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NIA s Schwartz on Assessing Cell Differentiation from Embryonic Stem Cells

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Catherine Schwartz
Researcher
National Institute of Aging/ Karolinska Institute

Name: Catherine Schwartz

Title: Researcher, National Institute of Aging/ Karolinska Institute

Professional Background: Catherine Schwartz is currently enrolled in the Karolinska Institute and National Institutes of Health's graduate partnership program, splitting her time between labs in Baltimore and Stockholm, Sweden. In the past she has also worked in the lab of Jeffery Barker, at the National Institute of Neurological Disorders and Strokes' Laboratory of Neurophysiology, and Gina MacDonald's lab at the department of chemistry at James Madison University.

Education: 2002 — BSc, chemistry, James Madison University.


Over the past six months, scientists from the National Institute of Aging's Stem Cells Unit and Sweden's Karolinska Institute have published three papers on dopaminergic and glial activity in human embryonic stem cells.

Last week, Catherine Schwartz, a graduate student and co-author on all three papers, presented some of the work the group has done using microarrays to examine this activity in a poster at Cambridge Healthtech Institute's Molecular Medicine Tri-Conference in San Francisco.

The poster, entitled "The development of a focused microarray to assess dopaminergic and glial cell differentiation derived from human stem cells," details the work that Schwartz and her co-authors, including scientists from NIA, Karolinska, and array firm SuperArray, published in the December 2005 issue of Stem Cells.

To discuss the poster and the array Schwartz and others developed for these experiments, BioArray News spoke with the NIA/Karolinska researcher this week.

How are you affiliated with both the National Institute on Aging and the Karolinska Institute?

I am actually in the graduate partnership program at the National Institutes of Health and they have collaborations with universities all over the world. Most of them are actually in the United States, but there are a few of them that are international. Because the NIH can't grant a degree, they collaborate with these other universities, provide funding, and the whole point is to try and set up a collaborative research project between two advisors.

So I am actually a graduate student at Karolinska.

Have you been traveling back and forth between the US and Stockholm a lot?

Yes, I just got back from Stockholm just prior to the conference, actually. So this is my first [week] back in the lab in about a month.

You have a number of contributors for this paper. How did the team coalesce and what role did SuperArray play?

A lot of people that were involved in the project were responsible for growing out different cell populations or screening different cell populations, because we used neural stem cells derived from human embryonic stem cells. We used dopaminergic progenitor cells. So we had a lot of collaborations within our own lab that were very apt at screening these populations.

The array was designed for the purpose of a few projects that are in the lab. We don't use it on a routine basis yet, but it was designed for the purpose of two projects; one involved dopaminergic neuron generation for pluripotent stem cells, and the other from glial generation from pluripotent stem cells.

I saw Mahendra Rao was listed as a co-author. What role did he play? BioArray News interviewed him last September (see BAN 9/14/2005).

He used to be the head of our lab here, but he actually moved on to Invitrogen. He's still at Johns Hopkins, but he actually left NIH as of October.

Why were you interested in providing an overview of the process of dopaminergic neuron and glial differentiation?

Mainly we were interested in these two cell lines because of the potential use of stem cells in replacement therapy for neurodegenerative disorders. Mainly things like Parkinson's disease, multiple sclerosis, and other diseases that involve glial degeneration and dopaminergic neuron degeneration. So our thought was also that we could use this array as a quick way to screen populations prior to doing transplantation, just to get an overview of the cell population to see if there were any possible contaminating pluripotent cells that could possibly be harmful to the transplantation. So, it's sort of our goal to routinely and quickly assess these cell populations to get an idea of what stage they are at, how mature they were, and what sort of signals were involved at that time we were testing.

When you were heading into this project did it seem like a formidable undertaking to accomplish your goals?

I thought it would be fairly easy to do and would be helpful for my own research, as well as some other research that is ongoing in the lab. I didn't think it was an enormous undertaking, but it was accomplished much quicker than I thought it would be.

How did you construct the array?

SuperArray was involved in choosing the probes. They have a very rigorous method of choosing the probes for the array. The array was designed and printed here [at NIH], and we did all the validation testing here, that was all done by [fellow investigator]Yongquan Liu. We sort of came up with the idea ourselves — what kinds of genes we were interested in looking at, etc. SuperArray was involved in designing the arrays, making sure they didn't cross hybridize.

We are hoping that it will be made commercially available through SuperArray in the next coming years. I believe they will be working on a mouse array as well. The array we have used is human, but the processes will translate over to mouse.

Can you walk me through the actual array? What's on it?

There are 281 probes on the array. It's arrayed in a 25x12 format and we've sort of separated them out so that you can look visually and see whether or not the array is working properly. The first portion of the array is mainly dopaminergic neuronal markers. The second portion is glial markers. Then you have ES and progenitor markers. And then the bottom part is cell signaling and positive detection controls and negative controls — all sorts of thing just to let us know the array is working properly.

How did you run the experiment?

We did use embryonic stem cells for a titration in the experiment, in which we varied the amounts of substantia nigra that contains dopaminergic and glial markers to human embryonic RNA. So we started out with all substantia nigra and varied the ratios until it was all human embryonic stem cell RNA. We wanted to see if we could detect genes in a concentration-dependent manner. We also used ES to derive neural stem cells. And these stem cell lines were from Bresagen, BG01 and BG03.

What kind of expression patterns did the array yield, and why were they significant?

We found out that we could detect dopaminergic and glial markers in a concentration-dependent manner. We also used it for application testing. So we used polysilated neural cell adhesion marker, which is a marker for neuroprogenitors. We selected them by flow cytometry and then used them towards dopaminergic neurons. We were able to detect markers for mature neurons as well as markers for pluripotency described in the cell line from which they were from. So overall, we were able to show that the array passed quality control testing and we were able to detect genes from the neuronal lineages and glial lineages. We were able to detect genes in a concentration-dependent manner showing the sensitivity of the array.

What are some interesting biological questions that exist that something like this could help to answer?

I have received some interest from people that are interested in just screening their population. Somebody at the [Tri-conference] was talking about some of the stem cells that they work with, that they try to induce towards neurons; screening their populations to see what's present. It also would be interesting in terms of signaling molecules. Taking a cell population that's induced towards either dopaminergic or glial cells and looking at exactly what types of signaling molecules are present.

It may also help to elucidate some of the mechanisms involved in differentiation. And it's really inexpensive, so say you want to do some expensive analysis such as massively parallel signature sequencing, you could quickly screen your population to see if it would be worth the $20,000 to $40,000 per experiment.

Or if you want to quickly screen a population prior to transplantation so you don't want to waste your time, it's also an effective tool. Say you are looking at a Parkinson's disease model and you are looking at something that has expressed dopaminergic markers. You don't necessarily want to transplant and then wait eight weeks if it's not the population you are interested in. So I think it can be used rapidly to test the population.

But, like with most arrays, you still have to confirm with PCR as well.

When do we get to call you 'doctor'?

Hopefully in two years. That's my goal.

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