Optogenetic Microwell Array Screening System: A High-Throughput Engineering Platform for Genetically Encoded Fluorescent Indicators.
Optogenetic Microwell Array Screening System: A High-Throughput Engineering Platform for Genetically Encoded Fluorescent Indicators.
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光遗传学微孔阵列筛选系统:基因编码荧光指示剂的高通量工程平台。
DOI:
10.1021/acssensors.3c01573
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发表时间:
2023
期刊:
影响因子:
8.9
通讯作者:
Berndt,Andre
中科院分区:
文献类型:
--
作者:
Rappleye,Michael;Wait,SarahJ;Lee,JustinDaho;Siebart,JamisonC;Torp,Lily;Smith,Netta;Muster,Jeanot;Matreyek,KennethA;Fowler,DouglasM;Berndt,Andre
Genetically encoded fluorescent indicators (GEFIs) are protein-based optogenetic tools that change their fluorescence intensity when binding specific ligands in cells and tissues. GEFI encoding DNA can be expressed in cell subtypes while monitoring cellular physiological responses. However, engineering GEFIs with physiological sensitivity and pharmacological specificity often requires iterative optimization through trial-and-error mutagenesis while assessing their biophysical functionin vitroone by one. Here, the vast mutational landscape of proteins constitutes a significant obstacle that slows GEFI development, particularly for sensors that rely on mammalian host systems for testing. To overcome these obstacles, we developed a multiplexed high-throughput engineering platform called the optogenetic microwell array screening system (Opto-MASS) that functionally tests thousands of GEFI variants in parallel in mammalian cells. Opto-MASS represents the next step for engineering optogenetic tools as it can screen large variant libraries orders of magnitude faster than current methods. We showcase this system by testing over 13,000 dopamine and 21,000 opioid sensor variants. We generated a new dopamine sensor, dMASS1, with a >6-fold signal increase to 100 nM dopamine exposure compared to its parent construct. Our new opioid sensor, μMASS1, has a ∼4.6-fold signal increase over its parent scaffold’s response to 500 nM DAMGO. Thus, Opto-MASS can rapidly engineer new sensors while significantly shortening the optimization time for new sensors with distinct biophysical properties.
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影响因子:
7.3
作者:
Hackley CR;Mazzoni EO;Blau J
通讯作者:
Blau J
DOI:
10.1126/science.aat4422
发表时间:
2018-06-29
期刊:
Science (New York, N.Y.)
影响因子:
--
作者:
Patriarchi T;Cho JR;Merten K;Howe MW;Marley A;Xiong WH;Folk RW;Broussard GJ;Liang R;Jang MJ;Zhong H;Dombeck D;von Zastrow M;Nimmerjahn A;Gradinaru V;Williams JT;Tian L
通讯作者:
Tian L
影响因子:
16.6
作者:
通讯作者:
--
影响因子:
8.6
作者:
Erdogan, Mutlu;Fabritius, Arne;Griesbeck, Oliver
通讯作者:
Griesbeck, Oliver
影响因子:
16.6
作者:
Kroning, Kayla E.;Wang, Wenjing
通讯作者:
Wang, Wenjing