Quantitative microbiome profiling in lumenal and tissue samples with broad coverage and dynamic range via a single-step 16S rRNA gene DNA copy quantification and amplicon barcoding

Current methods for detecting, accurately quantifying, and profiling complex microbial communities based on the microbial 16S rRNA marker genes are limited by a number of factors, including inconsistent extraction of microbial nucleic acids, amplification interference from contaminants and host DNA, different coverage of PCR primers utilized for quantification and sequencing, and potentially biases in PCR amplification rates among microbial taxa during amplicon barcoding. Here, we describe a single-step method that enables the quantification of microbial 16S rRNA gene DNA copies with wide dynamic range and broad microbial diversity, and simultaneous amplicon barcoding for quantitative 16S rRNA gene amplicon profiling of microbiota. The method is suitable for a variety of sample types and is robust in samples with low microbial abundance, including samples containing high levels of host mammalian DNA, as is common in human clinical samples. We demonstrate that our modification to the Earth Microbiome Project (EMP) V4 16S rRNA gene primers expands their microbial coverage while dramatically reducing non-specific mammalian mitochondrial DNA amplification, thus achieving wide dynamic range in microbial quantification and broad coverage for capturing high microbial diversity in samples with or without high host DNA background. The approach relies only on broadly available hardware (real-time PCR instruments) and standard reagents utilized for conventional 16S rRNA gene amplicon library preparation both of which make it amenable for immediate and widespread adoption. Simultaneous 16S rRNA gene DNA copy quantification and amplicon barcoding for multiplexed next-generation sequencing from the same analyzed sample, performed in a combined workflow, reduces the amount of sample needed and reduces time and reagent costs. Additionally, we demonstrate that using our modified 16S rRNA gene primers in a digital PCR (dPCR) format enables precise and exact microbial quantification in samples with very high host DNA background levels without the need for quantification standards. Potential future applications of this approach include: (1) quantitative microbiome profiling in human and animal microbiome research; (2) detection of monoinfections and profiling of polymicrobial infections in tissues, stool, and bodily fluids in human and veterinary medicine; (3) environmental sample analyses (e.g., soil and water); and (4) broad-coverage detection of microbial food contamination in products high in mammalian DNA, such as meat products. We predict that utilization of this approach primarily for quantitative microbiome profiling will be invaluable to microbiome studies, which have historically been limited to analysis of relative abundances of microbes