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December 25, 2020

Synthetic RNA molecules see the FOREST from the trees

The Hirohide Saito laboratory reports a new platform, FOREST, to evaluate the function of RNA structures at massive scale.

One of the major goals of synthetic biology is to understand and control cell functions. To do this, scientists have constructed synthetic biomolecules like RNA that function in cells. These synthetic RNA may consist of modules that act as sensors, switches, and actuators. Thus, by binding to target molecules in a cell, the synthetic RNA can modulate the target to affect how a cell behaves, such as move, grow or even die. However, scientists still struggle to build synthetic RNA that can bind to a wide variety of target molecules. As a solution, the laboratory of CiRA Professor Hirohide Saito reports a new biochemical and informatics system called FOREST (folded RNA element profiling with structure library). The study can be read in Nature Communications.

In the Central Dogma, DNA is transcribed into RNA which is translated into protein. DNA stores the genetic information of our bodies, while proteins are molecular machines tasked with regulating all the processes needed to maintain a cell. Originally, RNA was viewed as an intermediate, but biologists have come to realize that it has a diversity and function that matches if not exceeds proteins.

From the perspective of synthetic biology, RNA molecules are easier to construct than proteins. Prof. Saito and his research team are experts in synthetic RNA, having built RNA tools that can interact with proteins to program a cell into a desired state.

"In the cell, there are many natural RNA structures that bind to and regulate specific proteins, but we don't have a high-throughput, massive-parallel system that can assesses these combinations. That is why we developed FOREST," says Saito.

Fundamentally, FOREST consists of three steps. In the first, different motifs are extracted from RNA datasets to constitute an RNA structure library. Then the structures are assigned an RNA barcode. Finally, they are reacted on a DNA barcode microarray.

"The microarray allows us to do massive parallel and direct quantification of the RNA structures without any amplification step such as reverse transcription or PCR. These cause structure-dependent bias and should be avoided," said Kaoru Komatsu, who contributed to the study and earned his doctorate degree based on the research.

To demonstrate the usefulness of FOREST, the researchers applied it to stem-loop motifs and terminal motifs. Stem-loop motifs are found in pre-miRNA, which are known to regulate cell fate. Terminal motifs, on the other hand, are compatible with any RNA structure, which would validate the generality of FOREST.

The binding of stem-loop motifs to several proteins was investigated, including LIN28A protein, which is considered crucial for cell reprogramming to iPS cells. Similar experiments were done for the RNA motif known as the G-quadruplex structure, a noncanonical RNA structure whose bindings to other molecules are difficult to measure with current technologies. In both cases, FOREST verified that proteins have different specificities and preferences for a specific motif.

"Understanding the RNA-protein binding interactions will allow us to build better synthetic RNA for controlling cell behaviour," said Komatsu.

Indeed, while the laboratory has generated an assortment of RNA synthetic tools for iPS cell technology, they are leaky and need better for efficiency before they can be used to advance iPS cell research to the clinic.

"This is a very general system to extract RNA structural information," said Saito. "It can evaluate diverse RNA from multiple databases. We expect FOREST will help clarify the many essential but unknown functional RNA structures in a cell."

Paper Details
  • Journal: Nature Communications
  • Title: RNA structure-wide discovery of functional interactions with multiplexed RNA motif library
  • Authors: Kaoru R Komatsu1, Toshiki Taya2, Sora Matsumoto1, Emi Miyashita1, Shunnichi Kashida*1
    and Hirohide Saito*1
    *Co-corresponding author
  • Author Affiliations:
    1. Department of Life Science Frontiers, Center for iPS Cell Research and Application, Kyoto University, Kyoto, Japan
    2. Twist Bioscience, San Francisco, USA
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