ArticleiMetaOmics2025
Raman flow cytometry based single-cell species classification, viable-cell counting and vitality test for probiotic products.
Article in iMetaOmics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Deep Learning-Enhanced Raman Microspectroscopy Enables Rapid Microbial Classification and Captures Phylogenetic Relationships.Microorganisms · 2026Article
- Ecology-microbiome engineering in Sauce-flavor Baijiu via Single-Cell Raman Spectroscopy.Biodesign research · 2026Review
- Mechanisms and Applications of Gastrointestinal Microbiota-Metabolite Interactions in Ruminants: A Review.Microorganisms · 2025Review
- Apple Juice Fermented withFoods (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.