Literature DB >> 26061224

Construction of a robust and sensitive arginine biosensor through ancestral protein reconstruction.

Jason H Whitfield1, William H Zhang1, Michel K Herde2, Ben E Clifton1, Johanna Radziejewski2, Harald Janovjak3, Christian Henneberger2,4, Colin J Jackson1.   

Abstract

Biosensors for signaling molecules allow the study of physiological processes by bringing together the fields of protein engineering, fluorescence imaging, and cell biology. Construction of genetically encoded biosensors generally relies on the availability of a binding "core" that is both specific and stable, which can then be combined with fluorescent molecules to create a sensor. However, binding proteins with the desired properties are often not available in nature and substantial improvement to sensors can be required, particularly with regard to their durability. Ancestral protein reconstruction is a powerful protein-engineering tool able to generate highly stable and functional proteins. In this work, we sought to establish the utility of ancestral protein reconstruction to biosensor development, beginning with the construction of an l-arginine biosensor. l-arginine, as the immediate precursor to nitric oxide, is an important molecule in many physiological contexts including brain function. Using a combination of ancestral reconstruction and circular permutation, we constructed a Förster resonance energy transfer (FRET) biosensor for l-arginine (cpFLIPR). cpFLIPR displays high sensitivity and specificity, with a Kd of ∼14 µM and a maximal dynamic range of 35%. Importantly, cpFLIPR was highly robust, enabling accurate l-arginine measurement at physiological temperatures. We established that cpFLIPR is compatible with two-photon excitation fluorescence microscopy and report l-arginine concentrations in brain tissue.
© 2015 The Protein Society.

Entities:  

Keywords:  Förster resonance energy transfer (FRET); ancestral protein reconstruction; biosensor; fluorescence; neurobiology; nitric oxide; protein engineering

Mesh:

Substances:

Year:  2015        PMID: 26061224      PMCID: PMC4570536          DOI: 10.1002/pro.2721

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


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