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Optimization of GPCR-based fluorescent sensors for large-scale multiplexed in vivo imaging of neuromodulation

Optimization of GPCR-based fluorescent sensors for large-scale multiplexed in vivo imaging of neuromodulation
基于 GPCR 的荧光传感器的优化,用于神经调节的大规模多重体内成像
批准号:
10400198
负责人:
Samuel Andrew Hires
金额:
$89.08万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-05-01 至 2025-07-31

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中文摘要
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英文摘要
Neuromodulators regulate addiction, attention, cognition, mood, memory, motivation, sleep, and more through their influence on brain circuits. Classic tools for measuring neuromodulation in the brain have poor spatial and temporal resolution. This has hampered the discovery of the diverse and complex functions neuromodulation plays during behavior. Over the past few years, new indicators for imaging neuromodulator dynamics have begun to dismantle these barriers. However, all existing neuromodulator indicators have significant limitations. The goal of this proposal is to optimize our GPCR-activation-based (GRAB) genetically-encoded fluorescent indicators of four major neuromodulators: dopamine (DA), acetylcholine (ACh), norepinephrine (NE), and serotonin (5-HT). We will make their responses bigger and more specific, create red versions for multiplexed imaging, and make them easier for end-users to successfully deploy in vivo. In Aim 1, we will optimize GRAB indicators for DA, ACh, NE, and 5-HT by iteratively screening libraries via high-content confocal imaging and FACS. We will vary insertion site, linkers, cpGFP, FP-GPCR protein surface interface, and thermostabilizing GPCR residues on a range of chimeric GCPR sensor backbones. Library generation will be prioritized by computational prediction of function from GPCR structures. The dimensions of optimization will be brightness, dF/F0, ligand selectivity, affinity, and non-disruption of endogenous signals. Top hits will be validated following long-term expression in mammalian brain slice and behaving mice. Our targeted performance levels are: 1000x ligand selectivity across all neuromodulators (3rd gen), >5x SNR improvement over 2nd generation indicators in vitro and in vivo (3rd gen), and reliable single-trial subcellular resolution of graded responses with in vivo 2-photon imaging of cortex during behavior for all neuromodulators (4th gen). In Aim 2, we will use the same approach as Aim 1 to develop and validate in vivo 1st and 2nd generation red GRABs for the same neuromodulators to enable simultaneous imaging of multiple signals. Our targeted performance levels for second generation, spectrally orthogonal red GRABs are 10x dF/F in vitro, >50% dF/F in vivo responses. We will also engineer out any photoactivation of red GRAB fluorescence, demonstrate multiplexed imaging and optogenetic stimulation with zero opsin excitation crosstalk from imaging light. In Aim 3, we will optimize GRAB packaging and distribution for maximum end-user ease of use. We will quantify the best FPs for in vivo coexpression with GRABs, engineer viral-genetic strategies for robust, brain- wide GRAB expression from systemic AAV injection, and make cre-reporter mouse lines for the best green GRAB of each neuromodulator. Optimized plasmids, AAVs, and mice will be broadly disseminated. Successful completion of our Aims will yield an optimized suite of powerful molecular tools packaged for maximum utility and ease of use. Since these probes are well-suited for a large number of investigators, they will have a multiplicative impact on our understanding of neural circuit function and dysfunction.
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Optimization of GPCR-based fluorescent sensors for large-scale multiplexed in vivo imaging of neuromodulation
  • 批准号:
    10166173
  • 项目类别:
  • 资助金额:
    $95.99万
  • 财政年份:
    2021
  • 负责人:
    Samuel Andrew Hires
  • 依托单位:
Optimization of GPCR-based fluorescent sensors for large-scale multiplexed in vivo imaging of neuromodulation
  • 批准号:
    10700803
  • 项目类别:
  • 资助金额:
    $90.25万
  • 财政年份:
    2021
  • 负责人:
    Samuel Andrew Hires
  • 依托单位:
Exploring Anatomical and Circuit Plasticity Deficits in Fmr1 Mice During Tactile Learning
  • 批准号:
    9245579
  • 项目类别:
  • 资助金额:
    $29.26万
  • 财政年份:
    2017
  • 负责人:
    Samuel Andrew Hires
  • 依托单位:
Cortical circuit mechanisms of sensorimotor object localization
  • 批准号:
    10317072
  • 项目类别:
  • 资助金额:
    $36.09万
  • 财政年份:
    2017
  • 负责人:
    Samuel Andrew Hires
  • 依托单位:
海外基金