Benchmarking datasets for microbiome profiling

Sequencing-based microbiome profiling aims at detecting and quantifying individual members of a complex microbial community in a culture-independent manner. Due to its low cost, amplicon-based sequencing (ABS) of bacterial or fungal ribosomal DNA is the most widely used technology for this purpose, however results suffer from PCR biases. Shotgun metagenomics (SMG), conversely, allows unbiased interrogation of a microbial community but requires high sequencing depth. Here we report the development of a Meta-Total RNA Sequencing (MeTRS) method based on shotgun sequencing of 'untouched' total RNA and benchmark it on a human stool sample spiked-in with known numbers of yeast and bacterial cells. Compared to SMG or ABS, MeTRS displayed the highest sensitivity and linearity, especially for fungal species, and the greatest reproducibility, while requiring a ~20-fold lower sequencing depth than SMG. We therefore recommend MeTRS for large-scale profiling of complex microbiomes containing both bacteria and fungi.