High-throughput identification and quantification of single bacterial cells in the microbiota

The bacterial microbiota works as a community that consists of many individual organisms, i.e., cells. To fully understand the function of bacterial microbiota, individual cells must be identified; however, it is difficult with current techniques. Here, we develop a method, Barcoding Bacteria for Identification and Quantification (BarBIQ), which classifies single bacterial cells into taxa-named herein cell-based operational taxonomy units (cOTUs)-based on cellularly barcoded 16S rRNA sequences with single-base accuracy, and quantifies the cell number for each cOTU in the microbiota in a high-throughput manner. We apply BarBIQ to murine cecal microbiotas and quantify in total 3.4 x 10(5) bacterial cells containing 810 cOTUs. Interestingly, we find location-dependent global differences in the cecal microbiota depending on the dietary vitamin A deficiency, and more differentially abundant cOTUs at the proximal location than the distal location. Importantly, these location differences are not clearly shown by conventional 16S rRNA gene-amplicon sequencing methods, which quantify the 16S rRNA genes, not the cells. Thus, BarBIQ enables microbiota characterization with the identification and quantification of individual constituent bacteria, which is a cornerstone for microbiota studies. Here, Jin et al., develop a method called Barcoding Bacteria for Identification and Quantification (BarBIQ), which allows to both characterize the global microbiome and to identify and quantify single-cell bacterial members in a high-throughput manner.

Automated summary

The study develops a method called Barcoding Bacteria for Identification and Quantification (BarBIQ) that allows for the classification and quantification of individual bacterial cells in the microbiota. It is found that BarBIQ reveals location-dependent differences in the microbiota, which cannot be shown by conventional 16S rRNA gene-amplicon sequencing methods.