Biosensor-based dual-color droplet microfluidic platform for precise high-throughput screening of erythromycin hyperproducers
1. Introduction
The growing demand for natural products in pharmaceuticals, agriculture, and biotechnology has prompted advancements in microbial cell factory engineering. Among the innovative approaches, biosensor-based droplet microfluidic high-throughput screening has emerged as a powerful technique for detecting and selecting high-yield microbial strains. This method leverages genetically encoded biosensors to produce measurable outputs in response to specific metabolite concentrations, enabling rapid identification of desirable phenotypes from large mutant libraries. However, inherent biological variability among microbial cells poses challenges to the reliability and accuracy of this technique, necessitating refined strategies to enhance screening fidelity.
2. Limitations of Traditional Whole-Cell Biosensors in Droplet Microfluidics
Conventional single-color whole-cell biosensors, while effective under controlled conditions, often fail to maintain accuracy within microfluidic droplets. Environmental fluctuations significantly influence bacterial growth and gene expression, leading to heterogeneous cell populations within each droplet. This variability introduces inconsistencies in biosensor output signals, making it difficult to distinguish true positive signals from background noise. Moreover, the inability to measure or control cell density within individual droplets further exacerbates false-positive rates, creating a substantial burden for downstream validation processes.
3. Engineering Dual-Color Biosensors for Normalized Signal Output
To address the challenge of heterogeneity, this study introduced a novel dual-color biosensor design in Escherichia coli. By integrating a second reporter signal that reflects cell growth or viability, the system provides normalized outputs by comparing the product-indicative fluorescence to a constitutive reference. This internal control corrects for variances in cell density and gene expression, resulting in more accurate and robust detection of desired phenotypes. The dual-color format represents a significant step forward in biosensor design for high-throughput screening applications.
4. Integration with Droplet-Based Microfluidic Platforms
The enhanced dual-color biosensors were successfully implemented in a droplet-based microfluidic screening platform, enabling simultaneous analysis of thousands of individual microbial variants. This integration allowed for high-throughput, parallelized screening with improved signal consistency and droplet uniformity. In proof-of-concept experiments, the dual-color system exhibited a markedly higher enrichment ratio compared to its single-color counterpart, underscoring the effectiveness of this strategy in minimizing heterogeneity-induced noise and improving screening outcomes.
5. Application in Erythromycin-Producing Strain Improvement
To validate the practical benefits of the dual-color approach, the system was employed in screening both wild-type and mutagenized Saccharopolyspora erythraea strains for enhanced erythromycin production. Results showed a 24.2% increase in positive identification rates for the wild-type strain and an 11.9% increase for industrial S0-derived libraries using the dual-color method. Notably, strains exhibiting up to a 19.6% improvement in erythromycin yield were successfully isolated, demonstrating the method's potential for industrial strain development and optimization.
6. A Universal Strategy for Next-Generation Biosensor Applications
The dual-color whole-cell biosensor platform provides a universal framework for improving the accuracy and throughput of microbial screening campaigns. By accounting for biological variability within droplets, this system reduces false positives and minimizes the time and resources required for post-screening verification. Its compatibility with diverse natural product biosynthesis pathways makes it a versatile tool for synthetic biology, metabolic engineering, and bioprocess development. This work lays the foundation for the next generation of biosensor-driven high-throughput screening technologies.
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