Researchers found a new way to look at gene activity within a cell.
The ultra-efficient new method would allow scientists to study "1,000 genes in parallel in 10,000 single human cells," a University of Zurich press release reported.
Through this method the researchers found that there is a strong variation in the activity of genes and the spatial arrangement of transcript molecules in different cells.
"Whenever cells activate a gene, they produce gene specific transcript molecules, which make the function of the gene available to the cell. The measurement of gene activity is a routine activity in medical diagnostics, especially in cancer medicine," the press release reported.
Scientists usually determine gene activity by measuring the number of resulting transcript molecules, but the method can't determine the special arrangement of those molecules.
"[The method allows] for the first time, a parallel measurement of the amount and spatial organization of single transcript molecules in ten thousands single cells." This new method allows new insight into the "variability of gene activity within a single cell" that would have never been possible before.
The new method employs a combination of automated fluorescence, robots, and a supercomputer.
"When genes become active, specific transcript molecules are produced. We can stain them with the help of a robot," PhD student Thomas Stoeger, said.
The result is neon glowing images of transcript molecules, which are then analyzed by the supercomputer.
The researchers were expecting to find a high variability in the number of transcript molecules from cell-to-cell, what surprised them was the drastic difference between the molecule's spatial organizations.
"We realized that genes with a similar function also have a similar variability in the transcript patterns," Nico Battich, another Zurch PhD student, said. "This similarity exceeds the variability in the amount of transcript molecules, and allows us to predict the function of individual genes." The scientists suspect that transcript patterns are a countermeasure against the variability in the amount of transcript molecules. Thus, such patterns would be responsible for the robustness of processes within a cell."
"Our method will be of importance to basic research and the understanding of cancer tumors because it allows us to map the activity of genes within single tumor cells," study leader Professor Lucas Pelkmans, said.
