Distinguishing viable from non-viable microbes remains a major hurdle in microbiome research, limiting our ability to fully understand microbial community structure, function, and transmission. Microbial viability is critical for interpreting the biological and ecological roles of microbiomes, as only living microbes actively participate in processes such as metabolism, signaling, and host interactions. Existing methods, such as chemical-based viability assays and 16S rRNA transcript detection, have proven suboptimal in complex communities, while shotgun metagenomics and metatranscriptomics, though informative, are often prohibitively expensive and computationally demanding. To address these limitations, we are developing a novel, high-throughput viability assessment approach based on sequencing optimized marker gene transcripts.

Our method combines rational marker gene selection, in silico primer design, and amplicon sequencing to enable precise, scalable differentiation of actively transcribing microbes within diverse communities. We have constructed and evaluated a marker gene database, designed candidate primers, and established a marker gene amplicon-sequencing protocol using paired metagenomic and metatranscriptomic datasets. We have further tested this approach in synthetic microbial communities as well as realistic human-associated and built environment samples. In synthetic communities, the marker gene-based method accurately profiled community composition in DNA samples and successfully identified active microbial members in RNA-derived cDNA samples, supporting its potential for viability-aware microbiome profiling. The protocol is now close to finalization, with ongoing efforts focused on updating the marker gene database, further refining marker gene coverage, and implementing a finalized bench protocol for improved robustness and practical use. Once established, this workflow will offer an accessible, culture-independent solution for microbiome viability profiling. This approach has broad implications for advancing microbiome-based diagnostics, therapeutic development, and environmental surveillance by providing a much-needed tool to quantify the active, functional members of microbial communities.