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Biosensor Parts & Microbial Database Integration Platform. Explore, select, and compare genetically encoded biosensors.

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Sensor Selection Guide

Answer a few questions to find the best sensor for your experiment

Find Your Sensor

Our guided quiz helps you navigate 87 sensors across 17 analytes and 8 sensor types.

Sensor Database

Fluorescent proteins, biosensors, and biological parts

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How to Use Biosensors

A practical guide for getting started with genetically encoded biosensors

A genetically encoded biosensor is a molecular tool designed to detect and measure biological molecules (e.g., ions, metabolites) or environmental conditions within living cells. These biosensors are encoded by synthetic genes that can be introduced into cells through genetic engineering.

Key Features
  • Specificity: Designed to bind or interact with a particular target molecule (Ca2+, glucose, neurotransmitters) or respond to conditions (pH, oxidative stress)
  • Reporting Mechanism: Generate detectable signals (fluorescence/luminescence) upon binding to their target
  • Non-invasive: Continuous, real-time monitoring in natural cellular context without external probes
Applications
  • Cell signaling pathway studies
  • Metabolic activity monitoring
  • Drug discovery and screening
  • Neuroscience research
  • Environmental biosensing

Fluorescence-Based Biosensor Components

Fluorescence-based genetically encoded biosensors convert the detection of specific targets (ions, metabolites, or protein interactions) into measurable fluorescence changes.

Fluorescent Proteins

Core component that emits light when excited. Common variants include:

  • GFP variants: EGFP, cpGFP, LSSmGFP
  • Blue/Cyan: CFP, cpCerulean3, cpT-Sapphire
  • Yellow/Orange: YFP, LSSmApple, LSSmOrange
  • Red: mCherry, LSSmKate2
Sensing Domain (SBP)

Specifically binds the target molecule, undergoing conformational change. Examples:

  • Calcium: Calmodulin (used in GCaMP sensors)
  • Sucrose: ThuE receptor
  • Iron: DtxR binding protein
  • NADH/NAD+: Rex domain
Fluorescence Modulation Mechanisms
  • FRET: Donor and acceptor FPs - energy transfer efficiency changes with distance/orientation
  • cpFP: Circularly permuted FP - fluorescence intensity changes due to structural alterations
  • Single FP: Direct intensity, lifetime, or spectral changes upon target binding
Linker Regions

Flexible peptide sequences connecting FPs and sensing domains. Critical for:

  • Proper conformational changes
  • Effective fluorescence modulation
  • Sensor functionality and dynamic range
Design Considerations
Property Importance
Brightness Bright FPs improve signal-to-noise ratio
Photostability Resists photobleaching during time-lapse imaging
Dynamic Range Significant change upon target detection
Response Time Must capture biological process dynamics
Biocompatibility Should not interfere with cellular functions

Guidelines for Biosensor Application in Your System

Follow these steps to successfully apply biosensors to your research system. Remember: Know your system! This is the first key to success.

1
Register & Use MibiSense

Explore the MibiSense database to find information about available biosensors. The database provides plasmids, strains, KD values, and literature references but NOT about your specific system - you need to adapt the sensor to your organism.

2
Define Your Target & System

Identify what you want to measure (sucrose, ATP, Fe2+, calcium, etc.) and clarify:

  • What is your target system/organism?
  • Is there an expression system available?
  • What is known about protein production in your host (rare codons, etc.)?
3
Check the Literature

Research what is known about your target metabolite and relate it to your system:

  • KD values, concentration levels, stability
  • What is known about your biological system?
  • What do you want to know and why is it important?
  • How can biosensors help answer your question?
4
Check for Substrate Binding Proteins

Identify potential sensing domains for your target:

  • Molecular Recognition Element: Should ideally be monomeric, up to 100 kDa
  • Structurally characterized (X-ray, cryo-EM, AlphaFold)
  • Biochemically analyzed
  • Are there pre-existing biosensors or detection methods?
5
Collect & Sort All Information

Gather data on:

  • Targeted metabolite (KD, levels, stability, physiological role)
  • Substrate binding protein (structure & properties)
  • Background (pre-existing sensors or detection methods)
  • Expression requirements
  • Host properties (autofluorescence, growth conditions, etc.)
6
Approach MibiNet Z01 for Biosensor Creation

If no suitable sensor exists, collaborate with Project Z01:

  • Initial screens for expression of sensory cassettes in YOUR system
  • Biosensor creation pipeline and characterization (in vitro) in parallel
  • Distribution of the finalized biosensor
7
Apply the Biosensor

When you receive your biosensor:

  • Check fluorescence properties (FRET or Matryoshka) → Spectra
  • Determine what you want to observe
  • Test systemic properties (autofluorescence of media)
  • Perform in vitro titration and in vivo imaging of targeted metabolite
  • Receive assistance with data analysis and experiment refinement
Take Home Message: Individual requirements need to be identified together. MibiNet Z01 provides recommendation, creation, and assistance. The first key to success is knowing your system!

Design Principle Readout Advantages Count in DB
Matryoshka cpFP reporter + large Stokes-shift reference FP nested inside Ratiometric (reporter/reference) Built-in normalization, robust quantification -
FLIP (FRET) Donor and acceptor FPs flanking a binding domain FRET ratio change Well-established, good dynamic range -
Single cpFP Circularly permuted FP with inserted sensing domain Intensity change Simple design, bright signal -
FRET Direct FRET between two FPs FRET ratio Ratiometric, distance-sensitive -
Semi-synthetic FRET Protein-based FRET with synthetic fluorophore component FRET ratio Extended spectral range -

Host Organism Considerations

Before choosing a biosensor, thoroughly evaluate your target system:

Bacterial Systems
  • E. coli BL21(DE3): Most common for protein expression
  • E. coli K-12: General laboratory strain
  • Corynebacterium: Industrial production host
  • Check for autofluorescence in growth media
Genetic Compatibility
  • Codon usage: Verify rare codons match host
  • Promoter availability: T7, pBAD, native promoters
  • Plasmid origin: pUC, pBR322 compatibility
  • Selection markers: Antibiotic resistance
Expression Optimization
  • Temperature: 18-37°C for folding
  • Induction timing: OD600 ~0.6-0.8
  • Inducer concentration: IPTG (0.1-1 mM)
  • Expression time: 2-24 hours
Expression Requirements Checklist
  • Vector compatibility: Is the plasmid compatible with your host strain?
  • Promoter strength: Match promoter to desired expression level
  • Codon optimization: Rare codons may require special strains (e.g., Rosetta)
  • Protein folding: Lower temperatures often improve folding for complex sensors
  • Maturation time: Allow sufficient time for chromophore maturation (typically 1-4 hours)
Tip: Many biosensors in MibiSense are initially characterized in E. coli BL21(DE3). If your target organism is different, contact MibiNet Project Z01 for assistance with adaptation.

Imaging Techniques for Biosensors
Widefield Fluorescence

Fast, simple imaging suitable for routine monitoring. Best for detecting bulk fluorescence changes in cell populations.

  • Speed: High frame rates possible
  • Resolution: ~250 nm lateral
  • Best for: Population studies, plate assays
Confocal Microscopy

Provides optical sectioning to eliminate out-of-focus light. Essential for detailed cellular and subcellular imaging.

  • Speed: Moderate
  • Resolution: ~150 nm lateral
  • Best for: Subcellular localization, 3D imaging
FLIM (Fluorescence Lifetime)

Measures fluorescence decay time rather than intensity. Enables multiplexing with sensors having similar spectra but different lifetimes.

  • Speed: Slower, but improving
  • Advantage: Intensity-independent, environment-insensitive
  • Best for: Multiplexing, quantitative measurements
Plate Reader Assays

High-throughput measurement of fluorescence in multi-well plates. Ideal for screening and dose-response curves.

  • Throughput: 96, 384, or 1536 wells
  • Best for: KD determination, screening
Common Filter Sets for Biosensors
Sensor Type Fluorophore Excitation (nm) Emission (nm) Filter Set
Reporter (Matryoshka) cpGFP 488 505-520 Standard GFP
Reference (Matryoshka) LSSmOrange/LSSmApple 560-590 610-630 Texas Red
FRET Donor CFP 430-450 470-490 CFP/YFP
FRET Acceptor YFP 514 525-550 YFP
Important: Check your microscope's filter sets against the sensor's spectral properties before imaging. Improper filter sets can lead to crosstalk and inaccurate measurements.

Quantitative Analysis Methods
Ratiometric Analysis

For Matryoshka and FRET sensors, calculate the ratio between two emission channels:

Ratio = Reporter / Reference
  • Advantage: Normalizes for expression level and optical variations
  • Required for: Matryoshka sensors, FRET sensors
Dose-Response Curves

Fit sensor response to determine KD and dynamic range:

Response = Rmin + (Rmax - Rmin) × [L] / (KD + [L])
  • KD: Concentration at half-maximal response
  • Dynamic range: (Rmax - Rmin) / Rmin
Data Processing Steps
  1. Background subtraction: Subtract autofluorescence from media and cells
  2. Flat-field correction: Correct for illumination unevenness (if needed)
  3. ROI selection: Define regions of interest for analysis
  4. Ratio calculation: Compute reporter/reference ratios
  5. Normalization: Normalize to baseline or control conditions
  6. Statistical analysis: Apply appropriate statistical tests
Common Software Tools
  • ImageJ/Fiji: Free, widely used for image analysis
  • CellProfiler: Automated image analysis pipelines
  • Python: scikit-image, NumPy, pandas
  • GraphPad Prism: Curve fitting and statistics
  • Origin: Advanced data analysis
  • FLIMfit: Lifetime analysis software
  • OMERO: Image data management and sharing
Tip: Always include negative controls (cells without sensor) and positive controls (cells with known responding sensor) in your experiments.

Common Problems and Solutions

Possible Causes:
  • Low expression levels
  • Incorrect induction conditions
  • Poor chromophore maturation
  • Wrong filter sets
  • Protein not folding properly / inclusion body formation
Solutions:
  • Try lower temperature (18-25°C) for better folding
  • Increase induction time (up to 24 hours)
  • Verify plasmid sequence and transformation
  • Check microscope settings and filter sets
  • Use a positive control (e.g., standalone GFP)
  • Check for inclusion bodies - solubility issues indicate folding problems; consider fusion tags or chaperone co-expression

Possible Causes:
  • Media autofluorescence
  • Cellular autofluorescence
  • Improper background subtraction
  • Crosstalk between channels
Solutions:
  • Use minimal media when possible
  • Always include negative control (cells without sensor)
  • Properly subtract background from each image
  • Check for spectral bleed-through in FRET experiments
  • Consider using FLIM to avoid intensity-based issues

Possible Causes:
  • Sensor not functional in host organism
  • Target analyte not present in accessible form
  • pH or redox conditions affecting sensor
  • KD outside physiological range
Solutions:
  • Test sensor in original host organism as control
  • Verify analyte is reaching the cells
  • Check intracellular pH conditions
  • Perform in vitro titration to confirm functionality
  • Contact MibiNet Z01 for sensor optimization assistance

Solutions:
  • Reduce expression temperature (18-25°C)
  • Lower inducer concentration
  • Use chaperone co-expression strains
  • Test different promoters with weaker expression
  • Consider solubility tags (MBP, SUMO)

Solutions:
  • Reduce laser/illumination intensity
  • Use anti-fade mounting media (for fixed samples)
  • Limit exposure time
  • Use more photostable fluorescent proteins
  • Consider acquiring time-lapse images at lower frequency

Explore all resources: Visit our comprehensive Resources tab for database browsers, external database cards, and advanced search tools.
External Databases & Resources
FPbase

Comprehensive database of fluorescent proteins with spectral data, references, and sequence information.

BiosensorDB (UCSD)

Database of genetically encoded biosensors with characterization data and references.

RCSB PDB

Protein Data Bank - archive of 3D structural data for proteins and nucleic acids.

Imaging & Analysis Software
Community Support

3D Protein Structures

Interactive 3D visualization of fluorescent protein structures from PDB.

Select Protein

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About

This viewer displays 3D structures from the RCSB PDB using MolStar. 179 proteins have known 3D structures.

Structure Viewer

Select a protein to view its 3D structure

Fluorophore Testbase

20 fluorescent proteins available for biosensor construction and testing.

About Fluorescent Proteins

The fluorophore testbase contains a collection of fluorescent proteins (FPs) used in biosensor construction. These FPs serve as reporters, references, or FRET partners in genetically encoded biosensors.

Reporter FPs Change fluorescence upon sensing
Reference FPs Constant emission for ratiometric sensing
FRET Pairs Donor-acceptor combinations

Available Fluorophores

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Statistics & Analytics

Database analytics, visualization, and community dynamics data.

87
MibiSens Sensors
1,040
Fluorescent Proteins
453
Biosensors (UCSD)
179
3D Structures

Biosensor Analytics

Statistical analysis and trends from 453 fluorescent biosensors

Fluorescent Protein Analysis

Spectral properties and database statistics from 1,040 proteins

Sample Species Interactions

Sample microbial community interaction data from in silico models.

Species A Species B Interaction Type Mechanism Strength

Unified Database Search

Search across all open-access biosensor and synthetic biology databases.

Cross-Database Search
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About External Databases
Individual Database Browsers

Browse fluorescent proteins from FPbase. Click any entry to view on FPbase.

Open FPbase

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Browse biosensors from UCSD. Click any entry to view full details.

Open BiosensorDB

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Browse biological parts from multiple repositories.

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