1. Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning
- Author
-
Jonathan S. Marvin, Lindsay P. Cameron, Steffen Sinning, Jacob P. Keller, Duncan Temple Lang, Jennifer A. Prescher, Phillip M. Borden, Elizabeth K. Unger, Susan G. Amara, Veronica A. Alvarez, Gary Rudnick, Chunyang Dong, Jane Carlen, Meghan E. Flanigan, Loren L. Looger, Samantha Hartanto, Ruqiang Liang, Vladimir Yarov-Yarovoy, Amol V. Shivange, Michael Altermatt, Thomas L. Kash, Andrew J. Fisher, Aya Matsui, David A. Jaffe, Lin Tian, Samba Banala, Suzanne M. Underhill, Luke D. Lavis, David E. Olson, Grace O. Mizuno, Zi Yao, Olivia J Hon, Junqing Sun, Viviana Gradinaru, and Henry A. Lester
- Subjects
Sleep wake ,computer.software_genre ,Inbred C57BL ,Medical and Health Sciences ,Machine Learning ,Mice ,0302 clinical medicine ,Fear conditioning ,Serotonin transporter ,Serotonin Plasma Membrane Transport Proteins ,0303 health sciences ,Behavior, Animal ,biology ,Brain ,Biological Sciences ,Directed evolution ,Amygdala ,OSTA ,Mental Health ,fear-learning ,Algorithms ,Protein Binding ,Serotonin release ,Serotonin ,Bioengineering ,Machine learning ,Serotonergic ,Basic Behavioral and Social Science ,Article ,General Biochemistry, Genetics and Molecular Biology ,03 medical and health sciences ,iSeroSnFR ,fiber photometry ,Behavioral and Social Science ,Animals ,Humans ,Fear learning ,Amino Acid Sequence ,Wakefulness ,030304 developmental biology ,Behavior ,Photons ,Binding Sites ,business.industry ,Animal ,SERT ,Neurosciences ,Mice, Inbred C57BL ,fluorescence protein sensor ,Kinetics ,HEK293 Cells ,social behaviors ,biology.protein ,Linear Models ,sleep-wake ,Artificial intelligence ,Directed Molecular Evolution ,business ,Sleep ,computer ,030217 neurology & neurosurgery ,Developmental Biology - Abstract
Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which has been hampered by our inability to monitor serotonin release and transport with high spatial and temporal resolution. We developed and applied a binding-pocket redesign strategy, guided by machine learning, to create a high-performance, soluble, fluorescent serotonin sensor (iSeroSnFR), enabling optical detection of millisecond-scale serotonin transients. We demonstrate that iSeroSnFR can be used to detect serotonin release in freely behaving mice during fear conditioning, social interaction, and sleep/wake transitions. We also developed a robust assay of serotonin transporter function and modulation by drugs. We expect that both machine-learning-guided binding-pocket redesign and iSeroSnFR will have broad utility for the development of other sensors and invitro and invivo serotonin detection, respectively.
- Published
- 2020
- Full Text
- View/download PDF