Science Spatial Transcriptomics of Single-Cell Resolution Bacterial Populations

Monitor microbial communities cell by cell

In any biological community, gene expression is heterogeneous, which may be manifested in genetically identical individuals with different phenotypes
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We must observe individuals in context and analyze patterns in space and time in order to see the complete picture

Microbial populations exhibit heterogeneous gene expression profiles, leading to phenotypic differences between individual bacteria
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This diversity allows populations to survive under uncertain and fluctuating conditions, such as sudden exposure to antibiotics, dividing expensive functions between different subpopulations, and enabling interactions between different phenotypes

The micro-scale heterogeneity that defines microbial life can play an important role in areas such as antibiotic resistance and virulence
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However, our understanding of these basic characteristics is limited by our ability to capture this heterogeneity on relevant temporal and spatial scales

This article developed par-seqFISH (Parallel Sequential Fluorescence In Situ Hybridization), which is a high-throughput method that can capture the gene expression profile of individual bacteria while preserving their physical environment in a spatial structure environment
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We apply this method to the study of Pseudomonas aeruginosa, which is a typical biofilm-forming bacteria and an opportunistic human pathogen

In terms of P.
aeruginosa (P.

Transcriptional composition using par-seqFISH captures micro-scale phenotypic changes in free-living and sessile bacterial populations
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This article reports the population of P.
aeruginosa in growth, and proves that a single multicellular biofilm can contain coexisting but separate subpopulations with different physiological activities

Science, abi4882, this issue p.