A genetically encoded, high-signal-to-noise maltose sensor

Area of Science:

• Biochemistry
• Molecular Biology
• Genetics

Background:

• Genetically encoded indicators are vital tools for visualizing biological processes.
• Periplasmic binding proteins (PBPs) are bacterial proteins that bind specific molecules.
• Developing novel sensors for sugars like maltose is important for understanding cellular metabolism.

Purpose of the Study:

• To create a family of high-signal-to-noise, single-wavelength genetically encoded indicators for maltose.
• To optimize these sensors for brightness and maltose-dependent fluorescence changes.
• To demonstrate the versatility of these sensors in various biological contexts.

Main Methods:

• Insertion of circularly permuted fluorescent proteins into the Escherichia coli maltodextrin-binding protein (a PBP).
• Iterative optimization of sensor properties for imaging under one- and two-photon illumination.
• Tuning of maltose affinity and alteration of binding specificity using literature mutations.

Main Results:

• Generation of a four-color family of maltose indicators with high signal-to-noise ratios.
• Successful optimization for brightness and significant maltose-dependent fluorescence increases.
• Demonstrated ability to visualize maltose transport in E. coli and extracellular maltose in mammalian cells.

Conclusions:

• The developed genetically encoded maltose sensors are effective for real-time biological imaging.
• The methodology is adaptable for creating indicators for other analytes using the PBP scaffold.
• This work provides a foundation for reverse-engineering complex biological systems by visualizing key molecules.