When he’s not running his lab up at the Hutch or co-editing epigenetics’ only open source journal, Epigenetics and Chromatin, Dr. Steve Henikoff tinkers a bit (ok…that might be a bit of an understatement). Credited with inventing a range of useful research methods that have streamlined processes from sequencing to computational prediction tools, the Chicago native is definitely the type of PI you want on the receiving end of one of the R21 grants in the Roadmap Epigenomics’ Technology Development in Epigenetics segment.
For those of you that may not be up to date on the Roadmap Epigenomics initiative, the R21 grants fall into the high risk/high gain category and were rewarded to proposals that might lead to “…revolutionary epigenetic technologies…” But if you look at some of the talented labs that received these grants, they don’t seem that risky. Something useful will likely come out of these projects regardless of whether or not the end result matches that of their purpose. After all, it was while Henikoff was tweaking sequencing approaches to be more effective that he discovered genes nested in introns, a concept as foreign as the internet back in the ‘80’s.
Recently, there’s been ever-increasing evidence indicating that various epigenetic processes are very dynamic. CATCH-IT, an epicronym for Covalent Attachment of Tags to Capture Histones and Identify Turnover, will allow researchers to study nucleosome dynamics by enabling genome-wide measurement of histone replacement kinetics. We caught up with Roger Deal, a post-doc in the Henikoff Lab, who filled us in on the details.
Henikoff Lab Interview
EpiGenie: Your grant falls into the “high risk, high return” technology development category. When you succeed, how do you envision CATCH-ITs first big journal debut?
Deal: We envision the debut of CATCH-IT as primarily a solid proof-of-concept but also an illustration of the power and potential of this method to yield new insights into the relationship between nucleosome dynamics and gene expression.
In the future we plan to apply CATCH-IT to other cell types, including ES cells and their descendants. One of the great things about this technique is that in addition to giving real-time measurements of nucleosome dynamics, we’ll also be able to map the promoters and other regulatory elements that are being utilized in these cells.
And we’ll be able to get all that without using any transgenes or antibodies! So, CATCH-IT will truly be a “plug-and-play” method in the sense that it employs a generic set of reagents and could therefore theoretically be used on any cell type.
EpiGenie: What do you see as the biggest technology development hurdles with this project?
Deal: The downstream steps, such as pulldown of biotinylated histones and microarray analysis, are already well established so the hard part has been getting histones labeled with the synthetic amino acid Azidohomoalanine, coupling biotin to the labeled histones, and ensuring that we can remove all other DNA-binding proteins (which will also be labeled) from the chromatin prior to the pulldown.
We’ve worked out most of these issues, but one of the most frustrating problems we had to work around was the fact Copper, which catalyzes the coupling of biotin to AHA-labeled histones, causes chromatin to precipitate! In the end we found a trick to make it work and now we’re ironing out the smaller wrinkles in the procedure.
EpiGenie: Would this, or another hurdle be exacerbated by any specific model system, or research scenario?
Deal: We think the method should be widely applicable but will likely require some tweaking for each new cell type, particularly if the cell numbers are limiting.
EpiGenie: Can you expand on what will be CATCH-ITs readout technology? After the
pulldown, what’s next?
Deal: Right now we’re using high-density microarrays from Nimblegen as the readout for CATCH-IT, but we may use Illumina/Solexa sequencing in the future as well.
EpiGenie: Where would you like to take CATCH-IT in the future?
Deal: Down the road we hope to use CATCH-IT to profile nucleosome dynamics during cell differentiation in intact tissues by coupling it with a method for isolating individual cell types.