Quantitative metagenomics using a portable protocol

A field-deployable DNA sequencing approach for quantitative microbial community profiling can enable rapid responses for a range of applications in the water sector-from process control to wastewater surveillance. Current quantitative approaches require complex instrumentation and have long turnaround times for DNA recovery and absolute quantitation. In this study, we report a field-deployable rapid detection and rapid absolute quantitation (rD+rQ) workflow that leverages real-time Nanopore sequencing for quantitative metagenomics. This workflow integrates a high-molecular-weight DNA recovery protocol for diverse environmental matrices of relevance to the water sector, and multiplexed Nanopore sequencing with barcoded spike-in-based calibration (BSINC). BSINC using multispecies genomic spike-in controls exhibits significantly higher calibration accuracy compared to conventional approaches that utilize either a single DNA fragment or single organism spike-in controls. Dynamic detection and quantitation limits were established based on the coverage fraction of sequenced genomes and the coefficient of variation of genome copy numbers across replicates to enhance the accuracy and precision of microbial quantitation. The rD+rQ workflow achieves species-level identification and absolute quantitative results comparable to digital PCR in environmental samples. This portable laboratory and easy-to-use rD+rQ workflow should facilitate rapid decision-making for the water industry.IMPORTANCERapid and real-time monitoring of microbial communities is critical for a vast array of applications in environmental microbiology and biotechnology. While recent developments in portable sequencing technologies and associated workflows make onsite analysis possible, these approaches do not provide quantitative data on microbial concentrations. In this study, we present a sample and data processing workflow that enables nontargeted and quantitative microbial community profiling and demonstrate its validity on complex environmental samples. This approach for acquiring quantitative data can drive rapid decision-making from bioprocess control to wastewater-based epidemiology.