SRS-FISH: a high-throughput platform linking microbiome metabolism to identity at the single-cell level
SRS-FISH: a high-throughput platform linking microbiome metabolism to identity at the single-cell level
One of the biggest challenges in microbiome research in environmental and medical samples is to better understand functional properties of microbial community members at a single-cell level. Single-cell isotope probing has become a key tool for this purpose, but the current detection methods for determination of isotope incorporation into single cells do not allow high-throughput analyses. Here, we report on the development of an imaging-based approach termed stimulated Raman scattering-two-photon fluorescence in situ hybridization (SRS-FISH) for high-throughput metabolism and identity analyses of microbial communities with single-cell resolution. SRS-FISH offers an imaging speed of 10 to 100 ms per cell, which is two to three orders of magnitude faster than achievable by state-of-the-art methods. Using this technique, we delineated metabolic responses of 30,000 individual cells to various mucosal sugars in the human gut microbiome via incorporation of deuterium from heavy water as an activity marker. Application of SRS-FISH to investigate the utilization of host-derived nutrients by two major human gut microbiome taxa revealed that response to mucosal sugars tends to be dominated by Bacteroidales, with an unexpected finding that Clostridia can outperform Bacteroidales at foraging fucose. With high sensitivity and speed, SRS-FISH will enable researchers to probe the fine-scale temporal, spatial, and individual activity patterns of microbial cells in complex communities with unprecedented detail.
chemical imaging, microbiome heterogeneity, mucus degradation, multimodal microscopy, single-cell microbiology
e2203519119
Ge, Xiaowei
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Pereira, Fátima C
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Mitteregger, Matthias
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Berry, David
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Zhang, Meng
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Hausmann, Bela
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Zhang, Jing
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Schintlmeister, Arno
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Wagner, Michael
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Cheng, Ji-Xin
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28 June 2022
Ge, Xiaowei
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Pereira, Fátima C
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Mitteregger, Matthias
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Berry, David
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Zhang, Meng
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Hausmann, Bela
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Zhang, Jing
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Schintlmeister, Arno
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Wagner, Michael
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Cheng, Ji-Xin
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Ge, Xiaowei, Pereira, Fátima C, Mitteregger, Matthias, Berry, David, Zhang, Meng, Hausmann, Bela, Zhang, Jing, Schintlmeister, Arno, Wagner, Michael and Cheng, Ji-Xin
(2022)
SRS-FISH: a high-throughput platform linking microbiome metabolism to identity at the single-cell level.
Proceedings of the National Academy of Sciences of the United States of America, 119 (26), .
(doi:10.1073/pnas.2203519119).
Abstract
One of the biggest challenges in microbiome research in environmental and medical samples is to better understand functional properties of microbial community members at a single-cell level. Single-cell isotope probing has become a key tool for this purpose, but the current detection methods for determination of isotope incorporation into single cells do not allow high-throughput analyses. Here, we report on the development of an imaging-based approach termed stimulated Raman scattering-two-photon fluorescence in situ hybridization (SRS-FISH) for high-throughput metabolism and identity analyses of microbial communities with single-cell resolution. SRS-FISH offers an imaging speed of 10 to 100 ms per cell, which is two to three orders of magnitude faster than achievable by state-of-the-art methods. Using this technique, we delineated metabolic responses of 30,000 individual cells to various mucosal sugars in the human gut microbiome via incorporation of deuterium from heavy water as an activity marker. Application of SRS-FISH to investigate the utilization of host-derived nutrients by two major human gut microbiome taxa revealed that response to mucosal sugars tends to be dominated by Bacteroidales, with an unexpected finding that Clostridia can outperform Bacteroidales at foraging fucose. With high sensitivity and speed, SRS-FISH will enable researchers to probe the fine-scale temporal, spatial, and individual activity patterns of microbial cells in complex communities with unprecedented detail.
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pnas.2203519119
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Accepted/In Press date: 8 April 2022
Published date: 28 June 2022
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Funding Information:
ACKNOWLEDGMENTS. Research reported in this publication was funded by NIH Awards R35GM136223 (to J.-X.C.) and R01AI141439 (to J.-X.C.) and supported by the Boston University Micro and Nano Imaging Facility and Office of the Director, NIH Award S10OD024993. Funding for the presented research was also provided via Young Independent Research Group Grant ZK-57 (to F.C.P.) and by Austrian Science Fund Wittgensteinaward Z383-B (to M.W.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. We thank Jasmin Schwarz, Gudrun Kohl, and Petra Pjevac from the Joint Microbiome Facility of the Medical University of Vienna and the University of Vienna for assisting with amplicon sequencing.
Funding Information:
Research reported in this publication was funded by NIH Awards R35GM136223 (to J.-X.C.) and R01AI141439 (to J.-X.C.) and supported by the Boston University Micro and Nano Imaging Facility and Office of the Director, NIH Award S10OD024993. Funding for the presented research was also provided via Young Independent Research Group Grant ZK-57 (to F.C.P.) and by Austrian Science Fund Wittgensteinaward Z383-B (to M.W.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. We thank Jasmin Schwarz, Gudrun Kohl, and Petra Pjevac from the Joint Microbiome Facility of the Medical University of Vienna and the University of Vienna for assisting with amplicon sequencing.
Publisher Copyright:
Copyright © 2022 the Author(s)
Keywords:
chemical imaging, microbiome heterogeneity, mucus degradation, multimodal microscopy, single-cell microbiology
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Local EPrints ID: 469392
URI: http://eprints.soton.ac.uk/id/eprint/469392
ISSN: 0027-8424
PURE UUID: 8a6616d9-913e-4936-9a5d-2082ef246108
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Date deposited: 14 Sep 2022 16:41
Last modified: 17 Mar 2024 04:14
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Contributors
Author:
Xiaowei Ge
Author:
Fátima C Pereira
Author:
Matthias Mitteregger
Author:
David Berry
Author:
Meng Zhang
Author:
Bela Hausmann
Author:
Jing Zhang
Author:
Arno Schintlmeister
Author:
Michael Wagner
Author:
Ji-Xin Cheng
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