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Imaging biofilms using fluorescence in situ hybridization: seeing is believing
Abstract
Biofilms are complex structures with an intricate relationship between the resident microorganisms, the extracellular matrix, and the surrounding environment. Interest in biofilms is growing exponentially given its ubiquity in so diverse fields such as healthcare, environmental and industry. Molecular techniques (e.g., next-generation sequencing, RNA-seq) have been used to study biofilm properties. However, these techniques disrupt the spatial structure of biofilms; therefore, they do not allow to observe the location/position of biofilm components (e.g., cells, genes, metabolites), which is particularly relevant to explore and study the interactions and functions of microorganisms. Fluorescence in situ hybridization (FISH) has been arguably the most widely used method for an in situ analysis of spatial distribution of biofilms. In this review, an overview on different FISH variants already applied on biofilm studies (e.g., CLASI-FISH, BONCAT-FISH, HiPR-FISH, seq-FISH) will be explored. In combination with confocal laser scanning microscopy, these variants emerged as a powerful approach to visualize, quantify and locate microorganisms, genes, and metabolites inside biofilms. Finally, we discuss new possible research directions for the development of robust and accurate FISH-based approaches that will allow to dig deeper into the biofilm structure and function.
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“Advanced methods such as peptide nucleic acid fluorescence in situ hybridization (PNA-FISH)44 provide insights into the microbial composition and distribution but do not offer details about the structural and topographic interactions between biofilms and tissues that SEM provides.”
From SEMTWIST Quantification of Biofilm Infection in Human Chronic Wound Using Scanning Electron Microscopy and Machine Learning (2025) · cites this paper as [44]
In the citing paper
“PNA-FISH specifically identifies bacterial species and displays aggregation characteristics thus helping identify and characterize BFI.44”
From SEMTWIST Quantification of Biofilm Infection in Human Chronic Wound Using Scanning Electron Microscopy and Machine Learning (2025) · cites this paper as [44]
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Spatially resolved, highly multiplexed RNA profiling in single cells
Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S., & Zhuang, X. (2015) · Science · doi:10.1126/science.aaa6090 · Cited by 2,969
Imaging individual mRNA molecules using multiple singly labeled probes
Raj, A., van den Bogaard, P., Rifkin, S. A., van Oudenaarden, A., & Tyagi, S. (2008) · Nature Methods · doi:10.1038/nmeth.1253 · Cited by 2,028
Strategies for combating bacterial biofilm infections
Wu, H., Moser, C., Wang, H.-Z., Høiby, N., & Song, Z.-J. (2015) · International Journal of Oral Science · doi:10.1038/ijos.2014.65 · Cited by 925
Swidsinski, A., Weber, J., Loening-Baucke, V., Hale, L. P., & Lochs, H. (2005) · Journal of Clinical Microbiology · doi:10.1128/jcm.43.7.3380-3389.2005 · Cited by 894 · cited 1×
“As mentioned in previous sections, several FISH variants provide important phylogenetic information in complex and heterogeneous biofilms (Swidsinski et al., 2005).”
BackgroundShaping the growth behaviour of biofilms initiated from bacterial aggregates
Melaugh, G., Hutchison, J., Kragh, K. N., Irie, Y., Roberts, A., Bjarnsholt, T., Diggle, S. P., Gordon, V. D., & Allen, R. J. (2016) · PLoS ONE · doi:10.1371/journal.pone.0149683 · Cited by 93
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Cited by
Sorted by citations
Singh, S., Muniz De Oliveira, F., Wang, C., Kumar, M., Xuan, Y., DeMazumder, D., Sen, C. K., & Roy, S. (2025) · Advances in Wound Care · doi:10.1089/wound.2024.0291 · Cited by 6
Metadata
- Authors
- Barbosa, A., Miranda, S., Azevedo, N. F., Cerqueira, L., & Azevedo, A. S.
- Venue
- Frontiers in Cellular and Infection Microbiology
- Publisher
- Frontiers Media SA
- Published
- 2023-05-22
- Volume
- 13
- ISSN
- 2235-2988
- PMC
- PMC10239779
- Cited by
- 63
- References
- 5
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