Toolkit/FRET-based GECI sensors

FRET-based GECI sensors

Construct Pattern·Research·Since 2014

Also known as: Förster Resonance Energy Transfer-based sensors, FRET-based sensors

Taxonomy: Mechanism Branch / Architecture. Workflows sit above the mechanism and technique branches rather than replacing them.

Summary

From a variety of initial designs two have emerged as promising prototypes for further optimization: FRET (Förster Resonance Energy Transfer)-based sensors and single fluorophore sensors of the GCaMP family.

Usefulness & Problems

Why this is useful

FRET-based sensors are presented as one of the two main GECI design classes that emerged as promising prototypes. The review indicates that recent optimization efforts improved their performance.; genetically encoded calcium sensing; further optimization of calcium indicators

Source:

FRET-based sensors are presented as one of the two main GECI design classes that emerged as promising prototypes. The review indicates that recent optimization efforts improved their performance.

Source:

genetically encoded calcium sensing

Source:

further optimization of calcium indicators

Problem solved

They provide a genetically encoded sensor architecture for calcium imaging. The review treats them as a viable branch for continued performance optimization.; providing one of the main prototype architectures for genetically encoded calcium indicators

Source:

They provide a genetically encoded sensor architecture for calcium imaging. The review treats them as a viable branch for continued performance optimization.

Source:

providing one of the main prototype architectures for genetically encoded calcium indicators

Problem links

providing one of the main prototype architectures for genetically encoded calcium indicators

Literature

They provide a genetically encoded sensor architecture for calcium imaging. The review treats them as a viable branch for continued performance optimization.

Source:

They provide a genetically encoded sensor architecture for calcium imaging. The review treats them as a viable branch for continued performance optimization.

Published Workflows

Objective: Optimize genetically encoded calcium indicators to improve in vivo calcium imaging and neuronal activity readout.

Why it works: The review states that recent efforts combining structural analysis, engineering, and screening broke important performance thresholds in both major GECI classes.

calcium-dependent fluorescent sensingFRET-based signal transductionsingle-fluorophore signal transductionstructural analysisengineeringscreening

Stages

  1. 1.
    Prototype class prioritization(decision_gate)

    The review narrows a variety of initial designs to two prototype classes that are worth continued optimization.

    Selection: Identify initial GECI designs that emerged as promising prototypes for further optimization.

  2. 2.
    Structure-guided engineering and screening(broad_screen)

    This stage is presented as the route by which recent generations crossed important performance thresholds.

    Selection: Use structural analysis, engineering, and screening to improve sensor performance.

  3. 3.
    Post-threshold functional quality assessment(functional_characterization)

    The review explicitly says that even after performance improvements, other aspects of sensor function deserve attention.

    Selection: Evaluate additional aspects of sensor function after major performance gains.

  4. 4.
    Spectral and expression-platform expansion(secondary_characterization)

    The review identifies spectral improvement and better expression resources as remaining needs for technology maturation.

    Selection: Develop sensors with more favorable red or infrared emission and create stable or conditional expression lines.

Taxonomy & Function

Primary hierarchy

Mechanism Branch

Architecture: A reusable architecture pattern for arranging parts into an engineered system.

Target processes

recombinationselection

Implementation Constraints

cofactor dependency: cofactor requirement unknownencoding mode: genetically encodedimplementation constraint: context specific validationoperating role: sensor

The abstract supports that their improvement relied on structural analysis, engineering, and screening. As GECIs, they also require expression in living tissues or designated cell types for use.; requires continued structural analysis, engineering, and screening for optimization

The abstract does not specify that this class has fully resolved issues such as linearity, toxicity, or slow kinetics. It also does not state that it already satisfies the need for red or infrared emission.; remaining issues in sensor function still apply at the class level

Validation

Cell-freeBacteriaMammalianMouseHumanTherapeuticIndep. Replication

Supporting Sources

Ranked Claims

Claim 1design class prioritizationsupports2014Source 1needs review

Among initial GECI designs, FRET-based sensors and single-fluorophore GCaMP-family sensors emerged as promising prototypes for further optimization.

Claim 2performance trendsupports2014Source 1needs review

Recent structural analysis, engineering, and screening improved both FRET-based and GCaMP-family GECIs enough to cross important performance thresholds.

Approval Evidence

1 source2 linked approval claimsfirst-pass slug fret-based-geci-sensors
From a variety of initial designs two have emerged as promising prototypes for further optimization: FRET (Förster Resonance Energy Transfer)-based sensors and single fluorophore sensors of the GCaMP family.

Source:

design class prioritizationsupports

Among initial GECI designs, FRET-based sensors and single-fluorophore GCaMP-family sensors emerged as promising prototypes for further optimization.

Source:

performance trendsupports

Recent structural analysis, engineering, and screening improved both FRET-based and GCaMP-family GECIs enough to cross important performance thresholds.

Source:

Comparisons

Source-stated alternatives

The abstract directly contrasts FRET-based sensors with single-fluorophore sensors of the GCaMP family.

Source:

The abstract directly contrasts FRET-based sensors with single-fluorophore sensors of the GCaMP family.

Source-backed strengths

identified as one of two promising prototypes for further optimization; latest generations have crossed important performance thresholds

Source:

identified as one of two promising prototypes for further optimization

Source:

latest generations have crossed important performance thresholds

Compared with FRET

The abstract directly contrasts FRET-based sensors with single-fluorophore sensors of the GCaMP family.

Shared frame: source-stated alternative in extracted literature

Strengths here: identified as one of two promising prototypes for further optimization; latest generations have crossed important performance thresholds.

Relative tradeoffs: remaining issues in sensor function still apply at the class level.

Source:

The abstract directly contrasts FRET-based sensors with single-fluorophore sensors of the GCaMP family.

Compared with GCaMP

The abstract directly contrasts FRET-based sensors with single-fluorophore sensors of the GCaMP family.

Shared frame: source-stated alternative in extracted literature

Strengths here: identified as one of two promising prototypes for further optimization; latest generations have crossed important performance thresholds.

Relative tradeoffs: remaining issues in sensor function still apply at the class level.

Source:

The abstract directly contrasts FRET-based sensors with single-fluorophore sensors of the GCaMP family.

Compared with GCaMP calcium imaging

The abstract directly contrasts FRET-based sensors with single-fluorophore sensors of the GCaMP family.

Shared frame: source-stated alternative in extracted literature

Strengths here: identified as one of two promising prototypes for further optimization; latest generations have crossed important performance thresholds.

Relative tradeoffs: remaining issues in sensor function still apply at the class level.

Source:

The abstract directly contrasts FRET-based sensors with single-fluorophore sensors of the GCaMP family.

The abstract directly contrasts FRET-based sensors with single-fluorophore sensors of the GCaMP family.

Shared frame: source-stated alternative in extracted literature

Strengths here: identified as one of two promising prototypes for further optimization; latest generations have crossed important performance thresholds.

Relative tradeoffs: remaining issues in sensor function still apply at the class level.

Source:

The abstract directly contrasts FRET-based sensors with single-fluorophore sensors of the GCaMP family.

Ranked Citations

  1. 1.
    StructuralSource 1Frontiers in Molecular Neuroscience2014Claim 1Claim 2

    Seeded from load plan for claim cl2. Extracted from this source document.