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Related Concept Videos

Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

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Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
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Related Experiment Video

Updated: Nov 27, 2025

Multiplex Detection of Bacteria in Complex Clinical and Environmental Samples using Oligonucleotide-coupled Fluorescent Microspheres
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Highly multiplexed spatial mapping of microbial communities.

Hao Shi1, Qiaojuan Shi2, Benjamin Grodner2

  • 1Nancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA. hs673@cornell.edu.

Nature
|December 3, 2020
PubMed
Summary
This summary is machine-generated.

High-phylogenetic-resolution microbiome mapping by fluorescence in situ hybridization (HiPR-FISH) creates detailed maps of microbial communities. This technology reveals spatial network disruptions in the gut microbiome and stability in oral plaque.

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Area of Science:

  • Microbiology
  • Bioimaging
  • Bioinformatics

Background:

  • Mapping microbial communities in situ at high taxonomic and spatial resolution is challenging due to high species density and diversity.
  • Limitations in current optical imaging technology hinder detailed analysis of microbial community structures.

Purpose of the Study:

  • To introduce a versatile technology for high-phylogenetic-resolution microbiome mapping.
  • To enable micrometre-scale mapping of microbial locations and identities in complex communities.

Main Methods:

  • Developed high-phylogenetic-resolution microbiome mapping by fluorescence in situ hybridization (HiPR-FISH).
  • Utilized binary encoding, spectral imaging, and machine learning for decoding microbial identities.
  • Employed custom algorithms for automated probe design and single-cell image analysis.

Main Results:

  • Demonstrated HiPR-FISH's ability to distinguish 1,023 unique Escherichia coli isolates using binary barcodes.
  • Revealed antibiotic-induced disruption of spatial networks in the mouse gut microbiome.
  • Showed longitudinal stability of spatial architectures in the human oral plaque microbiome.
  • Observed diverse ribosome organization strategies in the human oral microbiome using HiPR-FISH with super-resolution imaging.

Conclusions:

  • HiPR-FISH provides a novel framework for analyzing the spatial ecology of environmental microbial communities at single-cell resolution.
  • This technology advances our understanding of microbiome structure and function in various environments.