Fluorophore-based Genetically Encoded Biosensors for Ratiometric Fluorescence Imaging in Microbes

Summary

This protocol describes the application of fluorophore-based genetically encoded biosensors in microbes for quantitative ratiometric fluorescence imaging under controlled conditions. By integrating these biosensing strategies with advanced imaging techniques, the method enables high-resolution, real-time analysis at the single-cell level, providing deeper insights into small-molecule dynamics.

Abstract

Investigating small-molecule dynamics within microbes is essential for comprehensive studies of microbial function. Both intra-organism and inter-organism small molecule dynamics play critical roles in microbial physiology, symbiosis, and disease. However, monitoring these dynamics remains highly challenging using most existing techniques. Fluorophore-based genetically encoded biosensors are powerful tools for tracking small-molecule dynamics in vivo and hold high potential for driving new discoveries. These biosensors are most commonly used in fluorescence imaging, often in combination with perfusion devices that allow precise control over environmental conditions. When integrated with advanced imaging techniques, this approach provides high-resolution, spatially and temporally resolved data, enabling insights into single-cell microbial responses. Despite their promise, implementing such biosensors remains technically challenging. Understanding the key steps is crucial for broader adoption. Here, we present a protocol designed to support the effective deployment of newly engineered biosensors into microbes for quantitative ratiometric fluorescence imaging under controlled conditions.

Introduction

Single-fluorophore intensity-based and dual-fluorophore biosensors are widely used by researchers for a variety of applications¹. Some studies have employed multiplex biosensor analyses to simultaneously track multiple signals within the same cells². Many of these biosensors rely on ligand-binding domains, where binding events induce conformational changes that alter fluorescence properties^3,4. Genetically encoded biosensors have become essential tools for in vivo imaging across a range of systems⁵, enabling high-resolution monito....

Protocol

1. Rational design of ratiometric biosensors (Figure 1)

NOTE: The binding protein of interest is selected as the sensory domain based on relevant criteria, including (i) specificity, (ii) affinity, (iii) structural information, and (iv) conformation rearrangement upon ligand binding. Specificity ensures that the biosensor selectively responds to the target molecule without cross-reactivity. Affinity is considered to align with the expected concentration range of the target molecule in the biological context. Structural information, derived from experimental data or computational ....

Results

To achieve successful ratiometric imaging of biosensors in microbial systems, several technical challenges must be addressed.

Expression System: The first challenge lies in the selection of the expression system; whether plasmid-based, chromosomally integrated, driven by constitutive or inducible promoters, and with or without subcellular targeting tags. These factors can significantly affect the biosensor's stability, toxicity, and localization within the cells (Figure 1<.......

Discussion

Genetically encoded fluorophore-based biosensors enable the real-time monitoring of intracellular analyte concentrations in living cells¹. These biosensors typically function by converting conformational changes into optical signals, which can be detected either ratiometrically or intensiometrically. Intensiometric biosensors rely on fluorescence intensity changes from a single FP, making them sensitive to variations in biosensor abundance, leading to potential measurement bias. This issue can be .......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Agar	Sigma-Aldrich Co.	A5306-250G
CellASIC ONIX plate for haploid yeast cells	Merck KGaA	Y04C-02-5PK
CellASIC ONIX2	Merck KGaA	CAX2-S0000
CSM-Ura	Thermo Fisher Scientific	11387899
D-glucose	Sigma-Aldrich Co.	G8270-100G
D-Sorbitol	Sigma-Aldrich Co.	S1876-10MG
NaCl	Sigma-Aldrich Co.	S9888-25G
pAG416 GPD GA-MatryoshCaMP6s	NA	7	For expression of the GA-MatryoshCaMP6s in yeast
TCS SP8 STED	Leica	NA
Yeast strain K601/ W303-1A MAT-a	NA	8	ade2-1 ura3-1 his3-11 trp1- 1 leu2-3 leu2-112 can1-100
YNB	BocaScientific	GCM16.0500
α-Mating Factor acetate salt	Sigma-Aldrich Co.	T6901-.5MG