Author Archives: Reyn Yoshioka

Rev and GO GO

Let’s go day four!

Today we continued our forays into bioinformatics using IPython, R, DAVID, and Revigo!

 

Rev and GO

Jeeze these titles are bad.

Today (or yesterday) we did a lot of stuff, mainly looking at differentially expressed genes in our sea star transcriptome.  Just about all we did is in my IPython Notebook.

I even was able to do most of my stuff in IPython with R!  There was very little use of excel except to open the files… I don’t get that awk business of dropping columns…

Until later today!

-R

 

Exploring the Galaxy

Let’s go day 2!

Our stuff in IPython:

https://www.dropbox.com/s/c6in770slyci8nd/Let%27s%20Go%20Day%20Two.ipynb

So to join our blastx output with the uniprot database, we used SQLshare:

SELECT * FROM [closek@gmail.com].[seastar_clc_uniprot_sprot_2.tab]blast
  Left join
  [sr320@washington.edu].[uniprot-reviewed_wGO_010714]unp
  on
  blast.Column3=unp.Entry

This gave us a new joined table :D

Specify what you want to see with

SELECT * FROM [closek@gmail.com].[seastar_clc_uniprot_sprot_2.tab]blast
  Left join
  [sr320@washington.edu].[uniprot-reviewed_wGO_010714]unp
  on
  blast.Column3=unp.Entry
  Where
  [Protein names] like ‘%interle%’

In this case it’s proteins with names like interle (interleukins?).

So now we’re looking at GO IDs…

SELECT * FROM [closek@gmail.com].[seastar_clc_uniprot_sprot_2.tab]blast
  Left join
  [sr320@washington.edu].[SPID and GO Numbers]go
  on
  blast.Column3=go.SPID

There were GO numbers in the last set, but this separates them out for easier use in the next steps and matches them to the SPIDs.

Now we’re matching the GO numbers up to GO slim terms to see the implicated processes:

SELECT * FROM [closek@gmail.com].[seastar_clc_uniprot_sprot_2.tab]blast
  Left join
  [sr320@washington.edu].[SPID and GO Numbers]go
  on
  blast.Column3=go.SPID
  Left join
  [sr320@washington.edu].[Go_to_Goslim]slim
  on
  go.GOID=slim.GO_id
  where
  aspect =‘P’  where aspect focuses on ‘P’ which represents biological processes (cellular processes = ‘C’,

Now to make a pretty plot!

Brought in the table into excel in a csv format.  Then selected all of the data and made a pivot table, which made counts of each time a GOslim term was used.  Using the chart maker, I could make a pie chart of the different processes that were represented.  Note that this does not represent the number of contigs, as there were multiple GOslim terms matched to single contigs (so we didn’t remove any duplicates).

SSTransGOslimplot_reynsattempt

OOOOOH PRETTY COLORS

 

Galaxy fun:

https://usegalaxy.org/u/ryosh/h/unnamed-history

After uploading the GOslim results onto galaxy, we could use a number of tools for exploring the data!  See the link :D

 

 

Strangled by IPython

Today we started grappling with terminal and IPython to try BLASTing…

It was quite a learning experience, trying to understand how a computer “thinks” to do what we want it do (along with bioinformatics techniques).

Before we went to IPython, we started with terminal, in which we set up our directories in Maxene.  Our process:

  1. say i love terminal – made our computer say “I love terminal”
  2. say please don’t fail me – made our computer beg for mercy
  3. pwd – present working directory, shows what directory we’re in at the time
  4. cd /Applications/blast – change our directory to the blast folder in applications
  5. ls – list, shows what’s in the current directory
  6. mkdir DB – make a database called “DB” OH NO!  We need admin permissions -_____-
  7. So… cd ../ to move up through directories
  8. Then move down directories… cd Users and so forth until we reach our needed folders in maxene
  9. In my own folder in our classes, mkdir DB to make the database DB!  Yay!
  10. Now ipython notebook to get whisked off to IPython

-_____-

Sadly, my IPython is not working with me and isn’t exporting an html properly so this will be updated as soon as that’s figured out…

In all honesty, today was pretty fun and I’m stoked to try using IPython to execute R statistics.  A new day tomorrow!

Snip, Snip: It’s All About Sterility

Just a note:  Today’s post is a two-fer, because 1) we worked until about midnight last night and I failed to make a post D:, and 2) today was very similar to yesterday.

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Giving a face to what we want to save (or at the very least understand). This is actually inaccurate since the mouth is underneath…

And no, although the title’s pun was intended, this post has nothing to do with vasectomies.  It’s about careful planning and maintaining sterility when you’re collecting samples and doing other things in the lab.

As you may know from mine and other posts, we just received 54 Pisaster sea stars that were being held at Merrowstone for an experiment.  They were collected from Ruby Beach on two different dates and were assumed to be healthy – completely free of SSWD pathogen.  This would have allowed us to do experiments to help us determine SSWD’s pathogen, comparing those that were naive and those that were infected with a putative pathogen.  However, what we thought were naive stars turned out to be infected, preventing their use in the experiment.  We had to choose between disposing them (what a waste!) or sampling from them, and so they were brought to FHL from Marrowstone for us to sample.

For our tissue sampling, we decided to be very careful (even more so than usual) and to use a very well laid-out process.  Because we were interested in seeing which tissues are targeted by the putative pathogen, we maintained sterility between stars and tissues (within the same star) to the best of our abilities.  It can be described kind of in recipe form:

Tools:

  • Plastic tray
  • Hypodermic needle (for sampling fluid)
  • Scalpel handle and blades
  • Dissections scissors
  • Plastic rulers
  • Forceps
  • Gloves
  • Paper towels
  • Tubes and bags
  • The trifecta: 10% bleach solution, reverse osmosis (RO) water, 95% ethanol (EtOH)
  • Sterile seawater (SSW).  I would actually argue this is super-sterile seawater (SSSW) since we made our best effort to have it really clean:  It was filtered to 0.22 μm and autoclaved.  But anyway…
  • Well plates
  • Alcohol lamp
  • Dry ice

Between each star:

  1. NEW GLOVES
  2. Remove tissue and bleach tray
  3. Sanitize tools:  scalpel handle, dissection scissors, forceps (bleach → RO water → EtOH → flame), ruler (just bleach: you can’t flame plastic safely…)
  4. NEW NEEDLE
  5. NEW SCALPEL BLADE

Between each tissue:

  1. Rinse tissue in SSSW in well plate (different well for each tissue!)
  2. Again, sanitize tools:  scalpel handle, dissection scissors, forceps (bleach → RO water → EtOH → flame), ruler (just bleach).
  3. Store sample as appropriate.  In most cases it was quick freezing in dry ice.
IMG_6196_small

Rinsing tissue in a well plate of SSSW. We didn’t want any tissue other than what we wanted in the tubes, but some contamination is inevitable.

This may seem excessive (I certainly hope it’s not), but being extremely careful with our sampling gave us confident in the utility of our samples.  It could have been faster or less expensive (could have not used a fresh blade between each star).  However, this would have sacrificed our trust in our methods, and if our samples didn’t work out we could needed to sample more – a luxury we might not have in the future.  Just a bit more work now can save us much more in the future.

 

 

 

Just a Bunch of Bitter Crabs

Today we had two excellent lectures by Lisa and Steve.  The commander gave a lecture on protistan diseases such as Bonamiasis, Haplosporidiosis, and Bitter Crab Syndrome (my favorite of them all).  It was neat to realize that there is almost certainly tons of disease in the world, but we mostly only notice them in organisms of commercial value.  Imagine what must be going on right under our noses!

Steve also gave an very though-provoking lecture on QPX and how molecular methods can give us insight to the relationship between the pathogen and the host as modulated by the environment.  It’s becoming increasingly clear that seeing the story of the data is complex – there are multiple ways to interpret even the same data.  It’s also clear that advances in molecular techniques are letting us see even more into host-pathogen relationships than ever before.

Unfortunately, I missed much of the laby-oyster labwork for today.  Morgan, Allison, Collin, and I began our set-up of a sea star experiment using sea stars that we had hoped were healthy but (as we recently found) were not.  We are now trying to make the best use of an unplanned situation – saving and sampling as much of these sea stars as we can.  Our only other option would be to simply euthanize and dispose of them, but it would be wasteful when we could do so much more.  More to come on this later!

(Gel) Bandz a Make Her Dance

Carolyn’s lecture today focused on examples of different pathogen groups.  The first group we looked at was fungi, using Abalone Shell Mycosis as a study case.  Marine fungi tend to be rare or unnoticed, so a marine fungal disease is quite interesting.  The disease had a large impact on New Zealand, where it impacted important Pāua (abalone) species such as Haliotis australis, H. virginea, and H. iris.  Because of the sand-like mineral deposits that form in the lesions caused by the fungi, it was originally believed that the disease lesions were actually physical damage from sand.  However, histological analyses (among others) revealed fungal hyphae in the lesion, implicating a fungus identified as from the class Deuteromycotina.  Another disease-causing marine fungus is Asperigillus sydowii of the sea fan Gorgonia ventalina.

The next group looked at diseases caused by metazoans.  I really loved this section – the pathogen was a sabellid polychaete (annelid worm) in abalone.  The polychaete was brought into California from South Africa via imported Haliotis midae and spread by the aquaculture industry.  It’s a really neat pathogen, forming mucus tubes along the leading edge of the abalone shell, which the host then covers up with its own shell.  This causes abnormal growth of the shell and weakens it – making for very sad abalone.  Even though it spread into the marine environment through aquaculture outflow, it was apparently eradicated in natural populations by culling gastropods – it was an incredible success story.  Neat fact: the worm is a simultaneous and self-fertilizing hermaphrodite, meaning that it only takes one to start an infection!

The last group we looked at was bacteria, specifically Nocardia crassostreae and Vibrio harveyi.  Nocardiosis affects Pacific Oysters (Crassostrea gigas) in which they are implicated with summer mortality on the West Coast but not in Japan.  Vibrio harveyi presents great case of the disease triangle in European abalone (Haliotis tuberculata).  The disease is temperature sensitive with a change of 1ºC eliciting a large increase in mortality.  The disease also depends on the host, which is more susceptible while spawning.  Lastly, Vibrio harveyi isn’t homogenous in itself – depending on the presence of a plasmid, the bacterium may or may not be virulent.

For lab, we started our experiment looking at the possibility of using oysters as a biocontrol of eelgrass laby.  Oysters potentially could filter out laby from the water column and make them less likely to infect eelgrass.  We had four groups in our experiment in triplicate, each having a total volume of 225 mL in a 250 mL beaker.  Two of the groups had oysters (10 per beaker) as treatment groups, and the other two had none.  Two also had laby in them (at a currently unknown concentration due to the difficulty of getting concentrated cultures).  All of them were treated with pen+strep to limit other growth and had a spin bar to maintain gas exchange.  Our set up was as follows:

Laby Control (none)
Oysters Ultimate treatment! Better have no laby at all…
Control (none) Should give us a Laby baseline There should be nothing happening here at all…
IMG_6033_small

Amanda showing us some cultured laby we’re using for our experiment

IMG_6060_edit

Rachel, Ruth, and Monica prepping our experiment

From each  beaker we’re taking 1000 μL water samples to quantify the amount of laby in each of them at 0, 1, 2, 4, 8, and 24 hours.  After the completion of this portion of the experiment, we’ll be putting in eelgrass shoots to see if we can get infection!  What we might hope to see is that the treatment with the oyster will have less (or no) infection as compared to the laby only treatment.  We’ll also be dissecting the oysters and blotting some of their tissue onto plates to see if we can get viable laby.

IMG_6063_small

Our set-up experiment on the gigantic stirrer plates.

IMG_6036_editsmall

Laby!  Behold the spindle-shaped cells and mucus net.

We also looked at the gels that Allison and Lauren ran using the same DNA extracts and PCR primers as we did two (?) days ago.  For the most part our results were the same, easing our minds that any issues we saw were not from operator error and cluing us in that problems were probably with the primers themselves.  The WC primers for laby performed quite nicely again, producing the same bright bands as before.  It was a nice confirmation that I didn’t mess up my first PCR O.O

Not very basic

Today was (almost) all about ocean acidification!  First things first, we had a lecture from Carolyn about ocean acidification (OA) and its consequences for marine life, of course focusing on disease.

Our oceans are (generally) not actually acidic, on average having a pH over 8, which is basic.  However, the dissolution of CO2 into the ocean results in the creation of H+ ions, decreasing the pH and essentially “acidifying” the ocean.  This can affect many aspects of marine biology, ranging from behavior to reproduction to diseases.  Unfortunately, the results of OA are not clear cut and depend on the organism you’re looking at and the aspect of its life you’re interested in.  For example, many shell-producing organisms suffer from OA because it’s harder to produce and maintain a shell in acidic conditions (H+ competes with Ca2+ for carbonate ions, forming bicarbonate instead of calcium carbonate).  On the other hand, a study by Miller et al (2013, http://onlinelibrary.wiley.com/doi/10.1111/gcb.12259/abstract) found that increased CO2 actually increased reproduction in anemonefish.

hoegh-guldberg et al 2007 fig 1 A

Figure 1A from Hoegh-Guldberg et al 2007 showing the dissolution of CO2 into the ocean and the negative relationship between atmospheric CO2 and carbonate (doi: 10.1126/science.1152509)

Carolyn also shared with us some of her and her colleagues’ research on OA’s trans-generational impacts on mollusc disease.  The resounding message was that impacts depend on your study organism and that changes in pH seem to be more problematic of the pH levels themselves.  As with everything, it’s complicated!

IMG_6020_small

Getting a tour of the OA Lab’s filtering system

Lecture was followed by a tour of the OA Lab.  The facilities afford researchers a large amount of control on the water chemistry of their studies.  The incoming water is quite thoroughly filtered (though not quite enough to filter out viral sized particles, but anyway) and the chemistry (pH, CO2, alkalinity, etc.) are routinely checked.  One thing that the facility can’t quite control is the salinity of the water.  The system cannot react fast enough to rapid changes in ambient salinity such as rain events.  However, they are careful to measure the changes in salinity in case anything goes strangely – in a way it’s like how it’s easier (though not really better) to apologize than to ask for permission.  In the end, this illustrates that in science, as with all things that require finite resources, there is a trade off things you can and can’t do.  Just as how organisms have trade-offs when dealing with OA and fighting infection!

IMG_6022_small

A typical set up in the OA Lab. Each cooler contains eight separate containers which each have their own water input. There are also pH electrodes, heaters, and refrigerators for maintaining the water properties during the studies. The lamp is used since this particular study is looking at algae.

After our (as usual glorious) lunch, we had another lecture where we explored case studies looking at changes in host susceptibility, resistance, and tolerance.  I found case study two particularly interesting – hyperparasitism of RLO in abalone by phage (viruses) improved the outlook for abalone infected by the syndrome.  The possibility of phage therapy in combating diseases is fascinating especially in a field where disease management is really difficult.

We closed our day by splitting off to do different things that needed doing – running more PCRs with our sea star and laby primers, setting up our oyster laby experiment (more to come, but in the meanwhile see Amanda’s post), and for me pulling out oysters that may be used to assess levels of sea star wasting disease pathogen in the field.  I’m really excited to see where that goes.  Who knows, we may get a new tool to study the epizootic!

Gellin’ like a felon

Today we were back onto our lecture track, bright and early at 8:30 am (I know, not that bad).  Carolyn gave us a very interesting lecture on invertebrate immunity, which is completely new to me (kind of ridiculous considering the research I’ve done revolved around coral disease).  The most evolutionary basal (?, I know primitive is an unpopular term) category of immune systems is innate immunity, which is generally non-specific and short-term.  While different types of pathogens may be recognized and addressed differently, the response is general and cannot distinguish closely related taxa.  The more sophisticated system, adaptive immunity, is considered characteristic of vertebrates.  In adaptive immunity, pathogens can be recognized and addressed specifically with a significant amount of memory.  There is some evidence, though, that invertebrates can have a form of quasi-adaptive immunity – for example, shrimp exposed to white spot syndrome virus are more resistant to infection as compared to naive shrimp, even about a month later.  It seems, though, that the mechanisms for this memory is different than the vertebrate adaptive immunity we’re more familiar with.

After lecture, we head over to lab 10 where we got our PCR reactions going.  The repetitive nature of pipetting was quite calming.  It went very smoothly, and we were able to get our reactions set up and going in the thermocyclers quite quickly.  Again, I was completely new to this except for reading about it in genetics.  I was very excited, since PCR is such a powerful tool that opens the door to many other molecular techniques.

IMG_5968_small

Collin and Morgan adding extracted DNA to their reaction tubes

Sarah and I used the West Coast 18S primers for amplifying laby DNA.  We made our master mix using a rule that I’ve never hear of and is quite ingenious – we made mix for 10% more reactions than we needed to, which ensures we have enough reagent for all of the reactions (as some is inevitably lost to pipetting error).  After that was all done, Lisa and Collin programmed the thermocyclers to get our reactions going.

AND THEN THERE WAS LUNCH!

Post-lunch, Steve gave a lecture on host response in pathogen-host interactions.  It was great to consider how the host changes during and after infection from both an individual and population level.  Disease is a powerful driver of natural selection – it does not just kill off individuals, but it changes the genetics of the populations it encounters!  This has significant implications of this on disease impacts and the future of disease.

IMG_5989_small

Casey getting the deadly ethidium bromide into our agarose gels.

IMG_5992_edit

Monica pouring the agarose into the gel mold

IMG_5995_small

A gel plate setting up with the well combs in

After the lecture, we finished off the day with running gels of our PCR products!  If all goes well, this will let us screen the samples for the presence/absence of the pathogen (laby for eelgrass and putative virus for the sea stars).

SHABAM!  Here’s the gel for the laby DNA (except for one culture on the sea star plate).  It looks like Sarah’s and my primer pair worked out pretty well, showing nice bands on the UH (unhealthy) eelgrass extractions and a few (and dim?!) bands on the ICH (Healthy) extractions.  Our negative came out clean as well!

LabyGel_small

The laby electrophoresis gel