View in EDS

Environmental microbial bioprospecting enabled by a Raman fingerprinting and functional sorting on a microfluidic static droplet array.

Saved in:
Bibliographic Details
Title: Environmental microbial bioprospecting enabled by a Raman fingerprinting and functional sorting on a microfluidic static droplet array.
Authors: Zheng, Guoxia1,2 (AUTHOR), Liu, Yanwen1 (AUTHOR), Chen, Huicheng3 (AUTHOR), Lu, Ling2,4 (AUTHOR), Wang, Lin1,2 (AUTHOR), Jia, Tingting1 (AUTHOR), Wang, Yunhua1,2,4 (AUTHOR) Wangyunhua@dlu.edu.cn
Source: Analytica Chimica Acta. May2026, Vol. 1400, pN.PAG-N.PAG. 1p.
Subjects: Bioprospecting, Microdroplets, Cell separation, Dimensional reduction algorithms, Soil microbiology, Bacteria, Chemical fingerprinting, Cell analysis
Abstract: Function-driven microbial bioprospecting has been hindered by persistent trade-offs among throughput, resolution, and cell viability in current single-cell analysis technologies. To overcome these limitations, we developed MicroSD-RFFS, a platform that seamlessly integrates a microfluidic static droplet array with Raman spectral fingerprinting and functional sorting. This platform achieves high-throughput single-cell encapsulation via blade-assisted droplet generation (∼3s, 720 droplets per chip), high-resolution spectral acquisition under low-power excitation (532 nm, 5 mW, 5 s per cell) by leveraging static droplet arrays on cost-effective aluminum foil-based chips, and culture-compatible sorting via substrate-induced replica plating. Applied to the screening of phosphorus-solubilizing bacteria (PSB), MicroSD-RFFS employs a dual-biomarker strategy that utilizes the C–D band ratio calibrated for D 2 O tolerance (CDR cal) to assess functional activity, and Raman fingerprinting for strain identification. By integrating an optimized dimensionality reduction method (a permutation-based singular value decomposition (SVD) low-rank approximation algorithm) along with discriminant models, the system efficiently isolated and identified six PSB strains from complex soil communities, achieving near-perfect discrimination probability (minimum Prob. = 0.979) and a reconstruction error on the order of 10−26∼10−28. These results are consistent with omics data and markedly outperform those obtained through conventional multivariate analysis. Their functional traits were accurately ranked based on CDR cal , consistent with conventional phosphorus-solubilizing activity assays. Thus, MicroSD-RFFS provides an efficient and robust platform and method for function-driven microbial discovery at the single-cell level. [Display omitted] • MicroSD-RFFS: Al-foil static-droplet chip and Raman for non-destructive microbial mining at single-cell resolution • CDR cal corrects D 2 O toxicity, ranks PSB activity quantitatively in situ • SVD-PCA-LDA classifies strains at >97% accuracy, reconstruction error ∼10−27 • Replica-plate stamping sorts 720 droplets in seconds, keeps cells alive • Six soil PSB isolated & cultured in 48h; fast, cheap, function-driven bioprospecting [ABSTRACT FROM AUTHOR]
Copyright of Analytica Chimica Acta is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Description
Abstract:Function-driven microbial bioprospecting has been hindered by persistent trade-offs among throughput, resolution, and cell viability in current single-cell analysis technologies. To overcome these limitations, we developed MicroSD-RFFS, a platform that seamlessly integrates a microfluidic static droplet array with Raman spectral fingerprinting and functional sorting. This platform achieves high-throughput single-cell encapsulation via blade-assisted droplet generation (∼3s, 720 droplets per chip), high-resolution spectral acquisition under low-power excitation (532 nm, 5 mW, 5 s per cell) by leveraging static droplet arrays on cost-effective aluminum foil-based chips, and culture-compatible sorting via substrate-induced replica plating. Applied to the screening of phosphorus-solubilizing bacteria (PSB), MicroSD-RFFS employs a dual-biomarker strategy that utilizes the C–D band ratio calibrated for D 2 O tolerance (CDR cal) to assess functional activity, and Raman fingerprinting for strain identification. By integrating an optimized dimensionality reduction method (a permutation-based singular value decomposition (SVD) low-rank approximation algorithm) along with discriminant models, the system efficiently isolated and identified six PSB strains from complex soil communities, achieving near-perfect discrimination probability (minimum Prob. = 0.979) and a reconstruction error on the order of 10−26∼10−28. These results are consistent with omics data and markedly outperform those obtained through conventional multivariate analysis. Their functional traits were accurately ranked based on CDR cal , consistent with conventional phosphorus-solubilizing activity assays. Thus, MicroSD-RFFS provides an efficient and robust platform and method for function-driven microbial discovery at the single-cell level. [Display omitted] • MicroSD-RFFS: Al-foil static-droplet chip and Raman for non-destructive microbial mining at single-cell resolution • CDR cal corrects D 2 O toxicity, ranks PSB activity quantitatively in situ • SVD-PCA-LDA classifies strains at >97% accuracy, reconstruction error ∼10−27 • Replica-plate stamping sorts 720 droplets in seconds, keeps cells alive • Six soil PSB isolated & cultured in 48h; fast, cheap, function-driven bioprospecting [ABSTRACT FROM AUTHOR]
ISSN:00032670
DOI:10.1016/j.aca.2026.345319