Summary: A new technique may offer superior predictions for the outcomes of diseases with a genetic component, from Alzheimer’s disease to depression.
Source: University of Virginia Health System.
New technique could offer answers on Alzheimer’s, autism, cancer and more.
An international team of researchers has found a way to diagnose disease and predict patient outcomes simply by measuring unbelievably small changes in interactions between molecules inside the body. The simple new technique could offer vastly superior predictions of disease severity in a huge range of conditions with a genetic component, such as Alzheimer’s, autism, cancer, cardiovascular disease, diabetes, obesity, schizophrenia and depression.
Measuring Gene Mutations
Gene mutations that cause disease physically alter the interactions of molecules that cells use to communicate with each other. Until now, scientists have had no easy way to measure the incredibly subtle changes in these interaction forces. But researcher J. Julius Zhu, PhD, of the University of Virginia School of Medicine, and his collaborators have developed a method to accurately and efficiently calculate these tiny changes. It’s a feat that requires incredible precision: Force is typically measured in newtons – the amount of force needed to accelerate one kilogram of mass one meter per second squared – but Zhu’s technique measures on a scale of piconewtons – one trillionth of a newton.
Zhu, of UVA’s Department of Pharmacology, and his colleagues have used the new technique to show that gene mutations responsible for mental-health diseases change molecular interactions by a few piconewtons. These small changes then have a tremendous ripple effect. The researchers found the molecular changes lead to harmful changes in how the cells communicate – and, ultimately, in cognitive ability. By measuring the molecular changes, the scientists could predict the resulting cognitive impairment. In essence, the researchers are directly linking these tiny molecular changes to big changes in human behavior.
Diagnosing Disease
Zhu’s approach represents a new use for a high-tech scientific instrument called “optical tweezers” that uses a highly focused laser to hold and move microscopic objects, much like regular tweezers might be used to grip and move a splinter. Using the optical tweezers, the scientists can measure the force required to break up intermolecular bonds between the signaling molecules inside the body, allowing them gauge the effects of gene mutations in patients. The researchers say the technique is simple to do and will dramatically improve our ability to diagnose mental illness and many other diseases.
Funding: The work was supported by the National Research Foundation of Korea, the National Natural Science Foundation of China, the Chinese Ministry of Education Project 111 Program, the National Key R&D Program of China and the National Institutes of Health. (NIH grants NS065183, NS089578, NS053570, NS091452, NS094980 and NS092548.)
Source: Josh Barney – University of Virginia Health System
Image Source: NeuroscienceNews.com image is in the public domain.
Original Research: Abstract for “Piconewton-Scale Analysis of Ras-BRaf Signal Transduction with Single-Molecule Force Spectroscopy” by Chae-Seok Lim, Cheng Wen, Yanghui Sheng, Guangfu Wang, Zhuan Zhou, Shiqiang Wang, Huaye Zhang, Anpei Ye, and J. Julius Zhu in Small. Published online August 15 2017 doi:10.1002/smll.201701972
[cbtabs][cbtab title=”MLA”]University of Virginia Health System “Doctors Can Now Predict the Severity of Your Disease by Measuring Molecules.” NeuroscienceNews. NeuroscienceNews, 12 September 2017.
<https://neurosciencenews.com/disease-molecular-monitoring-7470/>.[/cbtab][cbtab title=”APA”]University of Virginia Health System (2017, September 12). Doctors Can Now Predict the Severity of Your Disease by Measuring Molecules. NeuroscienceNew. Retrieved September 12, 2017 from https://neurosciencenews.com/disease-molecular-monitoring-7470/[/cbtab][cbtab title=”Chicago”]University of Virginia Health System “Doctors Can Now Predict the Severity of Your Disease by Measuring Molecules.” https://neurosciencenews.com/disease-molecular-monitoring-7470/ (accessed September 12, 2017).[/cbtab][/cbtabs]
Abstract
Piconewton-Scale Analysis of Ras-BRaf Signal Transduction with Single-Molecule Force Spectroscopy
Intermolecular interactions dominate the behavior of signal transduction in various physiological and pathological cell processes, yet assessing these interactions remains a challenging task. Here, this study reports a single-molecule force spectroscopic method that enables functional delineation of two interaction sites (≈35 pN and ≈90 pN) between signaling effectors Ras and BRaf in the canonical mitogen-activated protein kinase (MAPK) pathway. This analysis reveals mutations on BRaf at Q257 and A246, two sites frequently linked to cardio-faciocutaneous syndrome, result in ≈10−30 pN alterations in Ras[BOND]BRaf intermolecular binding force. The magnitude of changes in Ras[BOND]BRaf binding force correlates with the size of alterations in protein affinity and in α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-sensitive glutamate receptor (-R)-mediated synaptic transmission in neurons expressing replacement BRaf mutants, and predicts the extent of learning impairments in animals expressing replacement BRaf mutants. These results establish single-molecule force spectroscopy as an effective platform for evaluating the piconewton-level interaction of signaling molecules and predicting the behavior outcome of signal transduction.
“Piconewton-Scale Analysis of Ras-BRaf Signal Transduction with Single-Molecule Force Spectroscopy” by Chae-Seok Lim, Cheng Wen, Yanghui Sheng, Guangfu Wang, Zhuan Zhou, Shiqiang Wang, Huaye Zhang, Anpei Ye, and J. Julius Zhu in Small. Published online August 15 2017 doi:10.1002/smll.201701972
