Abstract
Understanding the metabolic interactions between bacteria in natural habitat at the single-cell level and the contribution of individual cell to their functions is essential for exploring the dark matter of uncultured bacteria. The combination of Raman-activated cell sorting (RACS) and single-cell Raman spectra (SCRS) with unique fingerprint characteristics makes it possible for research in the field of microbiology to enter the single cell era. This review presents an overview of current knowledge about the research progress of recognition and assessment of single bacterium cell based on RACS and further research perspectives. We first systematically summarize the label-free and non-destructive RACS strategies based on microfluidics, microdroplets, optical tweezers, and specially made substrates. The importance of RACS platforms in linking target cell genotype and phenotype is highlighted and the approaches mentioned in this paper for distinguishing single-cell phenotype include surface-enhanced Raman scattering (SERS), biomarkers, stable isotope probing (SIP), and machine learning. Finally, the prospects and challenges of RACS in exploring the world of unknown microorganisms are discussed.
Key points
• Analysis of single bacteria is essential for further understanding of the microbiological world.
• Raman-activated cell sorting (RACS) systems are significant protocol for characterizing phenotypes and genotypes of individual bacteria.
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This work was kindly supported by the Fundamental Research Funds for National Key R&D Program of China (2018YFC1602500), National Key R&D Program of China (2018YFC1602900), and Science and Technology innovation Plan of Shanghai (19391902000).
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LQ conceived the manuscript topics. Y-SS designed the structure of the mini-review. Y-SS, Q-JX, and GL wrote the manuscript. L-DZ and X-DP assisted in collecting and analyzing data. All authors read and approved the manuscript.
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Yan, S., Qiu, J., Guo, L. et al. Development overview of Raman-activated cell sorting devoted to bacterial detection at single-cell level. Appl Microbiol Biotechnol 105, 1315–1331 (2021). https://doi.org/10.1007/s00253-020-11081-1
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DOI: https://doi.org/10.1007/s00253-020-11081-1