New research has identified and described a cellular process that, despite what textbooks say, has remained elusive to scientists until now — precisely how the copying of genetic material that, once started, is properly turned off.
The finding concerns a key process essential to life: the transcription phase of gene expression, which enables cells to live and do their jobs.
During transcription, an enzyme called RNA polymerase wraps itself around the double helix of DNA, using one strand to match nucleotides to make a copy of genetic material — resulting in a newly synthesized strand of RNA that breaks off when transcription is complete. That RNA enables production of proteins, which are essential to all life and perform most of the work inside cells.
Just as with any coherent message, RNA needs to start and stop in the right place to make sense. A bacterial protein called Rho was discovered more than 50 years ago because of its ability to stop, or terminate, transcription. In every textbook, Rho is used as a model terminator that, using its very strong motor force, binds to the RNA and pulls it out of RNA polymerase. But a closer look by these scientists showed that Rho wouldn’t be able to find the RNAs it needs to release using the textbook mechanism.
In a major scientific advance, the latest version of DeepMind’s AI system AlphaFold has been recognized as a solution to the 50-year-old grand challenge of protein structure prediction, often referred to as the ‘protein folding problem’, according to a rigorous independent assessment. This breakthrough could significantly accelerate biological research over the long term, unlocking new possibilities in disease understanding and drug discovery among other fields.
Today, results from CASP14 show that DeepMind’s latest AlphaFold system achieves unparalleled levels of accuracy in structure prediction. The system is able to determine highly-accurate structures in a matter of days. CASP, the Critical Assessment of protein Structure Prediction, is a biennial community-run assessment started in 1994, and the gold standard for assessing predictive techniques. Participants must blindly predict the structure of proteins that have only recently — or in some cases not yet — been experimentally determined, and wait for their predictions to be compared to experimental data.
The chip, developed at Imperial College London and known as TriSilix, is a ‘micro laboratory’ which performs a miniature version of the polymerase chain reaction (PCR) on the spot. PCR is the gold-standard test for detecting viruses and bacteria in biological samples such as bodily fluids, feces, or environmental samples.
Although PCR is usually performed in a laboratory, which means test results aren’t immediately available, this new lab-on-a-chip can process and present results in a matter of minutes.
The chip is made from silicon, the same material that is used to make electronic chips. Silicon itself is cheap, however, it is expensive to process into chips which requires massive, ‘extremely clean’ factories otherwise known as cleanrooms. To make the new lab-on-chip, the researchers developed a series of methods to produce the chips in a standard laboratory, cutting the costs and time they take to fabricate, potentially allowing them to be produced anywhere in the world.
Research findings by a KAIST team provide insight into the complex mechanism of cellular senescence and present a potential therapeutic strategy for reducing age-related diseases associated with the accumulation of senescent cells.
Simulations that model molecular interactions have identified an enzyme that could be targeted to reverse a natural aging process called cellular senescence. The findings were validated with laboratory experiments on skin cells and skin equivalent tissues, and published in the Proceedings of the National Academy of Sciences (PNAS).
“Our research opens the door for a new generation that perceives aging as a reversible biological phenomenon,” says Professor Kwang-Hyun Cho of the Department of Bio and Brain engineering at the Korea Advanced Institute of Science and Technology (KAIST), who led the research with colleagues from KAIST and Amorepacific Corporation in Korea.
Fluorescent imaging technique simultaneously captures different signal types from multiple locations in a live cell.
Within a single cell, thousands of molecules, such as proteins, ions, and other signaling molecules, work together to perform all kinds of functions — absorbing nutrients, storing memories, and differentiating into specific tissues, among many others.
Deciphering these molecules, and all of their interactions, is a monumental task. Over the past 20 years, scientists have developed fluorescent reporters they can use to read out the dynamics of individual molecules within cells. However, typically only one or two such signals can be observed at a time, because a microscope cannot distinguish between many fluorescent colors.
MIT researchers have now developed a way to image up to five different molecule types at a time, by measuring each signal from random, distinct locations throughout a cell. This approach could allow scientists to learn much more about the complex signaling networks that control most cell functions, says Edward Boyden, the Y. Eva Tan Professor in Neurotechnology and a professor of biological engineering, media arts and sciences, and brain and cognitive sciences at MIT.