles. Working with the oil immersion objective meant working at 1000x, so often part of a cell got cut out from an image. This meant that some of the data, such as the number of vesicles per cell, could not be accurate. Working with UV was also challenging because the confluency and timing had to be perfect to ensure there were still attached cells to image. For example, 77B lasts only about half as long after induced apoptosis as the other cell lines, and if that time is exceeded there will be no cells left to image. Also, trying to segregate data was difficult because putting cells on UV radiation does not make them apoptotic. There were healthy cells within the UV exposed cultures and apoptotic cells within the normal cultures. This complicates categorizing for data analysis, so more emphasis should be placed on this in the future. Overall, UV exposure caused an average increase in both nuclei and vesicles in all cell lines. UV exposure caused an increase in the percentage of cells with elongated mitochondria for all cell lines except 88-503. This was most prevalently seen in FX96-24. The percentage of vesicles shed that contained nucleoids also increased for all cell lines except 88-503 and increased most for FX96-24. This presented an interesting trend. Nonpolar lipids only saw a significant change in abundance in vesicles with 77B, which experienced a decrease after UV exposure. Mitochondria in all vesicles were predominately inactive. However, the vast majority of vesicles had at least some mitochondria with high membrane potential. Quinacrine did not display significant trends

  50  

in the vesicles. It was observed that vacuoles increased with UV exposure, leading to an increase in quinacrine in those vacuoles. Future work must be done with vesicles, as this is just the beginning of this project. Due to some of the challenges above and other, new techniques should be attempted to continue this study. First, Electron Microscopy can be used to detail the shapes and sizes of vesicles accurately. Other techniques such as centrifugation can be used to isolate extracellular vesicles. Also, studying vesicles without apoptosis would be ideal because if DVLA is spreading through vesicles it is likely when tumor cells are proliferating, not dying. Different methods of apoptosis induction or other forms of vesicle enhancement can be attempted. Also, it when a vesicle is seen right next to a cell, it would be interesting to figure out a way to know if it is coming to or leaving the cell. Observations are also difficult because “Upon shedding, many vesicles do not remain intact in the extracellular space for long” (Cocucci et al. 2009). Thus, time-lapse photography, though challenging, could prove promising. Future observations focusing in this area are necessary. The study of extracellular vesicles is a promising lead to the question of how DVLA is transported. However, regardless of if it proves influential in this area, it is important to study extracellular vesicles extensively because they are prevalent in these cultures and are surely important in maintaining a balanced a healthy damselfish cell culture. ________________________________________________________________________ Acknowledgements. I am grateful to Dr. Michael C. Schmale, who has been my mentor this year, for putting in endless time and effort toward this project despite both of our busy schedules and for instilling in me his passion for the pursuit of knowledge, to Dr. Gary Hitchcock for being a thesis committee member and for supporting me throughout my research and my entire time at the University of Miami, to Dr. Lynne A. Fieber for being a part of my thesis committee and taking the time to read through and critique my work, to Dr. Patrick Gibbs for sharing his research and life knowledge with me and teaching me to question everything, to Dayana Vidal for patiently teaching me lab techniques and for her contagious humor every day, to Merly for being my daily motivator and inspiration, and to the Rosenstiel School of Marine and Atmospheric Science for giving me the resources and the opportunity to undertake this research experience. ___________________________________________________________________

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