Protein-Based MnII Sensor for Selective Real-Time Metal Imaging
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Solution Overview
Problem
Current methods for visualizing and quantifying manganese(II) concentrations in cells are limited, lacking real-time and subcellular specificity, and existing sensors suffer from interference from other biologically relevant metals like calcium and magnesium.
Innovation Solution
Development of a genetically encoded fluorescent sensor, MnLaMP, based on the lanthanide-binding protein LanM, engineered to selectively respond to manganese(II) with high specificity over interfering metals, utilizing a FRET pair for real-time imaging and monitoring manganese fluxes in bacterial cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional fluorescent sensors are used to detect manganese(II), then real-time imaging capability is achieved, but selectivity is lost due to interference from calcium and magnesium
Solution Approach 1:
The sensor design incorporates a specific binding pocket with localized chemical properties (carboxylate-rich coordination environment) that creates selective affinity for manganese(II) over other metal ions. This local chemical environment differentiation enables the sensor to distinguish manganese(II) from calcium and magnesium while maintaining real-time imaging capability.
Solution Approach 2:
The sensor utilizes changes in fluorescence parameters (intensity, wavelength) upon manganese(II) binding to generate detectable signals. The conformational changes induced by manganese(II) binding alter the fluorescence properties of the sensor, enabling real-time detection while the specific binding affinity ensures selectivity.
2Measurement precision
If existing manganese sensors are designed with high affinity for manganese, then detection sensitivity is improved, but interference from iron and zinc increases
Solution Approach 1:
Instead of designing a sensor that directly competes with biological ligands for manganese binding, the invention uses lanmodulin's native lanthanide-binding capability and engineers it to bind manganese(II). This inverted approach leverages the protein's inherent high affinity and selectivity for certain metal ions, then adapts it for manganese detection, achieving both sensitivity and resistance to interference from iron and zinc.
Solution Approach 2:
The sensor combines the lanmodulin protein scaffold with engineered binding sites that have specific coordination chemistry properties. This composite structure integrates the protein's structural stability and metal-binding capability with tailored coordination environments that preferentially bind manganese(II) over iron and zinc, achieving both high sensitivity and selectivity.
3Device complexity
If small-molecule sensors are used for manganese detection, then molecular simplicity is achieved, but cellular localization becomes uncontrolled leading to artifacts
Solution Approach 1:
The genetically encoded sensor utilizes the cell's own protein synthesis and localization machinery to achieve proper cellular distribution. By being a protein, the sensor can be targeted to specific compartments (mitochondria, nucleus, cytoplasm) using standard protein localization signals, eliminating the need for separate loading steps and ensuring reliable, artifact-free localization.
Solution Approach 2:
The protein-based sensor serves multiple functions: it can be genetically encoded for stable expression, targeted to specific cellular compartments using standard localization sequences, and integrated into the cell's natural protein turnover pathways. This multi-functionality provides both controlled localization and ease of use, overcoming the limitations of small-molecule sensors.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables real-time imaging and quantification of manganese(II) fluxes in cells, providing insights into manganese physiology and laying the foundation for broader applications in metal separations and imaging.
Implementation Method 1
utilizing a FRET pair for real-time imaging and monitoring manganese fluxes in bacterial cells
Implementation Method 2
MnII being the predominant oxidation state of manganese in the cell... MnII-phosphate complexes... MnII transporters... coordination chemistry, as MnII is the lowest ion in the Irving-Williams series
Data Source
AI summary
Provided are proteins and protein-based sensors for detecting MnII. The proteins may have the following sequence: Z1-MPTTTTKVDIAAFDPDKDGTIHLKDALAAGSAAFDKLDPD-KDGTLHAKDLKGRVSEADLKKLDPDX1DGTLHKKDYLAAVEAQFKAAX2PDNDGTIX3ARX4LASPAGSALVNLIR-X5-Z2 (SEQ ID NO:1), where Z1 and Z2 correspond to a FRET pair, X1 is N or G, X2 is N or D, X3 is D or H, X4 is E or D, and X5 is optional and is the sequence GSGC (SEQ ID NO:40) and when X5 is present, then Z1 and Z2 are absent. Z1 and Z2 are optional. Also provided are methods of using the proteins to detect and separate MnII. Also provided are compositions, kits, and devices.