Towards a Rapid-Turnaround Low-Depth Unbiased Metagenomics Sequencing Workflow on the Illumina Platforms

Unbiased metagenomic sequencing is conceptually well-suited for first-line diagnosis as all known and unknown infectious entities can be detected, but costs, turnaround time and human background reads in complex biofluids, such as plasma, hinder widespread deployment. Separate preparations of DNA and RNA also increases costs. In this study, we developed a rapid unbiased metagenomics next-generation sequencing (mNGS) workflow with a human background depletion method (HostEL) and a combined DNA/RNA library preparation kit (AmpRE) to address this issue. We enriched and detected bacterial and fungal standards spiked in plasma at physiological levels with low-depth sequencing (<1 million reads) for analytical validation. Clinical validation also showed 93% of plasma samples agreed with the clinical diagnostic test results when the diagnostic qPCR had a Ct < 33. The effect of different sequencing times was evaluated with the 19 h iSeq 100 paired end run, a more clinically palatable simulated iSeq 100 truncated run and the rapid 7 h MiniSeq platform. Our results demonstrate the ability to detect both DNA and RNA pathogens with low-depth sequencing and that iSeq 100 and MiniSeq platforms are compatible with unbiased low-depth metagenomics identification with the HostEL and AmpRE workflow.

Automated summary

In this study, a rapid unbiased metagenomics next-generation sequencing (mNGS) workflow with a human background depletion method (HostEL) and a combined DNA/RNA library preparation kit (AmpRE) was developed to address the issues of cost, turnaround time, and human background reads in complex biofluids. Low-depth sequencing (<1 million reads) was used to enrich and detect bacterial and fungal standards spiked in plasma at physiological levels. Clinical validation showed a high agreement between mNGS results and clinical diagnostic test results. Different sequencing times were evaluated, and the iSeq 100 and MiniSeq platforms were found to be compatible with the HostEL and AmpRE workflow for unbiased low-depth metagenomics identification.