Final Report Summary - TRNAPROLIF (Control of translation efficiency in proliferating and differentiated mammalian cells)
One of the most crucial decisions in the life of a cell in a body is to divide or not to divide. In this ERC grant we discovered that the protein translation machinery operates under two distinct modes in these two life stages of cells. The study was based on the well-known existence of “synonyms” in the language of DNA: different three-letter portions of the genetic code that encode the same amino acid, a building block of proteins. When the genetic code is translated into proteins – that is, when amino acids are manufactured on the basis of a particular DNA sequence – each synonym has its own decoding molecule, called transfer RNA (tRNA), which enables the translation. A tRNA is a two-headed molecular machine that on one end “reads” different synonyms of the code and on the other supplies the required amino acid for the synthesized protein.
Until this ERC project, the existence of more than 60 genetic three-letter synonyms, each having a corresponding tRNA, was not thought to have a major bearing on cell division. The ratios of different tRNAs were thought to be constant throughout the life of each cell, and in any event deviations or fluctuations in these ratios were not known to have particular biological significance. This project started when we discovered a potential role played by the relative amounts of different tRNAs in the cell at normal and malignant life states. The first sample of data that revealed this new mode of regulation was from more than 300 cancer patients’ profiles, which contained a large volume of tRNA expression data. The analysis revealed that two distinct subsets of tRNAs are present in the cell depending on whether it is cancerous or not.
We went on to develop algorithms for comparisons of the diverse cancerous samples. The analysis revealed a striking similarity in tRNA signatures among cancerous cells and healthy dividing cells. In other words, by measuring the relative amounts of tRNAs it was possible to tell whether the cell is dividing, as is the case with cancerous cells, embryonic stem cells and other stem cells, or whether it’s a healthy cell that has stopped dividing after having specialized into a particular tissue type, such as a bone, blood or skin. In fact, all cancerous cells in the study were found to have characteristic tRNA signatures, which could be further classified by cancer type.
At later stages of this ERC grant we progressed towards establishing a direct causal connection between tRNA expression patterns and cellular states – dividing or not. We adapted the CRISPR method for gene editing and silencing to knock out individual tRNAs, one at a time, from cells in diverse states of proliferation or differentiation. We found pro-proliferation, and pro-differentiation tRNAs – distinct tRNA genes that are needed only when cells divide or when they differentiate. These data open the possibility for a new concept for future treatment of cancer – targeted attack on these tRNAs that are exclusively needed for dividing, but not for non-dividing cells.
I acknowledge the public relationships office at the Weizmann Institute for participation in drafting this press release.
Until this ERC project, the existence of more than 60 genetic three-letter synonyms, each having a corresponding tRNA, was not thought to have a major bearing on cell division. The ratios of different tRNAs were thought to be constant throughout the life of each cell, and in any event deviations or fluctuations in these ratios were not known to have particular biological significance. This project started when we discovered a potential role played by the relative amounts of different tRNAs in the cell at normal and malignant life states. The first sample of data that revealed this new mode of regulation was from more than 300 cancer patients’ profiles, which contained a large volume of tRNA expression data. The analysis revealed that two distinct subsets of tRNAs are present in the cell depending on whether it is cancerous or not.
We went on to develop algorithms for comparisons of the diverse cancerous samples. The analysis revealed a striking similarity in tRNA signatures among cancerous cells and healthy dividing cells. In other words, by measuring the relative amounts of tRNAs it was possible to tell whether the cell is dividing, as is the case with cancerous cells, embryonic stem cells and other stem cells, or whether it’s a healthy cell that has stopped dividing after having specialized into a particular tissue type, such as a bone, blood or skin. In fact, all cancerous cells in the study were found to have characteristic tRNA signatures, which could be further classified by cancer type.
At later stages of this ERC grant we progressed towards establishing a direct causal connection between tRNA expression patterns and cellular states – dividing or not. We adapted the CRISPR method for gene editing and silencing to knock out individual tRNAs, one at a time, from cells in diverse states of proliferation or differentiation. We found pro-proliferation, and pro-differentiation tRNAs – distinct tRNA genes that are needed only when cells divide or when they differentiate. These data open the possibility for a new concept for future treatment of cancer – targeted attack on these tRNAs that are exclusively needed for dividing, but not for non-dividing cells.
I acknowledge the public relationships office at the Weizmann Institute for participation in drafting this press release.