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Commun Biol. 2019 Sep 17;2:344. doi: 10.1038/s42003-019-0589-x. eCollection 2019.

Bright split red fluorescent proteins for the visualization of endogenous proteins and synapses.

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1The UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, CA 94143 USA.
2Department of Biological Sciences, San Jose State University, San Jose, CA 95192 USA.
3Department of Bioengineering and Therapeutic Sciences, University of California in San Francisco, San Francisco, CA 94143 USA.
4School of Physics and Astronomy, University of Minnesota, Minneapolis, MN 55455 USA.
5School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084 China.
6Department of Pharmaceutical Chemistry, University of California in San Francisco, San Francisco, CA 94143 USA.
7Department Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA 94143 USA.
Chan Zuckerberg Biohub, San Francisco, CA 94158 USA.


Self-associating split fluorescent proteins (FPs) are split FPs whose two fragments spontaneously associate to form a functional FP. They have been widely used for labeling proteins, scaffolding protein assembly and detecting cell-cell contacts. Recently developments have expanded the palette of self-associating split FPs beyond the original split GFP1-10/11. However, these new ones have suffered from suboptimal fluorescence signal after complementation. Here, by investigating the complementation process, we have demonstrated two approaches to improve split FPs: assistance through SpyTag/SpyCatcher interaction and directed evolution. The latter has yielded two split sfCherry3 variants with substantially enhanced overall brightness, facilitating the tagging of endogenous proteins by gene editing. Based on sfCherry3, we have further developed a new red-colored trans-synaptic marker called Neuroligin-1 sfCherry3 Linker Across Synaptic Partners (NLG-1 CLASP) for multiplexed visualization of neuronal synapses in living C. elegans, demonstrating its broad applications.


Fluorescence imaging; Fluorescent proteins; Genetic engineering; Neural circuits

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