Self-complementing split fluorescent protein (split FP) consists of FP1-10 and FP11 fragments, which are non-fluorescent by themselves. Upon self-assembly, they reconstitute fluorescence. Compared to a full-length FP, FP11 is >10 times smaller (~16 a.a.), making it a modular tag. By combining directed evolution in E.coli and circular permutation of FPs, I have engineered numerous color variants of split FP with distinct binding specificities. Due to its small size, FP11 can be integrated into the genome via CRISPR with minimal genomic perturbation, enabling efficient visualization of endogenous proteins. In addition, FP11 can be tagged to a protein of interest in tandem for signal amplification.
The human brain consists of billions of intertwining neurons, all of which become precisely wired during development. But how does our brain know where to make neuronal connections? To address this question, I turn to embryonic motor neurons in Drosophila, which exhibit well-characterized sequences of axonal and dendritic formation. I am particularly interested in cell adhesion molecules, or CAMs, as they allow neurons to integrate cellular interactions into positional cues by mix-and-matching. Using fly genetics and imaging tools (including our own split FP system!), I study localization and function of CAMs and how their misregulation could lead to neurodevelopmental disorders.
Another layer of intercellular communications is mediated by a biomolecule called glycan. I am particularly interested in glycosaminoglycan, or GAG, which is a long chain of sugar modified by different pattens of sulfates. This "sulfation code" is relevant in medicine since some distinct sulfation patterns of GAGs are associated with human diseases, including Alzheimer's disease and cancer. In my master's thesis, I accidentally found that a GAG-binding protein, Cochlin, recognizes a unique subset of sulfation patterns highly expressed in cancers and heart diseases. My future goal is to redesign Cochlin and diversify its binding specificity toward recognizing an array of GAG sulfation patterns to decipher the "sulfation code".
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