Library strategies differentially shape microbial, functional, and host signals in clinical metagenomic sequencing.
Metagenomic next-generation sequencing (mNGS) is increasingly used in infectious disease diagnostics, yet how library preparation shapes the microbial, functional, and host signals recovered from clinical samples remains poorly defined. Here, we performed a within-sample parallel comparison of three mNGS library preparation strategies-DNA-based libraries (DNAlib), RNA-based libraries (RNAlib), and total nucleic acid-based libraries (TNAlib)-across a diverse range of clinical specimens spanning five sample types. Using a curated clinical infectome as a benchmark, we show that library strategies are not interchangeable but capture distinct biological dimensions of the same specimen. RNAlib provided the most comprehensive standalone recovery of the clinical infectome, with improved detection of RNA viruses and cellular pathogens, enhanced resolution of resistance and virulence signals, and preservation of infection-associated host immune signatures. DNAlib showed stronger baseline recovery of DNA viruses and broader host genome coverage, whereas the TNAlib workflow evaluated here largely behaved as an intermediate strategy rather than a consistent improvement over dedicated DNA- or RNA-based workflows. Together, these results establish that the library preparation protocol is a major determinant of how clinical mNGS data should be interpreted and provide a framework for selecting sequencing strategies according to specific diagnostic and biological questions.IMPORTANCEMetagenomic sequencing is increasingly used in infectious disease research and clinical diagnostics, but different library preparation strategies may recover fundamentally different biological signals from the same sample. These signals include not only pathogens but also background microbes, microbial functional activity, and host immune-response patterns. Here, we systematically compared DNA-, RNA-, and total nucleic acid-based metagenomic sequencing libraries using the same clinical samples processed in parallel. We found that the three strategies did not provide equivalent information. RNA-based sequencing generated the most informative single-library view of infection, particularly for RNA viruses, cellular pathogens, functional microbial signals, and host immune-response patterns. DNA-based sequencing was more effective for DNA virus and host genome recovery, whereas the total nucleic acid sequencing workflow evaluated here generally behaved as an intermediate strategy. These findings show that library preparation can substantially influence the interpretation of metagenomic data.