Scientists have developed a Raman-activated cell sorting strategy for high-throughput discovery of ethanol-tolerant microorganisms based on their metabolic activity rather than growth.

The study, led by the Qingdao Institute of Bioenergy and Bioprocess Technology (QIBEBT), Chinese Academy of Sciences, and the COFCO Nutrition & Health Research Institute, was published in Bioresource Technologyon July 14.

Conventional microbial screening generally follows an “isolate first, test later” workflow, in which cells are cultivated under selective pressure, isolated, and evaluated. This approach is slow, labor-intensive and biased toward fast-growing or abundant microbes. That matters in solid-state baijiu fermentation, where rising ethanol concentrations stress microbial communities, while valuable but low-abundance active microbes are easily overlooked.

The team therefore shifted the criterion from whether a cell could grow under ethanol stress to whether it kept its metabolism active. They combined heavy-water (D₂O) labeling with single-cell Raman spectroscopy and a high-throughput Raman-activated flow cytometer known as FlowRACS. Metabolically active cells incorporate deuterium from D₂O into newly synthesized biomolecules, producing a characteristic carbon-deuterium (C-D) Raman signal. Based on this signal, the team derived a carbon-to-deuterium ratio (CDR) and a Raman Tolerance Index (RTI) to quantify the in-situ ethanol tolerance of individual cells.

The platform functionally sorted 2,400 cells per hour at 91.3% accuracy. From pit mud pretreated with 8% ethanol, one sorting round followed by culture yielded six pure strains, all with RTI above 50%, versus only two among nine isolates from conventional agarose-plate screening. Overall, the strategy boosted strain-mining efficiency by 4.5 fold and phenotypic validation by 7 fold, cutting key steps from days to hours.

Genomic and transcriptomic analyses revealed distinct tolerance mechanisms. Lactiplantibacillus plantarum (RTI = 85.1%) enhanced lactate dehydrogenase expression by 3.4 fold while maintaining high alcohol dehydrogenase activity, reflecting adaptive redox balancing. Staphylococcus epidermidis (RTI = 62.2%) activated lipid-synthesis and glycerol-metabolism genes, pointing to cell-envelope remodeling. Both strains were rare in the original microbial community, showing that function-based sorting recovers key microbes missed by abundance- or growth-based approaches.

“The key is not simply judging whether cells grow under stress, but reading whether they keep their metabolism running”, said Assoc. Prof. ZHANG Jia of QIBEBT, co-corresponding author.

“By making metabolic phenotype the direct sorting criterion, we can obtain higher-performing strains directly from microbiome while shortening the screening-to-validation process”, said Dr. ZHENG Xiaowei of the COFCO Nutrition & Health Research Institute, co-corresponding author.

The approach could also be extended to acid, salt, and solvent tolerance, aiding the building of robust industrial chassis strain libraries. This work is the newest progress in the iMAPS Consortium (in-situ Metabolic Atlas Projects @ Single-cell; www.iMAPS.info).

Ramanome-based “function-first” strategy for high-throughput mining of ethanol-tolerant microbes for the fermentation industry