An optimized flow cytometry sorting-sequencing workflow reduces storage, sorting, and extraction bias in sorted microbial communities
Valerie Goethals, Nathan Vanwinsen, Fabian Mermans, Sofie De Gand, Nico Boon, Tom Van de Wiele, Kim De PaepeABSTRACT
Fluorescence-activated cell sorting (FACS) followed by metataxonomics is commonly used to probe the composition of microbial subpopulations with a functionality of interest. Metataxonomic analysis of sorted low-microbial-biomass samples is prone to contamination and bias introduced during sorting and DNA extraction. To improve metataxonomic accuracy, the DNA yield obtained by the DNeasy PowerSoil Pro kit was first maximized. FACS-sequencing using the optimized DNA extraction method distorted the composition of sorted microbiota by introducing sheath fluid contaminants, termed the FACSome. Since FACSome contaminants were experiment-specific, a standardized, applicable
IMPORTANCE
Bulk meta-omics fail to provide sufficient resolution to gain mechanistic insights in microbial ecosystems. Function-driven microbiome research requires high-throughput profiling of active microbial subpopulations. These can be singled out through fluorescence-activated cell sorting (FACS) combined with function-, activity-, or viability-based labeling. The resulting low-biomass sorted samples present a currently overlooked challenge for accurate 16S rRNA gene profiling. We systematically identified all potential sources of interference to enable decontamination of 16S rRNA gene sequences from sorted microbiota. While this study focused on metataxonomic read-outs, our optimized extraction and decontamination workflow can advance other sequencing-based omics analyses of sorted microbial communities. Our optimized FACS-sequencing workflow is thus imperative to unlock the full potential of single-cell labeling and FACS, in turn enabling mode-of-action studies that will broaden our understanding of microbe-environment interactions.