Author Archives: Amanda Shore

RCN and more

I am so grateful to be able to attend the EIMD RCN Meeting. It was really nice to see familiar faces (Bette Willis, Katie Sutherland, Melissa Garren) and of course it was good to meet new people and put a face to a familiar name.

Of the full 15 mins talks from yesterday, I think that I liked Katie Sutherland’s the best. Shifting targets of pathogens is something that our lab has struggled with during the process of discovering tho three bacteria that can cause tissue loss in the Hawaiian rice coral. Also, could Acropora palmata be developing mechanisms to control Serratia marcescens infections?!?! I had not heard of this phenomenon. Makes me wonder if the Coral Probiotic Hypothesis is at work.

Updates from the Oyster Filtration Experiment Part 2. Yesterday was 48hrs of oysters in the beakers, so they were removed and replace with the eelgrass. We dissected and saved tissue from 3 out of the 10 oysters from each beaker. Casey, Cody and Rachel noticed that many of the oysters didn’t look healthy. Instead of the digestive glands looking orangeish-pink, they were often brown to black looking. We did save i tissue slice for histology. I hope that the oysters were healthy enough to feed normally.

Today when we photographed the eelgrass, there were very small dark spots only in the SL treatment. I am really excited to see if these  dark spots really turn into progressing lesions.

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Oyster Filtration Experiment Part 2 – Day 2

The day started with me wanting to do some PCR, but, alas, the Laby WC primers were left in Seattle during Team Laby’s Epic qPCR Adventure. So instead, I did what I prob should have been doing in the first place, writing methods and doing statistics. As expected, there was no significant difference between the time points for the SOL treatment.
Today, Team Laby sampled and froze water at the 24hr time mark. I also spotted some water on an SSA plate to look for Laby growth. I will do this for the 48hr time point as well. Tomorrow marks the end of the oyster filtration part of the experiment, I hope that we won’t miss too many talks tomorrow while we dissect oysters and get the eelgrass in the beakers.

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Oyster Filtration Experiment – Take 2

Today, Rachel, Casey,Cody and I set up the second round of the Oyster Filtration Experiment.

The collection of Laby was alot more efficient this time around and I tried to use pipetting of the Laby off the plates to my advantage. Instead of adding Laby to the pool from straight off the plate scrapers, Casey herded most of the Laby to the middle of each plate. Then I would add 200uL filtered seawater to the plate and pipette up the suspended cells. The pool of Laby in the 50mL conical of SSA had much less clumping, I didn’t even need to add tween to a small sample to get a good hemocytometer count. After scraping prob 15 plates, we got a final concentration of Laby at 2.16×10^5 cells per mL. This is a similar concentration to what was added to the first filtration experiment.

This time around we are going to leave the oysters in for 48hrs instead of 24hrs. This is because at 24hrs, we started to see a downward trend in the SOL treatment. Perhaps 24hrs was simply not enough time to see the downward trend, if indeed that is what is happening.

 

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qPCR data!

qPCR data! It’s pretty cool. Also, today I learned that error bars and log scales don’t get along. The graph below is just the water samples that were collected at these 3 time points. We didn’t qPCR the other time points because of time and lack of DNA extraction kits at FHL. It looks like there was some Laby in the seawater that was used, although that is weird since this water was filtered. However, at T0 there is a lot of Laby in the treatments that we added Laby to (hooray) and more importantly there is a similar amount of Laby at T0 for the SL and SOL treatments. Levels of Laby in the SL treatment don’t seem to be decreasing over time, but they might be in the SOL treatment. I still need to run some stats. The consistent levels of Laby in the SL treatment is interesting because we thought that the Laby may be adhering to the sides of the beaker and that we might not get any cells from collection of water only.

 

qPCR

SW = Seawater only                                                             SO = Seawater and Oysters                                                 SL = Seawater and Laby                                                    SOL = Seawater and Oysters and Laby

 

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Back from Seattle

Today, we traveled back from Seattle with some lab supplies. So no lab/data to report yet. Tomorrow, I am going to examine the qPCR data thoroughly. Which means tomorrow’s post should be much more exciting. Lisa was kind enough to take us by the the Lake Washington ship channel in hopes to see jumping salmon. We did see some salmon, but none were jumping.

This evening, I went to the public seminar by Dr. Lisa Levin on deep sea industrialization. That was fantastic. I didn’t know to what extent that humans were already mining, harvesting, and unfortunately destroying really precious and unknown ecosystems at ocean floor. It also was rather unsettling to see photographs of the carnage that trawling can have on the ocean floor. Poor deep sea corals. Dr. Levin reported that some deep sea corals have been recorded as being over 4000 years old. FOUR THOUSAND. That is crazy. Here is a link to a NOAA website report about it.

http://coralreef.noaa.gov/deepseacorals/about/facts/dsc_oldest.html

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We are the qPCR masters.

Data!…coming soon to a classroom near you! Here is a mere taste of the data we have. Check out the R^2 on that one!

Standard curve of the first plate of  today's qPCR.

Standard curve of the first plate of today’s qPCR.

 

Today was spent in the lab at UW doing science (see title above). Then we got to see (& hold) abalone, squat lobsters, and other cool inverts.

 

2014-08-11 15.17.37

 

2014-08-11 15.17.10  2014-08-11 16.12.08 2014-08-11 16.15.27 2014-08-11 16.20.09 2014-08-11 16.23.33

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last ‘official’ day of the computer lab computers hating me

TEAM LABY!!! I streaked out Laby strain 8.16.D cultures onto 8 plates of SSA. Hopefully, by Sunday we will have enough Laby to do an infection trial with different concentrations of Laby. I hope that this will help us determine what concentration of Laby we should use for a second oyster filtration experiment.

I didn’t get a whole lot accomplished today computer wise but I do have I task to complete that I think will be very interesting. I am pulled out the contigs that were classified as bacterial in Galaxy. Then I reran the  BLAST of just these contigs but instead of a single (the top scoring) hit, I told it to give give me the top 50 hits for each contigs. With this information, I plan to see if I gene is only giving bacterial hits of if simply the top hit just happened to be characterizatino of that gene in a bacterium. This should give us an idea of actual bacterial contamination.

 

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interesting Laby PCR

Sorry everyone. I meant to past this about two days ago and just now got a chance to do so. R: Below is a gel of PCR (with Laby WC primers) on the serial dilution of Laby + SW as well as the water samples at T0 and T24 (first replicate of each treatment only). The top row of 0-10 is DNA extraction of serial dilution via boil prep. The bottom row of 0-10 is DNA extraction of serial dilution via DNeasy kit.

D: Both DNA extraction methods work. However, Lisa told me today that we got more DNeasy kits in, so the boil method won’t be needed. I think it is nice to know that the boil method works on Laby for future reference. It looks like the limit of Laby detection by cPCR is 10^3 cells per mL, because there are no bands for either DNA extraction method from 10^-2 and lower. I think that this is weird and that we should have seen bands further along the dilution series. One possible explanation is that clumps of Laby in the undiluted were not broken up so that no cells (or very few) actually made it into the next tube.  The really interesting results are not in the dilution series but in the actual water samples collected. For T0, we only got a PCR band in treatments were we added Laby (SL and SOL). Sweet. Even more interesting, at T24, Laby was detected in the beakers without oysters but Laby was NOT detected it the beaker with the oysters. This pattern is what we would expect if the oysters really are filtering out the Laby. However, an alternative explanation is that by this time the Laby have all stuck to a surface of some kind and were not picked up when we sampled the water from the beaker. The second explanation is prob more likely because the eelgrass in all the beakers looked funky, despite the oysters. We will have a better understanding af what is going on in the eelgrass after histology and image analysis.

LabyGel_Dilutions

SL = DNA ladder       0 = 10^0 (aka undiluted) SW + Laby    1 = 10^-1 SW + Laby                       2 = 10^-2 SW +Laby      3 = 10^-3 SW +Laby                       4 = 10^-4 SW + Laby      5 = 10^-5 SW + Laby                      6 = 10^-6 SW +Laby        7 = 10^-7 SW + Laby                      8 = 10^-8 SW + Laby      9 = 10^-9 SW + Laby                    10 = 10^-10 SW + Laby S = SW only                                          SO = SW plus Oyster    SL = SW plus Laby          SOL = SW plus Oyster plus Laby T0 = 0 hr collection                          T24 = 24 hr collection (+) = Laby DNA                                                         (-) = NTC

http://imgs.xkcd.com/comics/compiling.png

I should have just done this today. Anyway, David still was unagreeable so I continued this data mining process by downloading Stephen’s output file. The rest is below.

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!say ‘I love python’

But I am not sure that python loves me.

Between not being able to install the R package onto Ipython before lunch and then the David webserver not processing my data input, I have no pretty graphs/charts/etc to post. I do however have the 10 genes from the transcriptome that I think are interesting. I think some are interesting because they may be related to immunity in ways that you might not think about and are not normally listed for immune function.

1) Histidine Biosynthesis Process – While histidine is a essential amino acid, it is a precursor for histamine, the chemical that is released in high concentrations during an inflammatory response. It will be interesting to see if this contig is highly expressed in the virus exposed group.

2) Microtubule cytoskeleton organization process – DNA viruses need to get inside the nucleus in order to replicate. Often viruses travel along these cytosolic microtubules to get to the nucleus. Also, as virus starts to bud from the cell, structure deteriorates, so cells may need to upregulate cytoskeleton proteins to help repair damage from viral lysis/budding.

3)  Peptidoglycan metabolic process – BACTERIAL CELL WALLS!! this really shouldn’t be listed unless there is bacterial contamination. Eukaryotic cells do not synthesize peptidoglycan. Although, this gene could be in a pathway that in bacteria leads to peptidoglycan but in eukaryotes leads to synthesis of some other complex macromolecule.

4) Plasma membrane repair – This goes along with #2.

5) Cytokine production – essential for any immune response

6) pattern recognition receptors – obvious

7) Toll-like receptor – obvious

8) Ossification process – Is the seastar trying to repair its ossiciles during infection?

9) Osteoblast differentiation – This goes with #8

And finally my favorite…

10) Natural killer cell differentiation – A hallmark of adaptive immunity but crosses the bridge into innate immunity. Natural killer cells are responsible for screening virally infected cells and triggering apoptosis, not through phagocytosis, but by inducing pathways or by directly lysing cells by injecting cytotoxic chemicals. I don’t know that natural killer cells have been documented in inveurtabrates. Could the hemocytes in the seastar have this function during viral infection? I think that would be an amazing discovery.

Below is my IPython notebook from today.

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