STRATUM-Structured Framework for Reporting, Assessment, and Translational Utility of Metagenomics

Metagenomic next-generation sequencing (mNGS) enables broad, untargeted detection of pathogens and microbial signals across complex sample types. However, the diversity of operational contexts, from regulatory enforcement to exploratory discovery, challenges the defining of analytical or interpretive standards appropriate across all applications. Variability in laboratory practices, bioinformatic methods, and reporting conventions continues to limit consistency and decision-maker confidence in mNGS results.

We introduce STRATUM (Structured Framework for Reporting, Assessment, and Translational Utility of Metagenomics), a use-case-stratified framework that aligns quality assurance, metadata reporting, and interpretive standards with the consequence and intended use of metagenomic sequencing outputs.

STRATUM is organized around five representative biosurveillance use cases spanning public health, food safety, environmental monitoring, synthetic biology detection, and national security. A three-tier interpretive model calibrates analytical rigor, validation expectations, and reporting requirements to decision consequence; from high-consequence regulatory and clinical determinations (Tier 1), through operational surveillance (Tier 2), to exploratory and hypothesis-generating contexts (Tier 3).

The framework provides graduated guidance across key domains including sample preparation, sequencing design, controls and contamination governance, reference database curation, bioinformatics reproducibility, and multi-factor signal validation. Cross-cutting principles include explicit documentation of evidentiary bases, transparency in database and pipeline provenance, and defined escalation pathways when results transition between interpretive tiers.

Realizing the operational potential of mNGS requires evidentiary standards responsive to decision context rather than fixed across applications. STRATUM offers a consequence-tiered model for quality and reporting in applied metagenomics, supporting reproducible, transparent, and defensible sequencing-based surveillance across public health and biodefense domains.