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Environmental microbial bioprospecting enabled by a Raman fingerprinting and functional sorting on a microfluidic
Guoxia Zheng1, Yanwen Liu2, Huicheng Chen3
1Environmental and Chemical Engineering Institute, Dalian University, Dalian, 116622, China; Liaoning Provincial Key Laboratory of Biophysics, Dalian, 116622, China.
Analytica Chimica Acta
|March 15, 2026
Summary
We developed MicroSD-RFFS, a novel platform for microbial bioprospecting. This system enables high-throughput, high-resolution single-cell analysis and functional sorting, overcoming limitations of current technologies for efficient microbial discovery.
Area of Science:
- Microbiology
- Biotechnology
- Analytical Chemistry
Background:
- Current single-cell analysis technologies face trade-offs in throughput, resolution, and cell viability, hindering function-driven microbial bioprospecting.
- Developing advanced platforms is crucial for overcoming these limitations and enabling efficient microbial discovery.
Purpose of the Study:
- To develop and validate MicroSD-RFFS, a novel platform integrating microfluidic static droplet arrays, Raman spectral fingerprinting, and functional sorting.
- To overcome throughput, resolution, and cell viability limitations in single-cell microbial analysis.
- To enable efficient function-driven microbial discovery from complex environments.
Main Methods:
- MicroSD-RFFS platform combines blade-assisted droplet generation for high-throughput encapsulation, static droplet arrays on aluminum foil chips for high-resolution spectral acquisition, and substrate-induced replica plating for culture-compatible sorting.
- A dual-biomarker strategy using D2O-tolerant C-D band ratio (CDRcal) for functional activity and Raman fingerprinting for strain identification was employed.
- An optimized dimensionality reduction method (SVD-based) and discriminant models were integrated for efficient data analysis and discrimination.
Main Results:
- The platform achieved high-throughput encapsulation (720 droplets/chip in 3s) and high-resolution spectral acquisition (5s/cell at 5mW).
- Six phosphorus-solubilizing bacteria (PSB) strains were efficiently isolated and identified from complex soil communities with high discrimination probability (min. 0.979) and low reconstruction error (10^-26 to 10^-28).
- Functional traits were accurately ranked using CDRcal, consistent with conventional assays and outperforming traditional multivariate analysis.
Conclusions:
- MicroSD-RFFS provides an efficient, robust, and cost-effective platform for function-driven microbial discovery at the single-cell level.
- The integrated approach overcomes key limitations of existing single-cell analysis technologies.
- This platform facilitates the isolation and identification of functional microbes from complex environmental samples.
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