For over three decades, fluorescence in situ hybridization (FISH) has been a key method for visualizing microbial communities across diverse environments. Used by researchers all over the world, FISH provides information on the morphology, abundance, and spatial organization of microorganisms living in complex communities. However, the approach is limited by its dependence on a single gene product, 16S rRNA, which cannot distinguish closely related microorganisms and is generally reliable only at the genus level. Moreover, microbes with low ribosome counts produce weak fluorescent signals that are difficult to detect, and the labor-intensive design and optimization of FISH probes make the method impractical for scaling across the vast diversity of microbial life.
To address these limitations, the authors developed GenomeFISH, a genome-based FISH method that combines high-throughput, single-cell genomics with whole-genome hybridization to visualize microbial communities with strain-level specificity. For GenomeFISH, probes are generated from the entire genome of a microorganism, which can be rapidly recovered from any given sample using fluorescence-activated single cell sorting (FACS) or alternatively, from microbial cultures. These genomes are amplified (when using single cells), fragmented, fluorescently labelled, and applied back to the original sample to visualize the microorganism of interest. As GenomeFISH targets the entire genome, it omits the need to design probes, while increasing sensitivity and specificity. In tests across diverse samples, GenomeFISH was able to visualize closely related strains (up to 99% average nucleotide identity) and microbes that could not be observed with traditional FISH.
GenomeFISH provides researchers with a powerful tool for investigating the fine-scale structure and dynamics of microbial communities. It also dramatically expands detection capabilities, allowing visualization of microorganisms that traditional FISH would typically miss, including those hidden in highly autofluorescent matrices or exhibiting very low metabolic activity. While rRNA-based FISH has underpinned the ‘full-cycle approach’ in microbial ecology for over three decades—profiling a community and then visualizing it based on rRNA gene sequencing—GenomeFISH modernizes this approach for the meta-omic era, enabling both analysis and visualization of microbes directly from their genomes. With its high sensitivity, strain-level resolution, and high-throughput capabilities, the authors envisage GenomeFISH becoming the new gold standard for visualizing complex microbial communities.
Read the full journal article titled ‘GenomeFISH: genome-based fluorescence in situ hybridization for strain-level visualization of microbial communities‘ in The ISME Journal. This article has been selected as Editor’s Choice for the month of July 2025.
Authors
1. J. Pamela Engelberts, Queensland University of Technology, Australia
2. Jun Ye, University of Queensland, Australia
3. Donovan H. Parks, University of Queensland, Australia
4. Eilish S. McMaster, Queensland University of Technology, Australia
5. Allison S. McInnes, Queensland University of Technology, Australia
6. Ben J. Woodcroft, Queensland University of Technology, Australia
7. James G. Volmer, Queensland University of Technology, Australia
8. Simon J. McIlroy, Queensland University of Technology, Australia
9. Gene W. Tyson, Queensland University of Technology, Australia