The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Spatial transcriptomics of planktonic and sessile bacterial populations at single-cell resolution
Open accessAbstract
Spying on microbial communities, cell by cell: Within any community of organisms, gene expression is heterogeneous, which can manifest in genetically identical individuals having a different phenotype. One has to look at individuals in context and analyze patterns in both space and time to see the full picture. Aiming to fill a gap in current methods, Dar et al . developed a transcriptome-imaging method named parallel sequential fluorescence in situ hybridization (par-seqFISH). They applied this technique to the opportunistic pathogen Pseudomonas aeruginosa , focusing on biofilms where growth conditions can change at microscopic scale. Development of these communities, as revealed by mRNA composition, were followed in space and time. The results revealed a heterogeneous phenotypic landscape, with oxygen availability shaping the metabolism at a spatial scale of microns within a single contiguous biofilm segment. This tool should be applicable to complex microbial communities in the environment and the human microbiome. —MAF
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Cited by
The expanding vistas of spatial transcriptomics
Tian, L., Chen, F., & Macosko, E. Z. (2023) · Nature Biotechnology · doi:10.1038/s41587-022-01448-2 · Cited by 539
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Imaging biofilms using fluorescence in situ hybridization: seeing is believing
Barbosa, A., Miranda, S., Azevedo, N. F., Cerqueira, L., & Azevedo, A. S. (2023) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2023.1195803 · Cited by 63
Computational methods and challenges in analyzing intratumoral microbiome data
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Metadata
- Authors
- Dar, D., Dar, N., Cai, L., & Newman, D. K.
- Venue
- Science
- Published
- 2021-08-13
- Volume
- 373
- Issue
- 6556
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W3192380610
- Cited by
- 299
- References
- 15
- FWCI
- 12.75
- Type
- journal article
- Language
- en
- Open access
- green
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