mGreenLantern: a bright monomeric fluorescent protein with rapid expression and cell filling properties for neuronal imaging

Although ubiquitous in biological studies, the enhanced green and yellow fluorescent proteins (EGFP and EYFP) were not specifically optimized for neuroscience, and their underwhelming brightness and slow expression in brain tissue limits the fidelity of dendritic spine analysis and other indispensable techniques for studying neurodevelopment and plasticity. We hypothesized that EGFP’s low solubility in mammalian systems must limit the total fluorescence output of whole cells, and that improving folding efficiency could therefore translate into greater brightness of expressing neurons. By introducing rationally selected combinations of folding-enhancing mutations into GFP templates and screening for brightness and expression rate in human cells, we developed mGreenLantern, a fluorescent protein having up to sixfold greater brightness in cells than EGFP. mGreenLantern illuminates neurons in the mouse brain within 72 h, dramatically reducing lag time between viral transduction and imaging, while its high brightness improves detection of neuronal morphology using widefield, confocal, and two-photon microscopy. When virally expressed to projection neurons in vivo, mGreenLantern fluorescence developed four times faster than EYFP and highlighted long-range processes that were poorly detectable in EYFP-labeled cells. Additionally, mGreenLantern retains strong fluorescence after tissue clearing and expansion microscopy, thereby facilitating superresolution and whole-brain imaging without immunohistochemistry. mGreenLantern can directly replace EGFP/EYFP in diverse systems due to its compatibility with GFP filter sets, recognition by EGFP antibodies, and excellent performance in mouse, human, and bacterial cells. Our screening and rational engineering approach is broadly applicable and suggests that greater potential of fluorescent proteins, including biosensors, could be unlocked using a similar strategy.