Raman flow cytometry based single‐cell species classification, viable‐cell counting and vitality test for probiotic products
The rapidly expanding probiotic industry demands efficient methods for quality assessment of probiotic products. We previously established a microscopic imaging and Raman spectroscopy (miRS) based approach for rapid identification and tests for viability and vitality at single-cell resolution via single-cell Raman spectra (SCRS), yet its wider application is limited by the throughput of SCRS acquisition. Here, we employed a Raman flow cytometry (RFC) approach to accomplish this mission, which features a greatly simplified experimental workflow yet with >10-fold higher throughput than miRS. At SCRS acquisition speed of one bacterial cell per second, RFC achieves much higher sampling depth, leading to higher accuracy of species classification than miRS in both reference ramanome database construction and quality assessment of probiotic products. Specifically, based on the fingerprint regions, the accuracy in classifying species and strains is notably improved, both for an isogenic population and for a multi-strain probiotic product. Moreover, for probiotic products with highly biased compositions, the sensitivity of detecting and classifying low-abundance members is order-of-magnitude higher. Furthermore, based on the fingerprint regions plus the C-D band, D<sub>2</sub>O-probed RFC rapidly yields viable-cell counts and quantifies single-cell vitality in a species/strain-resolved fashion yet without the need for fluorescence labeling, underscoring its strength over propidium monoazide (PMA)-based fluorescence flow cytometry. Due to its speed, accuracy, sensitivity, rich information and ease of use, RFC is a powerful platform for quality assessment for probiotics and other live-cell products.
Authors
- Shuhua Tian (ORCID: https://orcid.org/0000-0001-5492-7635)
- Xixian Wang (ORCID: https://orcid.org/0000-0003-4856-6516)
- Zhidian Diao
- Shi Huang (ORCID: https://orcid.org/0000-0003-2674-2830)
- Jia Zhang (ORCID: https://orcid.org/0000-0002-2063-2385)
- Teng Xu (ORCID: https://orcid.org/0000-0002-3682-5309)
- Xiaoyan Jing (ORCID: https://orcid.org/0000-0003-3296-4958)
- Bo Ma (ORCID: https://orcid.org/0000-0002-8501-772X)
- Wei‐Lian Hung (ORCID: https://orcid.org/0000-0002-4223-170X)
- Ziyuan Ding
- Yikun Duan
- Xiaowei Zheng (ORCID: https://orcid.org/0000-0002-8653-7129)
- Pengfei Zhu (ORCID: https://orcid.org/0000-0003-2141-8636)
- Jian Xu (ORCID: https://orcid.org/0000-0002-0548-8477)
- Ting Sun (ORCID: https://orcid.org/0000-0001-8287-0541)
- Jianmei Wang (ORCID: https://orcid.org/0000-0002-1126-0612)
- Xuan Zhou (ORCID: https://orcid.org/0000-0003-4737-3851)
- Xia Ma
Institutions
- Cell Biotech (South Korea) (KR)
- Inner Mongolia Electric Power Survey & Design Institute (China) (CN)
- Shandong Lianxing Energy Group (China) (CN)
- Inner Mongolia Yili Industrial Group (China) (CN)
- Qingdao Institute of Bioenergy and Bioprocess Technology (CN)
- University of Chinese Academy of Sciences (CN)
- Ocean University of China (CN)
- University of Hong Kong (HK)
Publication Details
- Journal
- iMetaOmics.
- Published
- 2025-05-19
- DOI
- https://doi.org/10.1002/imo2.70024
- Citations
- 4
- Primary Topic
- Spectroscopy Techniques in Biomedical and Chemical Research
- Type
- article
- Field-Weighted Citation Impact
- 6.54
Funders
- National Science Foundation
- National Natural Science Foundation of China
- University of Hong Kong