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Updated: Jul 16, 2026

Techniques for the Evolution of Robust Pentose-fermenting Yeast for Bioconversion of Lignocellulose to Ethanol
Published on: October 24, 2016
Metabolism-driven and high-efficiency mining of ethanol-tolerant microorganisms from pit mud microbiota using
Teng Xu1, Qing Sun2, Gongchao Jing3
1Single-Cell Center, Key Laboratory of Photoelectric Conversion and Utilization of Solar Energy, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China; University of Jinan, Jinan, Shandong, China.
None:
Mining stress-tolerant microorganisms from complex microbiomes is pivotal for the development of robust microbial chassis. However, conventional culture-first methods were laborious, low throughput, and inefficient for high-performance cells. Here, we developed and applied a high-throughput microfluidic optical tweezers-based Raman-activated cell sorting (RACS) system coupled with deuterium oxide (D2O)-labelled single-cell Raman spectroscopy (SCRS). Leveraging a high screening throughput of ∼ 2,400 cells/h and a sorting accuracy of 91.3%, we successfully and efficiently enriched highly ethanol-tolerant cells from pit mud microbiomes. In a single sorting run, the system enriched 177 highly metabolic-active cells under ethanol stress before cultivation. Targeted cultivation on MRS medium yielded 6 isolates, all showing strong tolerance to 8% (v/v) ethanol in a 7 h SCRS-based assessment, whereas conventional culture-first screening achieved only 2 out 9 (22.2%) success. Genome sequencing and strain-specific transcriptomic profiling further provided molecular support for the ethanol-tolerant phenotypes of Lactiplantibacillus plantarum F4 (Raman Tolerance Index = 85.1 ± 3.41%) and Staphylococcus epidermidis F5 (RTI = 62.2 ± 1.09%). These molecular responses support the physiological relevance of the Raman screening signal. Overall, this integrated workflow achieved a 4.5-fold improvement in enrichment, and a 6.86-fold increase in assessment efficiency compared with conventional methods. Therefore, by sorting target cells based on metabolic activity in a screen-before-culture manner, D2O-RACS is a powerful and versatile platform for efficient mining of stress-tolerant cells.
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