# Life Aquatic 2014 EIMD

Alright, here it is.

We had some good times. Hope you all are well!

# Wrapping up

Hope you all saw Queen B kill it at the VMAs last night! With class over, it might be a while before any of you get to reading notebook posts, but I wanted to post an update on the sea star ISH since not everyone was involved in that project.

On Friday we grabbed Carolyn and Colleen to examine the sea star slides, but unfortunately it seems like the counter stain wasn’t very effective and we couldn’t really see the tissue cross sections on any of the 12 star ISH slides well at all.

treated (sick) star

We did spend some time examining the H&E slides and got some good pictures.

H&E

H&E

Have an amazing summer and good luck to those of you starting school this week!

# One Last Post…

This may very well be my very last notebook post.. I know, so sad.  The paper is coming together wonderfully and we pretty much have way too many awesome stories to do them all justice (TLRs, Complement cascades, WNT signaling, the list goes on).  But I suppose that’s a good problem to have.  Everyone’s presentations this morning were wonderful.  It’s great to know that we all got such awesome projects done in such a short time.  I’m going to miss FHL, and all of my wonderful classmates (I have to be sappy and include this).  Looking forward to continued collaborations with you all!!

# Wnt Signaling KEGG Pathway

Below is the the KEGG pathway for the Wnt Signaling Pathway in purple sea urchins (green). I have added all the contegs found significantly enriched in the Pycnopodia  transcriptome. They are in the red and blue boxes. The numbers after each term show the log fold change (red = negative, blue = positive). between the animals with clinical signs and those without. I have not looked through the other annotated genes yet for to see if there are more relating to the wnt signaling pathway there.

Echinoderm_WntPathway_KEGG_SS

Here is my working copy of the gene list I am working from. I have not added all my references in yet but have UniProt information and some of the references included.

Contigs_Wnt_8-20-14

# Two recent tasks, including some R code!

In addition to hashing out the writing plan and starting the writing itself, which has been a terrific group effort, the past couple days have consisted of two main tasks.

First, I went through the transcriptome that had been blasted against the nucleotide database to remove any bacterial sequences with an e-value of less than 1e-200. We had agreed that these sequences would most likely represent contamination as the sequencing method targeted mRNA with polyA tails, which would not include bacteria. It turns out that there was an e-value threshold around 1e-179 before all the remaining, lowest e-values were zeros. I removed 1102 sequences with the following R code:

phel5<-read.csv(“Phel_clc_blastn_nt_edit.csv”) # this is the nucleotide blasted transcriptome that I edited to contain fewer columsn – the contig names are the key result from this code anyway so it’s fine
length(phel5$e) # 10768 total phel5$tax
summary(phel5$tax) levels(phel5$tax)
hist(phel5$e) # How many to take out? 1102 – same as ipython. This code makes a data frame of the REMOVED contigs. my.data.frame2 <- subset(phel5, tax == “Bacteria” & e < 1e-200) length(my.data.frame2$tax)
my.data.frame2$e write.csv(my.data.frame2,file=”Phel_clc_blastn_nt_removed.csv”) # This code makes a data frame of the final file (final data frame) without the REMOVED values: all those that aren’t bacteria + those that are bacteria but have e > 1e-200 my.data.frame <- subset(phel5, tax !=(“Bacteria”)) summary(my.data.frame$tax)
my.data.frame3 <- subset(phel5, tax ==”Bacteria” & e > 1e-200)
my.data.frame4<-rbind(my.data.frame,my.data.frame3)
length(my.data.frame4\$tax) # 9666

#length of #4 should = 10768-1102 = 9666
10768-1102

# Write final file to directory
write.csv(my.data.frame4,file=”Phel_clc_blastn_nt_nobact.csv”)

Steven then checked the fasta file to see whether this process had removed the unusually large contains, which was mostly the case. Ultimately, this process led to removing approximately 1000 contains from the transcriptome file of ~ 30,000 contains that we have been using as the basis of our analyses.

• This will affect our characterization of the transcriptome (e.g. species distributions, gene annotations), which is good timing as we’re working on that now
• It will not affect the enrichment analyses based on DEGs with SPIDs as none of the bacterial sequences removed belonged to the SPID-annotated DEGs

The second major thing I’ve been working on is sorting through the differentially expressed genes in the enriched processes that map to the Toll pathway. This has been a good way to learn a lot more about the details of the Toll pathway, and above all the variability between species as well as the gaps in the knowledge!

# Life Aquatic with Team Labby (feat. Team Transcriptome)

Today (8/19/14) we continued to work on our paper. Evidently at one point Casey came looking for me and I missed her. Supposedly this is not the first time something like this has happened to which my colleagues responded by asking each other “Where’s Cody?” As it so happens this question has been asked by enough colleagues to “catch on” as it were. I find this surprising. As we were watching life Aquatic Last Night someone in the movie said “Where’s Cody?” A good time was had by all. All this is to say that I don’t remember actively seeking out places where people will not be able to find me so I don’t really know what the solution to this predicament would be. Suggestions?

# Puzzlin’ Away With Team Labby

Today (8/18/14)  We continued to work on all of our projects. Casey and I made a video. I thought it turned out well. We continued working on all our puzzles depicted below. And of course, we continued working on summarizing the results of our experiment. On the whole it is coming along nicely and I am learning lots by reading through so many different papers. It is really fun to be able to put faces to the names of people who have written the papers I am reading. The RCN meeting was really eye opening in that sense. Taking a step back for a moment, the RCN was not only a really exciting opportunity to meet many different scientists involved in really cool project it was also just a really cool way to cap off an amazing experience here at Friday Harbor Labs.

This is a puzzle of a shipwreck

This puzzle shows 2 different views of surface of the Earth. This is also one of those puzzles that is made up of many tiny little pictures. Cool. But difficult.

This puzzle, to my knowledge, has not yet been assembled but depicts a turtle.

This puzzle is currently in the process of being assembled. More to follow.

So it’s been a few days since I last posted (whoops), but I’ve been busy writing up what we have for the sea star transcriptome and in particular what complement cascade genes we have.  Echinoderms were already described as having two proteins involved in the complement cascade: C3 and C2/Bf, however we found two more which were significantly deferentially expressed: Ficolin-2 and Properdin.  Both of these are proteins involved in alternate activation of the complement cascade system.  Looks like the infected stars are definitely responding to something though we’re still working at getting the full picture of how they’re responding and to what.

# This is what it sounds like when you speak in hashtags

I’m allowed to have an opinion, and I think that people just sound ridiculous when actually saying “hashtag.” Call me old fashioned, but I prefer to save it for the post.

# Integrating the integrins

We’re finishing up the sea star ISH this week! This experiment has been going pretty smoothly, other than having to track down some emergency sheep serum today. We’ve added some abalone slides to the mix too, so we have 18 in situ hybridizations in total for counter staining and visualizing under the microscope tomorrow.

The real fun today was dicing up the cell adhesion story hidden in the Pycnopodia helianthoides transcriptome. I had to do a lot of reading and searching to really start understanding focal adhesion complexes and how they involve different proteins and downstream processes, so I started building that database of papers and stuck them in my folder on Google Drive.

I also wanted to better understand which focal adhesion genes change expression, and how the coelomocytes are responding to disease. It makes intuitive sense that focal adhesion might play a role in the clotting response we’re seeing from changes in the coagulation pathway. Let me paint a picture: fibronectin is an abundantly soluble protein in the extracellular matrix (ECM), although not physiologically active until self-assembled into fibrils. It binds to integrin receptors on the cell surface as well as extracellular matrix components such as collagen, fibrin, and heparan sulfate proteoglycans (Pancov 2002). Understanding the backdrop that the extracellular fibronectin matrix scaffolding plays in cell adhesion is important, but the interesting changes in gene expression are also at the cell-surface level: what focal adhesion receptor and substrate genes are changing and what signal pathways might be affected?

Integrins are the transmembrane proteins that make up an important part of the focal adhesion complex on the cell membrane, binding the cell to the ECM and setting off a potential inside-out signaling event between cell and ECM (Widmaier et al 2012). There’s a plethora of proteins that can interact at the focal adhesion junction.

The following table is a list of interacting proteins I pulled from Plow et al, 2000:

 Ligand Integrin Adenovirus penton base protein αvβ3, αvβ5 Bone sialoprotein αvβ3, αvβ5 Borrelia burgdorferi αIIbβ3 Candida albicans αMβ2 Collagens α1β1, α2β1, α11β1, αIbβ3 Denatured collagen α5β1, αvβ3, αIIbβ3 Cytotactin/tenascin-C α8β1, α9β1, αvβ3, αvβ6 Decorsin αIIbβ3 Disintegrins αvβ3, αIIbβ3 E cadherin αEβ7 Echovirus 1 α2β1 Epiligrin α3β1 Factor X αMβ2 Fibronectin α2β1, α3β1, α4β1, α4β7, α5β1, α8β1, αvβ1, αvβ3, αvβ5, αvβ6, αvβ8, αIIbβ3 Fibrinogen α5β1, αMβ2, αvβ3, αxβ2, αIIbβ3 HIV Tat protein αvβ3, αvβ5 iC3b αMβ2, αxβ2 ICAM-1 αLβ2, αMβ2 ICAM-2,3,4,5 αLβ2 Invasin α3β1, α4β1, α5β1, α6β1 Laminin α1β1, α2β1, α6β1, α7β1, α6β4, αvβ3 MAdCAM-1 α4β7 Matrix metalloproteinase-2 αvβ3 Neutrophil inhibitory factor αMβ2 Osteopontin αvβ3 Plasminogen αIIbβ3 Prothrombin αvβ3, αIIbβ3 Sperm fertilin α6β1 Thrombospondin α3β1, αvβ3, αIIbβ3 VCAM-1 α4β1, α4β7 Vitronectin αvβ1, αvβ3, αvβ5, αIIbβ3 von Willebrand factor αvβ3, αIIbβ3

So, that’s cool. You might recognize some proteins in that list. Why are integrins and focal adhesion complexes important?

We see transcriptome-wide changes in at least 24 integrins or integrin-binding genes:

 Protein names log2Fold Change pvalue Entry Length (aa) Disintegrin and metalloproteinase domain-containing protein 10 (ADAM 10) 2.77 1.42E-07 Q8JIY1 749 A disintegrin and metalloproteinase with thrombospondin motifs 3 (ADAM-TS 3) 3.77 6.09E-13 O15072 1205 Disintegrin and metalloproteinase domain-containing protein 12 (ADAM 12) 4.17 3.68E-14 Q61824 903 A disintegrin and metalloproteinase with thrombospondin motifs 6 (ADAM-TS 6) -2.33 0.002229 Q9UKP5 1117 A disintegrin and metalloproteinase with thrombospondin motifs 13 (ADAM-TS 13) (vWF-cleaving protease) 7.96 1.97E-16 Q76LX8 1427 Sushi/vWF, EGF and pentraxin domain-containing protein 1 (Polydom) 2.20 0.00026 A2AVA0 3567 Sushi/vWF, EGF and pentraxin domain-containing protein 1 (Polydom) 4.20 1.75E-06 A2AVA0 3567 Sushi/vWF, EGF and pentraxin domain-containing protein 1 (Polydom) 1.61 1.26E-05 A2AVA0 3567 Sushi/vWF, EGF and pentraxin domain-containing protein 1 (Polydom) -1.91 0.005433 A2AVA0 3567 Integrin beta-PS 1.74 0.007869 P11584 846 Integrin alpha-4 (CD antigen CD49d) 3.07 6.60E-09 Q00651 1039 Integrin alpha-4 (CD antigen CD49d) 3.63 6.34E-06 Q00651 1039 Integrin beta-1 (Fibronectin receptor subunit beta) (CD antigen CD29) -1.40 0.001249 B0FYY4 798 Matrix metalloproteinase-19 (MMP-19) 4.22 3.85E-06 Q9JHI0 527 Matrix metalloproteinase-24 (MMP-24) 2.24 0.000174 Q9R0S2 618 Collagenase 3 (MMP-13) 3.39 2.10E-05 O77656 471 Collagenase 3 (MMP-13) 10.84 3.86E-43 O77656 471 Stromelysin-1  (MMP-3) 3.97 2.12E-06 P28863 478 Collagenase 3 (MMP-13) 7.82 1.48E-18 O77656 471 Matrix metalloproteinase-17 (MMP-17) 4.08 8.08E-09 Q9ULZ9 603 Matrix metalloproteinase-16 (MMP-16) 3.43 7.61E-07 Q9WTR0 607

A lot of these proteins pop up as important clotting or anticlotting responses, especially sushi, ADAM proteins, and MMPs. It may be reasonable to think more in depth about the role that changes in focal adhesion have on signaling events. How are the cells, specifically the coelomocytes, responding to this infection?

Side note! In my search today I came across a really cool protein called integrin-linked kinase (ILK). In addition to being an awesome part of the focal adhesion complex, it’s a biochemically inactive kinase…. it doesn’t phosphorylate proteins! Here’s a phylogenetic tree I generated in String with ILK (first, left-most column of green and orange) and its known interacting proteins.