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Whitehead's Marson on Using ChIP-Chip to Investigate Regulatory T Cells


Alexander Marson
Graduate Student
Whitehead Institute, MIT
Name: Alexander Marson
Title: Graduate Student, Whitehead Institute, MIT
Education: 2004-present, PhD, biology, Massachusetts Institute of Technology; 2002-present, MD, Harvard Medical School; 2001-2002, MPhil, biology, University of Cambridge, UK; 1997-2001, AB, biology, Harvard College.

A paper in this month’s issue of Nature discusses the use of chromatin immunoprecipitation-on-chip technology to interrogate how defects in regulatory T cells may cause the body to attack itself, resulting in one or more autoimmune diseases — such as rheumatoid arthritis, lupus, multiple sclerosis, and thyroid disease [Marson, et al. Foxp3 occupancy and regulation of key target genes during T-cell stimulation. Nature. 2007 Jan 21; [Epub ahead of print]].
Authored by researchers from the Whitehead Institute for Biomedical Research, the paper reports the discovery of 30 genes that go awry in autoimmune diseases. The researchers discovered the genes by investigating a transcription factor called Foxp3 that is thought to be integral in the production of regulatory T cells.
To learn more about the research, BioArray News spoke last week with Alexander Marson, lead author on the paper and a graduate student in Richard Young’s lab at the Whitehead Institute.
How did you wind up in Rick Young’s lab?
I am an MD/PhD student. I was in medical school in Harvard and then I came to work in Rick’s lab at the Massachusetts Institute of Technology and I got excited about regulatory T cells. I first heard about them in medical school and I thought that doing ChIP-on-chip on Foxp3 was something that Rick’s lab was uniquely well set up to do.
So I got excited about the project and we collaborated with Harold von Boehmer’s lab [at Harvard], and Karsten Kretschmer and I worked together to set up a system to identify Foxp3 targets.
And what is the background on how this paper came about?
The field, within the past ten years or so, has identified regulatory T cells as a subset of T cells that have a remarkable functional property. They are able to suppress other T-cell populations and prevent them from attacking the self and causing autoimmune disease.
It’s also known that in mice, if you remove regulatory T cells, it causes massive, multi-organ autoimmunity. Regulatory T cells also are dysfunctional in a lot of common human autoimmune diseases. Regulatory T cells in multiple sclerosis patients appear not to work as well to suppress other T cells as they would in healthy people.
Four years ago, Foxp3 was identified as a key regulator of regulatory T cells. Foxp3 is a transcription factor that is selectively expressed in regulatory T cells. It seems to be absolutely required for the development and function of regulatory T cells.
So Foxp3 has become a tremendous interest. In addition to being a marker for regulatory T cells, it also became an entry point to study the molecular underpinnings of regulatory T cells’ ability to suppress other T cells and prevent autoimmune disease.
So, if you could understand what Foxp3 is targeting you’d start to figure out what are the genes that are specifically controlled to give regulatory T cells their unique identity.
People had tried expression studies alone and some information was known, but understanding the direct targets of Foxp3 allows you to weed out what are the secondary effects of other differences between regulatory T cells and non-regulatory T cells and to really concentrate on the direct targets that are controlled by this transcription factor that is essential for the development and function of regulatory T cells.
And ChIP-on-chip is currently the best way to identify direct regulatory targets of a transcription factor. So we were excited about this.
How did you set up a system to do this?
To set up a system, we created a cell line that expressed an epitope-tagged version of Foxp3, which allowed us to do ChIP-on-chip with an anti-flag antibody. We also used a microarray platform that we recently published on with the Jaenisch lab. So the arrays we used were actually the same array design that was used by Boyer in a paper last year about Polycomb [Nature. 2006 May 18;441(7091):349-53].
The array is designed to tile probes at the promoter regions of most known genes in the mouse genome. And so it focuses on 10 kilobases of sequence around the start site of every annotated genes, and it goes 8 kb upstream and 2 kb downstream from annotated start sites with a 50-base-pair probe roughly every 250 base pairs along the stretch of promoter. This allows you to identify immuno-enriched portions of the genome after you do an IP with an anti-Foxp3, or in this case, an anti-flag antibody. The immuno-enriched portions are then identified on the microarray and those are the directly bound regions of the transcription factor that you are studying.
Didn’t Agilent also play a role in developing these arrays?
Well, these arrays were custom ordered from Agilent, although now I believe that some version of these arrays are available as a catalog product.
Walk me through how you approached the study.
We did duplicates with the flag IP, and we saw that we were pulling down enrichment encoding some known targets of Foxp3. We also did a flag IP in the cell that didn’t have a flag-tagged version of Foxp3 as a negative control to show that we were pulling down things that were specific to the actual flag-tag Foxp3 and not just background. We also had a positive control of doing an IP with a different transcription factor E2F4, which is something that we’ve used a lot. So we were able to show that we pulled down known E2F4 targets that were distinct from the Foxp3 targets. We also did the flag IPs in different conditions, in both stimulated and non-stimulated cells to allow us to see where Foxp3 binds before stimulation and where Foxp3 binds after a cell is stimulated.
And what did you find?
If you look at the regions that are bound after T-cell stimulation, Foxp3 is already there, and seems to already be at those same promoter regions prior to stimulation, usually at a lower level of enrichment. For many of the genes we also see additional sites of recruitment of Foxp3. So it seems to be pre-bound at most genes, but there’s additional recruitment at targets genes after T-cell stimulation. This was also interesting given that we saw a more pronounced transcriptional effect at the targets after T-cell stimulation.
After looking at those results, what is the next step in your work?
Well, I think there are a few logical follow-ups. One is to pick some of the Foxp3 targets and dissect out their biological role in regulatory T cells, and also to see if mutations in those genes are associated with autoimmune disease. I think a longer term goal is to see if there are any compounds that mimic the function of Foxp3 at its target genes which might be a potential way of developing new therapies to regulate the immune system.
Who, in your opinion, needs to read your paper to move it along on that path?
I suspect that these genes tell us something fundamentally interesting about how the immune system is regulated. I look forward to seeing what the applications are that a lot of groups come up with. I think that people who study autoimmune disease, who study transplant biology, and even people who study cancer immunology, might be interested in following up on some of these targets and seeing if there’s any interesting applications. And I guess that applies to academics and those in industry that are more focused on developing therapeutic applications.
What have you learned about ChIP-on-chip from this research?
Well, ChIP-on-chip is definitely growing in its usage, and as it becomes more standardized, more and more groups are using the technology, but it still requires just a huge amount of support from people with various levels of expertise like bioinformaticians. The Young lab and our collaborators had the requisite experience to handle the huge amount of information that comes off of this chip.      

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