Single-cell RNA sequencing of plant-associated bacterial communities
- 1The Ohio State University, United States
- 2South Dakota State University, United States
- 3Departments of Plant Science and Biology & Microbiology, South Dakota State University, United States
Plants in soil are not solitary, hence continually interact with and obtain benefits from a community of microbes (“microbiome”). The meta-functional output from the microbiome results from complex interactions among the different community members with distinct taxonomic identities and metabolic capacities. Particularly, the bacterial communities of the root surface are spatially organized structures composed of root-attached biofilms and planktonic cells arranged in complex layers. With the distinct but coordinated roles among the different member cells, bacterial communities resemble properties of a multicellular organism. High throughput sequencing technologies have allowed rapid and large-scale analysis of taxonomic composition and metabolic capacities of bacterial communities. However, these methods are generally unable to reconstruct the assembly of these communities, or how the gene expression patterns in individual cells/species are coordinated within these communities. Single-cell transcriptomes of community members can identify how gene expression patterns vary among members of the community, including differences among different cells of the same species. This information can be used to classify cells based on functional gene expression patterns, and predict the spatial organization of the community. Here we discuss strategies for the isolation of single bacterial cells, mRNA enrichment, library construction, and analysis and interpretation of the resulting single-cell RNA-Seq datasets. Unraveling regulatory and metabolic processes at the single cell level is expected to yield an unprecedented discovery of mechanisms involved in bacterial recruitment, attachment, assembly, organization of the community, or in the specific interactions among the different members of these communities.
Keywords: rhizosphere, microbiome, FACS (fluorescence-activated cell sorting), Rolling circle amplification (RCA), Single primer isothermal amplification (SPIA), droplet-sequencing (Drop-seq), split pool ligation-based transcriptome sequencing (SPLiT-seq)
Received: 05 Apr 2019;
Accepted: 11 Oct 2019.
Copyright: © 2019 Ma, Bücking, Gonzalez Hernandez and Subramanian. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Sen Subramanian, South Dakota State University, Departments of Plant Science and Biology & Microbiology, Brookings, 57007, South Dakota, United States, Senthil.Subramanian@sdstate.edu