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Highly multiplexed spatial mapping of microbial communities

Author

Listed:
  • Hao Shi

    (Cornell University)

  • Qiaojuan Shi

    (Cornell University)

  • Benjamin Grodner

    (Cornell University)

  • Joan Sesing Lenz

    (Cornell University)

  • Warren R. Zipfel

    (Cornell University)

  • Ilana Lauren Brito

    (Cornell University)

  • Iwijn De Vlaminck

    (Cornell University)

Abstract

Mapping the complex biogeography of microbial communities in situ with high taxonomic and spatial resolution poses a major challenge because of the high density1 and rich diversity2 of species in environmental microbiomes and the limitations of optical imaging technology3–6. Here we introduce high-phylogenetic-resolution microbiome mapping by fluorescence in situ hybridization (HiPR-FISH), a versatile technology that uses binary encoding, spectral imaging and decoding based on machine learning to create micrometre-scale maps of the locations and identities of hundreds of microbial species in complex communities. We show that 10-bit HiPR-FISH can distinguish between 1,023 isolates of Escherichia coli, each fluorescently labelled with a unique binary barcode. HiPR-FISH, in conjunction with custom algorithms for automated probe design and analysis of single-cell images, reveals the disruption of spatial networks in the mouse gut microbiome in response to treatment with antibiotics, and the longitudinal stability of spatial architectures in the human oral plaque microbiome. Combined with super-resolution imaging, HiPR-FISH shows the diverse strategies of ribosome organization that are exhibited by taxa in the human oral microbiome. HiPR-FISH provides a framework for analysing the spatial ecology of environmental microbial communities at single-cell resolution.

Suggested Citation

  • Hao Shi & Qiaojuan Shi & Benjamin Grodner & Joan Sesing Lenz & Warren R. Zipfel & Ilana Lauren Brito & Iwijn De Vlaminck, 2020. "Highly multiplexed spatial mapping of microbial communities," Nature, Nature, vol. 588(7839), pages 676-681, December.
  • Handle: RePEc:nat:nature:v:588:y:2020:i:7839:d:10.1038_s41586-020-2983-4
    DOI: 10.1038/s41586-020-2983-4
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    Citations

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    Cited by:

    1. Xiaofan Jin & Feiqiao B. Yu & Jia Yan & Allison M. Weakley & Veronika Dubinkina & Xiandong Meng & Katherine S. Pollard, 2023. "Culturing of a complex gut microbial community in mucin-hydrogel carriers reveals strain- and gene-associated spatial organization," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    2. Zhaohui Cao & Wenlong Zuo & Lanxiang Wang & Junyu Chen & Zepeng Qu & Fan Jin & Lei Dai, 2023. "Spatial profiling of microbial communities by sequential FISH with error-robust encoding," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    3. Jan Kretschmer & Tomáš David & Martin Dračínský & Ondřej Socha & Daniel Jirak & Martin Vít & Radek Jurok & Martin Kuchař & Ivana Císařová & Miloslav Polasek, 2022. "Paramagnetic encoding of molecules," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    4. Junyoung Seo & Yeonbo Sim & Jeewon Kim & Hyunwoo Kim & In Cho & Hoyeon Nam & Young-Gyu Yoon & Jae-Byum Chang, 2022. "PICASSO allows ultra-multiplexed fluorescence imaging of spatially overlapping proteins without reference spectra measurements," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    5. Tomáš David & Miroslava Šedinová & Aneta Myšková & Jaroslav Kuneš & Lenka Maletínská & Radek Pohl & Martin Dračínský & Helena Mertlíková-Kaiserová & Karel Čížek & Blanka Klepetářová & Miroslava Liteck, 2024. "Ultra-inert lanthanide chelates as mass tags for multiplexed bioanalysis," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

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