Toward Accurate and Robust Environmental Surveillance Using Metagenomics

Abstract

Environmental surveillance is a critical tool for combatting public health threats represented by the global COVID-19 pandemic and the continuous increase of antibiotic resistance in pathogens. With its power to detect entire microbial communities, metagenomics-based methods stand out in addressing the need. However, several hurdles remain to be overcome in order to generate actionable interpretations from metagenomic sequencing data for infection prevention. Conceptually and technically, we focus on viability assessment, taxonomic resolution, and quantitative metagenomics, and discuss their current advancements, necessary precautions and directions to further development. We highlight the importance of building solid conceptual frameworks and identifying rational limits to facilitate the application of techniques. We also propose the usage of internal standards as a promising approach to overcome analytical bottlenecks introduced by low biomass samples and the inherent lack of quantitation in metagenomics. Taken together, we hope this perspective will contribute to bringing accurate and consistent metagenomics-based environmental surveillance to the ground.

Keywords: environmental surveillance; limit of detection; metagenomics; quantitative metagenomics; taxonomic resolution; viability.

FIGURE 1

(A) Best practices in environmental surveillance using metagenomics (with examples). Internal standards are added to collected samples, while external standards are run in parallel with samples throughout the pipeline to assure its performance. An example is provided for demonstration purposes. Note that the standards given in this example only have theoretical potentials; more investigations are needed for benchmark and optimization. In this example, species level resolution is needed to distinguish S. epidermidis, S. aureus, and S. delphini. Assuming S. delphini is a good internal standard for Staphylococcus but not for Clostridium, in this case, quantitative risk assessment can only be achieved for S. epidermidis and S. aureus, but qualitative lesson can still be gained for C. difficile. (B) Viability assessment coupled with metagenomic sequencing represents an accessible way to infer infection risk.