NIH BRAIN Initiative scientists used machine learning to redesign a bacterial ‘Venus flytrap’ protein that can monitor brain serotonin levels in real time.
Serotonin is a neurochemical that plays a critical role in the way the brain controls our thoughts and feelings. For example, many antidepressants are designed to alter serotonin signals sent between neurons. In an article in the journal Cell, researchers described how they used advanced genetic engineering techniques to transform a bacterial protein into a new research tool that may help monitor serotonin transmission with greater fidelity than current methods. Preclinical experiments, primarily in mice, showed that the sensor could detect subtle, real-time changes in brain serotonin levels during sleep, fear, and social interactions, as well as test the effectiveness of new psychoactive drugs.
Current methods can only detect broad changes in serotonin signaling. In this study, the researchers transformed a nutrient-grabbing, Venus flytrap-shaped bacterial protein into a highly sensitive sensor that fluorescently lights up when it captures serotonin.
The researchers used machine learning algorithms to help a computer ‘think up’ 250,000 new designs. After three rounds of testing, the scientists settled on one. Initial experiments suggested that the new sensor reliably detected serotonin at different levels in the brain while having little or no reaction to other neurotransmitters or similarly shaped drugs. Experiments in mouse brain slices showed that the sensor responded to serotonin signals sent between neurons at synaptic communications points. Meanwhile, experiments on cells in petri dishes suggested that the sensor could effectively monitor changes in these signals caused by drugs, including cocaine, MDMA and several commonly used antidepressants.
Finally, experiments in mice showed that the sensor could help scientists study serotonin neurotransmission under more natural conditions. For instance, the researchers witnessed an expected rise in serotonin levels when mice were awake and a fall as mice fell asleep. They also spotted a greater drop when the mice eventually entered the deeper, R.E.M. sleep states. Traditional serotonin monitoring methods would have missed these changes. In addition, the scientists saw serotonin levels rise differently in two separate brain fear circuits when mice were warned of a foot shock by a ringing bell.
News Source: NIH
