@article {65902,
	title = {Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning.},
	journal = {Cell},
	volume = {183},
	year = {2020},
	month = {2020 Dec 23},
	pages = {1986-2002.e26},
	abstract = {<p>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 in\&nbsp;vitro and in\&nbsp;vivo serotonin detection, respectively.</p>
},
	issn = {1097-4172},
	doi = {10.1016/j.cell.2020.11.040},
	author = {Unger, Elizabeth K and Keller, Jacob P and Altermatt, Michael and Liang, Ruqiang and Matsui, Aya and Dong, Chunyang and Hon, Olivia J and Yao, Zi and Sun, Junqing and Banala, Samba and Flanigan, Meghan E and Jaffe, David A and Hartanto, Samantha and Carlen, Jane and Mizuno, Grace O and Borden, Phillip M and Shivange, Amol V and Cameron, Lindsay P and Sinning, Steffen and Underhill, Suzanne M and Olson, David E and Amara, Susan G and Temple Lang, Duncan and Rudnick, Gary and Marvin, Jonathan S and Lavis, Luke D and Lester, Henry A and Alvarez, Veronica A and Fisher, Andrew J and Prescher, Jennifer A and Kash, Thomas L and Yarov-Yarovoy, Vladimir and Gradinaru, Viviana and Looger, Loren L and Tian, Lin}
}
@article {49023,
	title = {Aberrant calcium signaling in astrocytes inhibits neuronal excitability in a human Down syndrome stem cell model.},
	journal = {Cell Reports},
	volume = {24},
	year = {2018},
	month = {2018 Jul 10},
	pages = {355-65},
	abstract = {<p>Down syndrome (DS) is a genetic disorder that causes cognitive impairment. The staggering effects associated with an extra copy of human chromosome 21 (HSA21) complicates mechanistic understanding of DS pathophysiology. We examined the neuron-astrocyte interplay in a fully recapitulated HSA21 trisomy cellular model differentiated from DS-patient-derived induced pluripotent stem cells (iPSCs). By combining calcium imaging with genetic approaches, we discovered the functional defects of DS astroglia and their effects on neuronal excitability. Compared with control isogenic astroglia, DS astroglia exhibited more-frequent spontaneous calcium fluctuations, which reduced the excitability of co-cultured neurons. Furthermore, suppressed neuronal activity could be rescued by abolishing astrocytic spontaneous calcium activity either chemically by blocking adenosine-mediated signaling or genetically by knockdown of inositol triphosphate (IP3) receptors or S100B, a calcium binding protein coded on HSA21. Our results suggest a mechanism by which DS alters the function of astrocytes, which subsequently disturbs neuronal excitability.</p>
},
	doi = {10.1101/247585},
	author = {Tian, Lin and Or, Grace and Wang, Yinxue and Shi, Guilai and Wang, Yizhi and Sun, Junqing and Papadopoulos, Stelios and Broussard, Gerard and Unger, Elizabeth and Deng, Wenbin and Weick, Jason and Bhattacharyya, Anita and Chen, Chao-Yin and Yu, Guoqiang and Looger, Loren L}
}
