Membraneless organelles (MLOs), also referred to as "biomolecular condensates," arise through a biological phenomenon known as liquid-liquid phase separation (LLPS). These MLOs are dynamic structures composed of proteins and nucleic acids. Although the involvement of proteins in LLPS has been extensively studied, there is a burgeoning interest within the scientific community to comprehend the role of RNAs in this process. RNAs, being nucleic acids responsible for numerous biological functions, including coding, decoding, gene regulation, expression, and protein synthesis, have drawn increasing attention for their potential contribution to phase separation phenomena.
Recently, it has been discovered through studies that MLOs contain a significant abundance of RNAs that were previously challenging to extract using conventional methods. However, with the development of improved techniques such as needle shearing and heating, these RNAs can now be efficiently recovered. This characteristic of being semi-extractable opens up exciting possibilities for their potential role as essential biomarkers and drug targets in diagnosing and treating various diseases. Despite this promising potential, the identification and characterization of these semi-extractable RNAs within MLOs remain largely unexplored, with only a limited number of studies having successfully tackled this area of research. As a result, there is a pressing need for further investigation to unlock the full potential of these RNAs in advancing our understanding and therapeutic approaches for various medical conditions.
In response to this void, a groundbreaking effort was undertaken by Dr. Chao Zeng, an assistant professor at Waseda University, alongside Dr. Michiaki Hamada from the same institution, as well as Dr. Takeshi Chujo from Kumamoto University and Dr. Tetsuro Hirose from Osaka University. Together, they have successfully devised an innovative bioinformatic pipeline, designed to identify semi-extractable RNAs across various human cell lines. The remarkable outcomes of their research have been documented and published in the esteemed journal Nucleic Acids Research on July 19, 2023.
The research team conducted cellular RNA extraction and sequencing on five human cell lines, namely A10, A549, HEK293, HeLa, and HAP1 cells. They then employed various computational techniques to analyze the RNA sequencing data. Specifically, they compared samples extracted using the conventional RNA extraction method with those extracted using an improved method through differential expression analysis. As a result, the researchers successfully identified RNA transcripts that exhibited consistent semi-extractability across all five cell lines.
To gain further insights, the team also conducted repeat density and sequence motif analysis to explore potential factors that might influence the semi-extractability of these RNA transcripts. Additionally, they utilized the SEEKR algorithm to perform k-mer analysis, which allowed them to functionally categorize the semi-extractable RNAs based on their k-mer content. These comprehensive analyses shed light on the underlying mechanisms and characteristics of semi-extractable RNAs in the studied human cell lines.
Chao Zeng, sharing the key finding of their study, elaborates, "Through the utilization of our newly devised bioinformatic analysis pipeline, we thoroughly investigated raw experimental data from various cultured human cell types. As a result, we accomplished the identification and characterization of 1,074 semi-extractable RNAs, which may play significant roles in the formation of phase-separated membraneless organelles."
After an extensive examination of the localization of semi-extractable RNAs both in chromatin and within the cell, the research team made significant observations. They noted that these RNAs exhibited enrichment in repressed and repetitive heterochromatin regions, particularly in Polycomb-repressed areas. Furthermore, within the cells, the RNAs were prominently concentrated in the nucleus, including the nucleolus, but were found to be dissociated from the chromatin.
Moreover, the researchers put forth a hypothesis suggesting that the semi-extractable RNAs might serve as a platform for interacting with other RNAs. To test this conjecture, they conducted a comparison between semi-extractable RNAs and approximately 600 hub RNAs known to engage in protein-mediated RNA-RNA interactions with multiple other RNAs. The outcome of their investigation confirmed the validity of their hypothesis, as the semi-extractable RNAs demonstrated their role as crucial hubs in facilitating RNA-RNA interactions.
Upon conducting further analysis of semi-extractable RNA, a significant observation emerged. RNA-binding proteins displayed a clear preference for binding to AU-rich regions that were associated with these RNAs. It is worth noting that while messenger RNAs typically showcase AU-rich regions at the 3' end, which plays a role in regulating RNA stability, semi-extractable RNAs exhibited a concentration of AU regions at the 5' end. This finding suggests a potential involvement in yet-to-be-discovered functions for semi-extractable RNAs.
This study presents a pioneering dataset of semi-extractable RNAs in human cell lines, offering a valuable resource for delving into RNA-based phase separations. Enthusiastically, Michiaki Hamada concludes, "By integrating semi-extractable RNAs with RNA interaction studies in the future, we can gain invaluable insights into the molecular mechanisms that underlie RNA-induced phase separation in cells."
The findings from this study open up new perspectives for investigating the role of RNA in various biological processes, including cancer development and progression, viral RNA degradation, and cellular stress responses. Moreover, these insights have the potential to fuel the advancement of therapeutic strategies targeting cancer and infectious diseases. (DPK/NW)
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