NEW YORK (GenomeWeb) – As part of its High-Risk/High-Reward Research Program, the National Institutes of Health has awarded a University of California, San Diego investigator a five-year, $3.8 million grant to develop a technology to map complete RNA interactomes in cells or tissues using high-throughput DNA sequencing.
According to UCSD's Sheng Zhong, the funding will be used to further refine the technology, as well as to investigate the mechanisms underlying cell fate decisions in early mammalian development.
While technologies exist for studying RNA-RNA interactions, they all require starting with a specific target molecule, Zhong said. "For example, you [can] start by enriching for one RNA, then ask the question, 'What might be the interacting partners?' Or, you start from one protein that would assist RNA-RNA interaction."
Taking this route to explore the entire RNA interactome, he added, would be extraordinarily time-consuming. "We want to remove that bottleneck [with] a technology that would directly map" multiple interactions simultaneously, he said.
Many popular methods are also limited by their need for the ectopic expression of either proteins or synthetic RNA molecules, Zhong explained.
However, "when you express something ectopically, you bias the endogenous concentration," he said. "That could potentially … lead to finding spurious interactions. As soon as you perturb, you may bias your findings — you may identify interactions that are possible … but not necessarily happening under endogenous conditions."
Without requiring the genomic perturbation of ectopic expression, Zhong thinks that the new technology will also allow for assaying human tissues.
Underlying Zhong's approach is a process that converts RNA interaction into unique, synthetic DNA sequences. He declined to comment on the specifics of this method ahead of the publication of a manuscript, currently under review, that provides such details.
Once the RNA interactions have been converted into DNA sequences, they are read using existing platforms.
Because of the sheer number of possible RNA-RNA interactions, and the fact that Zhong's technology is designed to not only identify these reactions but also measure their intensity, "the readout would need to be extremely high-throughput," and current DNA sequencing tools fit that bill, he said.
Zhong believes the work described in the upcoming publication is proof of principle for his technology, and he said that the NIH grant money would enable further optimization to ensure that it is sensitive, specific, and simple to use. And part of that effort will involve its application in a study of cell fate decisions during pre-implantation development.
In mammals, "a fertilized zygote has to divide and set apart the first two cell populations," one of which becomes an embryo and the other the placenta, Zhong explained. "But what is the physical principle that underlies this first cell fate decision? That is a fundamental question."
Using the RNA interaction-mapping technology, he and his colleagues hope to generate large-scale maps of the molecular interactions directly within cells from animal models at different stages of pre-implantation development in order to identify those that are relevant to early cell fate decisions.
Longer term, Zhong also sees potential for his technology in the burgeoning field of RNA therapeutics.
"A critical piece of information [for this space] is to know which RNA interacts with which [and] with what affinity," he said. "If you have that information, there is the potential of leveraging RNA mimics as potential [drug] candidates," for instance.