mGreenLantern: a bright monomeric fluorescent protein with rapid expression and cell filling properties for neuronal imaging
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- Benjamin C. Campbell
- Helen and Robert Appel Alzheimer’s Disease Research Institute, Weill Cornell Medicine, New York, NY 10021;
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- Elisa M. Nabel
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029;
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- Mitchell H. Murdock
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021;
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- Cristina Lao-Peregrin
- Department of Psychiatry, Weill Cornell Medicine, Cornell University, New York, NY 10021;
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- Pantelis Tsoulfas
- Department of Biomedical Sciences, Marquette University, Milwaukee, WI 53211;
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- Murray G. Blackmore
- Department of Neurological Surgery, Miami Project to Cure Paralysis, University of Miami Miller School of Medicine, Miami, FL 33136;
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- Francis S. Lee
- Department of Psychiatry, Weill Cornell Medicine, Cornell University, New York, NY 10021;
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- Conor Liston
- Helen and Robert Appel Alzheimer’s Disease Research Institute, Weill Cornell Medicine, New York, NY 10021;
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- Hirofumi Morishita
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029;
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- Gregory A. Petsko
- Helen and Robert Appel Alzheimer’s Disease Research Institute, Weill Cornell Medicine, New York, NY 10021;
抄録
<jats:title>Significance</jats:title> <jats:p>We have developed a fluorescent protein, mGreenLantern, that features exceptionally high brightness in mouse, bacterial, and human cells (up to sixfold brighter than EGFP) and have demonstrated its superior ability to highlight neuronal morphology compared to EGFP and EYFP. Screening fluorescent protein mutants based on whole-cell brightness while evaluating expression kinetics in lysate enabled us to identify variants exhibiting striking divergences between their computed spectroscopic brightness and actual performance in cells. mGreenLantern additionally features unusually high chemical and thermodynamic stability and is compatible with existing GFP filter sets, excitation sources, commercial EGFP antibodies, expansion microscopy, and whole-brain tissue clearing. Our hypothesis-driven engineering strategy represents a generalizable method with great potential to enhance the performance of constitutive reporters and GFP-based biosensors.</jats:p>
収録刊行物
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- Proceedings of the National Academy of Sciences
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Proceedings of the National Academy of Sciences 117 (48), 30710-30721, 2020-11-18
Proceedings of the National Academy of Sciences