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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 det...

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Autores principales: Ge, Xiaowei, Pereira, Fátima C., Mitteregger, Matthias, Berry, David, Zhang, Meng, Hausmann, Bela, Zhang, Jing, Schintlmeister, Arno, Wagner, Michael, Cheng, Ji-Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9245642/
https://www.ncbi.nlm.nih.gov/pubmed/35727976
http://dx.doi.org/10.1073/pnas.2203519119
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author Ge, Xiaowei
Pereira, Fátima C.
Mitteregger, Matthias
Berry, David
Zhang, Meng
Hausmann, Bela
Zhang, Jing
Schintlmeister, Arno
Wagner, Michael
Cheng, Ji-Xin
author_facet Ge, Xiaowei
Pereira, Fátima C.
Mitteregger, Matthias
Berry, David
Zhang, Meng
Hausmann, Bela
Zhang, Jing
Schintlmeister, Arno
Wagner, Michael
Cheng, Ji-Xin
author_sort Ge, Xiaowei
collection PubMed
description 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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spelling pubmed-92456422022-07-01 SRS-FISH: A high-throughput platform linking microbiome metabolism to identity at the single-cell level Ge, Xiaowei Pereira, Fátima C. Mitteregger, Matthias Berry, David Zhang, Meng Hausmann, Bela Zhang, Jing Schintlmeister, Arno Wagner, Michael Cheng, Ji-Xin Proc Natl Acad Sci U S A Biological Sciences 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. National Academy of Sciences 2022-06-21 2022-06-28 /pmc/articles/PMC9245642/ /pubmed/35727976 http://dx.doi.org/10.1073/pnas.2203519119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Ge, Xiaowei
Pereira, Fátima C.
Mitteregger, Matthias
Berry, David
Zhang, Meng
Hausmann, Bela
Zhang, Jing
Schintlmeister, Arno
Wagner, Michael
Cheng, Ji-Xin
SRS-FISH: A high-throughput platform linking microbiome metabolism to identity at the single-cell level
title SRS-FISH: A high-throughput platform linking microbiome metabolism to identity at the single-cell level
title_full SRS-FISH: A high-throughput platform linking microbiome metabolism to identity at the single-cell level
title_fullStr SRS-FISH: A high-throughput platform linking microbiome metabolism to identity at the single-cell level
title_full_unstemmed SRS-FISH: A high-throughput platform linking microbiome metabolism to identity at the single-cell level
title_short SRS-FISH: A high-throughput platform linking microbiome metabolism to identity at the single-cell level
title_sort srs-fish: a high-throughput platform linking microbiome metabolism to identity at the single-cell level
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9245642/
https://www.ncbi.nlm.nih.gov/pubmed/35727976
http://dx.doi.org/10.1073/pnas.2203519119
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