Single-cell resolution genetic association analysis of heterogeneous bacterial communities by utilizing droplet digital PCR
L. A. L. Dutra, M. Jalasvuori, O. Franz, K. Nurminen, P. Salmi, M. Tiirola, R. Penttinen
Abstract
Microbial communities often respond to environmental challenges, such as the presence of antibiotics, as a whole. Dissecting these community-level effects into separate acting entities requires the identification of organisms that carry functional genes for the observed feature. However, unculturable microbes are abundant in various environments, hence making the identification challenging. Moreover, while at present the development and application of single-cell tools for eukaryotic cells are enhancing, the comparable methodologies applicable for prokaryotic cells are still scarce and have not gained broad and solid status as tools for investigating microbial populations. Here, we present a cultivation-free technique that can be utilized to link functional genes with the carrying bacterial species at single-cell resolution. The developed protocol is relatively simple to use, utilizes commercially available droplet microfluidics devices, does not require toxic reagents, and eliminates invalid signals emerging from extracellular DNA. We validate the methodology by studying the conjugative transfer of antibiotic resistance plasmids in an environment challenged by antibiotics. Furthermore, the method can be customized for any given genetic trait to accurately identify its hosting subpopulation from a heterogeneous and potentially uncultivable bacterial community. ImportanceBacterial systems usually contain numerous different species that may harbor highly similar or identical genes that confer same phenotypic qualities for the community. To decipher the functions of these systems, we report the development of a novel methodology that enables investigating microbial communities at single-cell level. This user-friendly method utilizes droplet digital PCR (ddPCR) to find and identify carriers of specific genes potentially from various microbial sample types. By pinpointing gene carriers, such as those responsible for antibiotic resistance, this method can provide insights to the behavior of microbial communities and gene transfer therein. By strategically combining the use of common methods (ddPCR and amplicon sequencing), the workflow is highly accessible. Thus, it allows also the researchers without a background in single-cell techniques or access to special equipment to adopt the method for producing single-cell data to serve their own research, enabling new research avenues in microbial genetics and ecology.
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