>UBC Seminar – Dr. Dawn Bowdish, McMaster University

>[This talk was given by a good friend, Dr. Dawn Bowdish – and is WAY outside of the topics that I normally cover. However, there is some interesting work with SNPs which is worth mentioning, if you can get past the non-genomic part at the start – which I suggest. As always, mistakes are my misunderstanding of the topic – not the speakers!]

Talk title: The class A scavenger receptors are associated with host defense towards Mycobacteium tuberculosis.

Lab URL: http://www.bowdish.ca/lab

Post-doc was done at oxford, where most of the work that will be presented today was done.
1.The role of the scavenger receptors in Mycobacterium tuberculosis in infection
2.Polymorphisms in scavenger receptors and susceptibility to M. Tuberculosis infection
3.The role of the cytoplasmic tail in scavenger receptor signalling
4.Evolution of scavenger receptor domains.

Macrophages are beautiful cells. They don’t have a single form – you know it when you see it. Paraphrased: ‘phooi to t-cells.’

[at this point, the projector died. Dawn offers to tell macrophage stories… Someone wants to know all about Oxford. “It was very Harry Potter.” AV people mess around in the back….]

Macrophages are central to everything she studies. They are an integral part of mammalian biology:

  • Embryonic development, organ structure
  • chronic disease
  • genetic diseases
  • infectious disease
  • autoimmunity
  • cancer

Macrophages receptors are indicators of phenotype, function and biomarkers for disease phenotype

Scavenger receptors: several classes of them exist. The only conserved feature is that they bind modified lipids (acLDL) with varying efficiency.

Class A scavengers: includes 2 that Dawn studies specifically: MARCO and SRA (I and II). Found in all organisms from plants to humans, yeast.. etc. They are involved in cell-cell interactions, and have been adapted to many other cell-interactions.

Marco (Macrophage receptor with collagenous structure) and SRA (scavenger receptor class A)have similar ligands, which is very broad. “Molecular fly paper.” In general, restricted to expression in macrophages)

They only bind some bacterial well, but not all.

SRA plays a role in homeostasis and infectious disease, septic shock.
Marco plays a role in infectious disease. (Redundancy in vitro – requires double knock out.)

The binding domains, however are very different. In Marco, binding is at the end of the receptor. In SRA, it’s the 2nd last.

MARCO is not expressed in any cell line, and is not in bone marrow macrophage. Thus, it’s often overlooked.

Three types of activation: Classical, alternative, innate (hypothesized). Marco seems to be innate activation, and the properties/phenotype are not well understood. Possibly a phenotype for immuno-modulation, but when it’s used is not known. Fills a niche, which doesn’t quite fit with the known models in mouse.

So, how does it work in TB? (Not something Dr. Bowdish intended to study, but ended up falling into it in oxford.)

There are many types of uptake – and many new ones have been discovered. There’s still room for more receptors, however, and it’s possible that the scavenger receptors might be involved in TB.

SRA is up-regulated in response to IFN-gamma and BCG, knockouts are susceptible to BG induced shock. But MARCO? No clear connection. There is still no human anti-MARCO antibody, so these experiments can’t be repeated for human cells.

Collaboration with Dr. Russell and Sakamoto from Cornell, and ended up getting involved. They had a ligand (Trehalose dimycholate) that no one had ever found a receptor for – and that turned out to be MARCO. Using TDM coated beads, you could see if it was picked up.

Use a cell line with MARCO receptor – and the beads. MARCO showed that it picked up the beads, SRA did not pick up beads. Could knock it down with a specific inhibitor for MARCO. (shown with fluorescence microscopy.)

Previous work had shown that TDM induces cytokine production in a MyD88 dependent fashion. There was a TLR2 &4 response – so did a knock out, and showed that it could use either of them.

Minimum signal complex required is Marco + TLR (2 or 4). This recreates the pro-inflammatory response. Could never recreate this with SLA.

Is MARCO the missing factor in TDM signalling? Yes. So, it’s not that they’ve lost the pathway or ability – just lacking the particular co-receptor to interact with TDM.

How MARCO works in cytoplasm, however, is another story – it has a very small cytoplasmic tail… which includes a predicted myristolation site. Made constructs with different part of the tail – which didn’t change the signalling much. The model proposed, however, is that MARCO is a tethering receptor, which binds or transports the TDM beads to TLRs via CD14. (Similar to the LPS signalling complex.) This was tested with a NF-kb reporter system.

More experiments were done using the knockouts without MARCO or DKO, and were able to continue along to find that MARCO appears to be involved in response to M. Tuberculosis.

Up till now, this was in vitro and mouse. A switch was made to human models.

Started looking for groups looking at SNPs in humans. Did a study interested in whether these SNPs are related to human disease. (Adrian Hill?)

It works well because TB has been around for a long time – 40,000 years.

The Hill group has samples from Gambia, to study TB. Screened 3,500 individuals (HIV free), do controls for the usual (age, sex, etc), and then screened 25SNPs in MARCO and 22 in MSR1.

[Presents a fancy map, showing coverage.]

Much to surprise: there were no SNPs what so ever in SRA – found 4 in MARCO with association to susceptibility and resistance. However, they were all in introns. They were found in introns, and discovered that it was in a putative splice site. (There were no splice variants known in mice, at the time – and there are still none known.) Using assays, Dr. Bowdish found there were indeed splice variants, caused by the SNP.

Oddly enough, this splice variant seems to knock out the binding domain of MARCO. (And the SNP seems to be predominant in african populations – and is very uncommon in caucasians.)

Tentative model: TDM induces MARCO expression. MARCO is regulated at transcriptional and post-translational modification levels. Thus, splice variants may induce differences in response to TB bacteria.

Goals for the future:

  • Understand role of macrophage receptors in infectious disease
  • Attribute functional significance of genetic variability in macrophage genes
  • Characterize phenotype of innate activation & determine if this can be manipulated by immunomodulation
  • Collaborating with people studying other receptors.

Open day on October 26th, 2009 : Institute of infectious disease research opening day.

>Searching for SNPs… a disaster waiting to happen.

>Well, I’m postponing my planned article, because I just don’t feel in the mood to work on that tonight. Instead, I figured I’d touch on something a little more important to me this evening: WTSS SNP calls. Well, as my committee members would say, they’re not SNPs, they’re variations or putative mutations. Technically, that makes them Single Nucleotide Variations, or SNVs. (They’re only polymorphisms if they’re common to a portion of the population.

In this case, they’re from cancer cell lines, so after I filter out all the real SNPs, what’s left are SNVs… and they’re bloody annoying. This is the second major project I’ve done where SNP calling has played a central role. The first was based on very early 454 data, where homopolymers were frequent, and thus finding SNVs was pretty easy: they were all over the place! After much work, it turned out that pretty much all of them were fake (false positives), and I learned to check for homopolymer runs – a simple trick, easily accomplished by visualizing the data.

We moved onto Illumina, after that. Actually, it was still Solexa at the time. Yes, this is older data – nearly a year old. It wasn’t particularly reliable, and I’ve now used several different aligners, references and otherwise, each time (I thought) improving the data. We came down to a couple very intriguing variations, and decided to sequence them. After several rounds of primer design, we finally got one that worked… and lo and behold. 0/2. Neither of them are real. So, now comes the post-mortem: Why did we get the false positives this time? Is it bias from the platform? Bad alignments? Or something even more suspicious… do we have evidence of edited RNA? Who knows. The game begins all over again, in the quest for answering the question “why?” Why do we get unexpected results?

Fortunately, I’m a scientist, so that question is really something I like. I don’t begrudge the last year’s worth of work – which apparently is now more or less down the toilet – but I hope that the why leads to something more interesting this time. (Thank goodness I have other projects on the go, as well!)

Ah, science. Good thing I’m hooked, otherwise I’d have tossed in the towel long ago.

>My Geneticist dot com

>A while back, I received an email from a company called mygeneticist.com that is doing genetic testing to help patients identify adverse drug reactions. I’m not sure what the relationship is, but they seem to be a part of something called DiscoverMe technologies. I bring mygeneticist up, because I had an “interview” with one of their partners, to determine if I am a good subject for their genetic testing program. It seems I’m too healthy to be included, unless they later decide to include me as a control. Nuts-it! (I’m still trying to figure out how to get my genome sequenced here at the GSC too, but I don’t think anyone wants to fund that…)

At any rate, I spoke with the representative of their clinical side of operations this morning and had an interesting conversation about my background. In typical fashion, I also took the time to ask a few specific questions about their operations. I’m pretty sure they didn’t tell me much more than was available on their various web pages, but I think there was some interesting information that came out of it.

When I originally read their email, I had assumed that they were going to be doing WTSS on each of their patients. At about $8000 per patient, it’s expensive, but a relatively cheap form of discovery – if you can get around some of the challenges involved in tissue selection, etc. Instead, it seems that they’re doing specific gene interrogation, although I wasn’t able to get the type of platform their using. This leads me to believe that they’re probably doing some form of literature check for genes related to the drugs of interest, followed by a PCR or Array based validation across their patient group. Considering the challenges of associating drug reactions with SNPs and genomic variation, I would be very curious to see what they have planned for “value-added” resources. Any drug company can find out (and probably does already know) what’s in the literature, and any genetic testing done without approval from the FDA will probaby be sued/litigated/regulated out of existance… which doesn’t leave a lot of wiggle room for them.

And that lead me to thinking about a lot of other questions, which went un-asked. (I’ll probably email the Genomics expert there to ask some questions, though I’m mostly interested in the business side of it, which they probably won’t answer.) What makes them think that people will pay for their services? How can they charge a low-enough fee to make the service attractive while getting making a profit? And, from the scientific side, assuming they’re not just a diagnostic application company, I’m not sure how they’ll get a large enough cohort to make sense of the data they receive through their recruitment strategy.

Anyhow, I’ll be keeping my eyes on this company – if they’re still around in a year or two, I’d be very interested in talking to them again about their plans in the next-generation sequencing field.

>SNP callers.

>I thought I’d switch gears a bit this morning. I keep hearing people say that the next project their company/institute/lab is going to tackle is a SNP calling application, which strikes me as odd. I’ve written at least 3 over the last several months, and they’re all trivial. They seem to perform as well as any one else’s SNP calls, and, if they take up more memory, I didn’t think that was too big of a problem. We have machines with lots of RAM these days, and it’s relatively cheap, these days.

What really strikes me as odd is that people think there’s money in this. I just can’t see it. The barrier to creating a new SNP calling program is incredibly low. I’d suggest it’s even lower than creating an aligner – and there are already 20 or so of those out there. There’s even an aligner being developed at the GSC (which I don’t care for in the slightest, I might add) that works reasonably well.

I think the big thing that everyone is missing is that it’s not the SNPs being called that important – it’s SNP management. In order to do SNP filtering, I have a huge postgresql database with SNPs from a variety of sources, in several large tables, which have to be compared against the SNPs and gene calls from my data set. Even then, I would have a very difficult time handing off my database to someone else – my database is scalable, but completely un-automated, and has nothing but the psql interface, which is clearly not the most user friendly. If I were going to hire a grad student and allocate money to software development, I wouldn’t spend the money on a SNP caller and have the grad student write the database – I’d put the grad student to work on his own SNP caller and buy a SNP management tool. Unfortunately, it’s a big project, and I don’t think there’s a single tool out there that would begin to meet the needs of people managing output from massively-parallel sequencing efforts.

Anyhow, just some food for thought, while I write tools that manage SNPs this morning.