Live blogger: Eilidh McClain
Editors: Paul Dylag and Jennifer Baker
This piece was written live during the 7th annual RNA Symposium: From Molecules to Medicines, hosted by the University of Michigan’s Center for RNA Biomedicine. Follow MiSciWriters’ coverage of this event on Twitter with the hashtag #umichrna.
In response to multiple external factors, chromatin in chromosomes is able to dynamically shift in order to facilitate gene regulation. Gene expression is altered in part by the use of RNA-protein interactions within the chromatin. However, study of these interactions features many experimental requirements that are not optimized for studying chromatin dynamics as a whole and its role in gene regulation. Dr. Steve Henikoff and coworkers at the Basic Sciences Division of the Fred Hutchinson Cancer Center have tackled this RNA-protein interaction problem by developing new and powerful tools for studying those interactions. Now that these tools have been developed, they can provide interesting insights to the role of chromatin dynamics in regulation of gene expression and silencing with relative ease compared with previous methodology.
What is gene expression and silencing?
In our chromosomes, which contain all of the genetic information needed to develop and grow, there is a gaggle of proteins, deoxyribonucleic acid (DNA), and ribonucleic acid (RNA) called chromatin. The DNA and RNA encode the genes required to create proteins that then create and make up the rest of the human body. But not all genes are expressed at the same time or in the same quantity, meaning that they do not undergo the transcription and translation processes. For example, what might be needed when one is a young child in order to grow very quickly will not necessarily be required for an adult who has stopped growing. The regulation of when and where genes are expressed is called gene expression. How does this all come together, then? How does a cell know what genes to express at a given time?
The answer to that question is a hot area in biology and biophysics and is still being studied. What we do know is the chromatin clumps around proteins called histones. A histone is a 8-part protein complex that acts as an structure for DNA to wrap around, similar to how a vacuum cleaner cord is wrapped around two pegs after cleaning for safe and efficient storage. To express a certain gene at a certain time, these histones can be modified so that the chromatin shifts around, exposing a DNA region of interest to RNA polymerase II so that it can be transcribed into RNA. If the gene is inaccessible due to the chromatin remaining tightly packed, this is called gene silencing.
How does the chromatin know to shift around? The answer is epigenetics, a mechanism that determines which genes are turned on or off. Epigenetics depends on external factors such as cell type (stem cells, for example, would need a different regulatory process than a cell that’s already been specialized), disease state, and physiological stimuli. One example of an epigenetics is the flagging the histones with methyl tags, termed methylation. Typically, methylation prevents RNA polymerase II from binding, preventing that segment of DNA from being transcribed. Methylation is only one way that the chromosome modifies itself in order to control gene expression; there are many other types of modifications that are currently being studied.
Inside the chromosome, interactions between RNA and various proteins can pass along methylation information in order to regulate the gene. As the chromatin shifts around to allow RNA polymerase II to access different sites, these interactions are how the different parts of the chromatin communicate with one another. These interactions are unknowns, the study of which motivates this talk and many others in the field.
How are RNA-protein interactions traditionally studied?
RNA-based interactions are principally studied using immunoprecipitation methods. The recognition of a desired protein is accomplished with specific antibodies bound to a solid-state material like agarose gel or magnetic beads, allowing the protein-antibody to precipitate out of solution to be studied. For example, chromatin immunoprecipitation (ChIP), one of the most utilized methods, was developed in 1984 by Gilmour and Lis, and involves five steps:
- Cross-linking protein to target DNA sequences
- Breaking genomic DNA into smaller pieces
- Precipitating out the protein bound to these DNA chunks
- Freeing the DNA fragments from precipitated proteins
- Amplifying DNA for sequencing.
While immunoprecipitation is the traditional method, there are weaknesses to this method. Large sample inputs and optimized cross-linking conditions are required, which inhibit the accessibility of the technique. In addition, different interaction types exist in the chromatin as a whole, such as RNA-protein, RNA-chromatin, and RNA-modification interactions. Targeting each type of interaction requires a separate immunoprecipitation technique, making the study of RNA-protein interactions rather inefficient and time-consuming. These techniques also cannot comprehensively study chromatin dynamics or the role of chromatin movement in the expression of certain genes at certain times. The fragmentation is also very important, and if the DNA and protein don’t fragment in a specific way, the experiment must be repeated – this is one of the primary downsides to ChIP in particular.
What are the new tools developed to study RNA-protein interactions, and what are their benefits?
In order to combat the drawbacks of immunoprecipitation, Henikoff and coworkers developed three principal tools that circumvent the issues with traditional methods. The first of these methods is CUT&RUN. CUT&RUN maps transcription factors, which are proteins that regulate the conversion of DNA to RNA, giving valuable information about transcription conditions in different areas of the genome. This is an improvement over ChIP because only a small amount of DNA is needed to gain the information needed, and it doesn’t have the same fragmentation problem. Therefore, backgrounds are low and fewer cells are needed to achieve a good signal.
The second and third methods, CUT&Tag and RT&Tag, can be used in tandem. CUT&Tag can operate with low cell numbers and sample quantities. CUT&Tag extracts the DNA of interest tethered to the protein it interacts with, and then sequenced. During the pandemic, Henikoff used some surplus supplies and collected data using this technique in his laundry room! This amusing demonstration shows the ease of this method compared to other immunoprecipitation methods. The third method, RT&Tag, uses antibodies, similar to immunoprecipitation, but instead has the ability to identify RNA in proximity to those antibodies rather than depending on cross-linking. RT&Tag shows that long non-coding RNAs are not merely ‘junk’, and they can have important chromatin-modifying functions.
One benefit of RT&Tag in particular is that cross-linking is not required to study the RNA-protein interaction, and the method doesn’t require very much sample input. This helps optimize the process of study, especially in the case of precious samples, where high yields are difficult to obtain. In addition to these benefits, RT&Tag can also be used for multiple types of RNA-protein interactions, making this method far more efficient than immunoprecipitation. These methods have been scaled up and provide valuable tools for studying organismal development and disease pathology.
One question asked of Dr. Henikoff after the talk involves the yield of RNA during these multi-step processes. Is there a bias over which ones survive the protocol and which ones do not? Unfortunately, one drawback is that there is no independent way of knowing what the yields of RNA are – but there are ways to determine if detected RNAs have biological significance.
What’s next?
After many proofs of concept by Dr. Henikoff’s lab, these methods can now be applied to important questions involving chromatin dynamics. Given an appropriate and available antibody, RT&Tag in particular can be used for many different types of applications, including chromatin and cytoplasmic studies in order to elucidate the relationship between RNA and proteins. These methods fill the need to achieve high-throughput profiling of chromatin-bound DNA, RNA, and proteins and are useful for situations where sample input is limited.
About the speaker
Steve Henikoff is a professor and investigator in the Basic Sciences Division of the Howard Hughes Medical Institute in Seattle and has been studying proteins in the epigenome for many years. The goal of his research lab is to better understand inheritance that does not depend solely on DNA sequence using novel tools. Henikoff has received many honors and awards, including the privilege of being an elected fellow for the American Association for the Advancement of Science in 2012 and became an elected member of the American Academy of Arts and Sciences just last year. In addition to this, he has given keynote speeches at talks on multiple continents. He is currently the Field Chief Editor for Frontiers in Epigenetics and Epigenomics, the most cited journal in the field.
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