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An automated Raman-based platform for the sorting of live cells by functional properties

A Publisher Correction to this article was published on 12 April 2019

This article has been updated

Abstract

Stable-isotope probing is widely used to study the function of microbial taxa in their natural environment, but sorting of isotopically labelled microbial cells from complex samples for subsequent genomic analysis or cultivation is still in its early infancy. Here, we introduce an optofluidic platform for automated sorting of stable-isotope-probing-labelled microbial cells, combining microfluidics, optical tweezing and Raman microspectroscopy, which yields live cells suitable for subsequent single-cell genomics, mini-metagenomics or cultivation. We describe the design and optimization of this Raman-activated cell-sorting approach, illustrate its operation with four model bacteria (two intestinal, one soil and one marine) and demonstrate its high sorting accuracy (98.3 ± 1.7%), throughput (200–500 cells h−1; 3.3–8.3 cells min−1) and compatibility with cultivation. Application of this sorting approach for the metagenomic characterization of bacteria involved in mucin degradation in the mouse colon revealed a diverse consortium of bacteria, including several members of the underexplored family Muribaculaceae, highlighting both the complexity of this niche and the potential of Raman-activated cell sorting for identifying key players in targeted processes.

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Fig. 1: Design and working principle of the RACS system.
Fig. 2: RACS operation.
Fig. 3: RACS of reference strains, and performance criteria.
Fig. 4: RACS analysis and targeted mini-metagenomics of mucin-degrading bacteria from a mouse colon microbiota.

Code availability

All of the custom codes used in this study can be accessed upon request from the corresponding author. MATLAB GUI (graphical user interface) software for the operation of the RACS platform is provided in Supplementary Files 1 and 2. R code for the calculation in Supplementary Fig. 18 is provided in Supplementary File 3.

Data availability

The data that support the findings of this study are available from the corresponding author upon request. 16S rRNA gene sequence data have been deposited in the NCBI Sequence Read Archive under SRP144990. Metagenomic data have been deposited in the NCBI under SRP144778. MAGs have been deposited as whole-genome shotgun projects at DDBJ/ENA/GenBank under the accessions RYVY00000000–RYWW00000000. All accession numbers with information on the associated samples are provided in Supplementary Table 6.

Change history

  • 12 April 2019

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Acknowledgements

We acknowledge support by a US Department of Energy Joint Genome Institute Emerging Technologies Opportunity grant (DE-AC02-05CH11231 to R.S. and M.W.). M.W. and M.P. were also supported by the European Research Council via the Advanced Grant project NITRICARE 294343. R.S. acknowledges support from a Gordon and Betty Moore Marine Microbial Initiative Investigator Award (no. 3783). F.M. was supported by the Engineering and Physical Sciences Research Council (EP/R035350/1 and EP/S001921/1). F.C.P. and D.B. were supported by the Austrian Science Fund (FWF; P26127-B20) and the European Research Council (Starting Grant: FunKeyGut 741623). F.C.P. was also supported by the European Union’s Horizon 2020 Framework Programme for Research and Innovation (no. 658718). A.J.M. was supported by the Austrian Science Fund (FWF) project Microbial Nitrogen Cycling–From Single Cells to Ecosystems (W1257). We thank R. Weiß and N. Ivleva for collaboration on the surface-enhanced Raman spectroscopy, C. Herbold for bioinformatics assistance and input, and T. Woyke and R. Malmstrom for many helpful discussions.

Author information

Authors and Affiliations

Authors

Contributions

K.S.L. and R.S. created the software for the RACS. K.S.L., D.B. and R.S. performed the numerical calculations. K.S.L., M.P., J.N., V.I.F. and F.M. developed the RACS system and designed and performed the pure culture RACS experiments. K.S.L., F.C.P. and D.B. designed and performed the mouse colon sample experiments. K.S.L., A.J.M. and H.D. designed and performed the marine enrichment sample experiments. M.W. and R.S. supervised the project. All authors wrote the manuscript.

Corresponding author

Correspondence to Roman Stocker.

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The authors declare no competing interests.

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Supplementary information

Supplementary Information

Supplementary Figures 1–19, Supplementary Tables 1–6, legends for Supplementary Movies and legends for Supplementary Files.

Reporting Summary

Supplementary File 1

MATLAB GUI code for the operation of RACS.

Supplementary File 2

MATLAB GUI code for the operation of RACS.

Supplementary File 3

R code for the calculation in Supplementary Figure 18.

Supplementary File 4

CAD diagrams for the microfluidic sorter.

Supplementary Video 1

A numerically simulated (COMSOL Multiphysics) depiction of the vertical flow focusing.

Supplementary Video 2

An experimental validation of the vertical flow focusing effect.

Supplementary Video 3

Flow within the device.

Supplementary Video 4

An overview of the fully automated RACS process.

Supplementary Video 5

Flow carries cells passing through the evaluation region into the collection outlet.

Supplementary Video 6

Continuous single cell optical tweezing and release.

Supplementary Video 7

Continuous single cell optical tweezing and release.

Supplementary Video 8

Magnetic stirrer designed to prevent cell sedimentation and allow for continuous cell injection during the experiment.

Supplementary Video 9

Laser-induced (photophoretic) cell damage by a high-power Raman laser.

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Lee, K.S., Palatinszky, M., Pereira, F.C. et al. An automated Raman-based platform for the sorting of live cells by functional properties. Nat Microbiol 4, 1035–1048 (2019). https://doi.org/10.1038/s41564-019-0394-9

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