Species‐Level Characterization of the Nasal Microbiome in Various Disease States Utilizing Third‐Generation Sequencing

Clinical microbiology has long relied on culture-based methods, yet these approaches miss fastidious, slow-growing, or unculturable organisms and incompletely characterize polymicrobial communities. Short-read next-generation sequencing (NGS), particularly 16S rRNA analysis, has advanced microbiome research but is limited to genus-level resolution, limiting our understanding of microbiome. Third generation long-read sequencing is a technologic advance, allowing full-length 16S profiling and precise species-level identification. This distinction is particularly important in sinonasal disease, where pathogenic and commensal species within the same genus may carry different implications for health and treatment. We present our preliminary work using long-read sequencing to characterize the sinonasal microbiome and discuss the implication of these new platforms. Culture-based methods remain the backbone of clinical microbiology, providing viable isolates for susceptibility testing and epidemiology, but they suffer from critical limitations [1]. They favor easily cultured organisms while missing fastidious, anaerobic, or low-burden microbes, and they incompletely characterize polymicrobial environments such as the sinonasal cavity [2]. Additionally, results are slow, often taking days to weeks, and do not always reflect the dynamic microbial communities that influence disease [3]. In chronic rhinosinusitis, where dysbiosis may play a role in pathogenesis, culture may capture only part of the picture and misrepresent the true microbial landscape [4]. Short-read sequencing has expanded our ability to study sinonasal microbiome by uncovering organisms that cannot be cultured and by providing snapshots of community composition [5]. These methods classically rely on sequencing 16S rRNA gene; however this limits taxonomic resolution to the genus level [6]. This limitation is not trivial. Within the same genus, species can have very different, even opposing, clinical roles. For example, Staphylococcus aureus is a well-known pathogen, whereas Staphylococcus epidermidis is considered a commensal that can become pathogenic under certain circumstances. Collapsing them into a single “Staphylococcus” category obscures these distinctions and undermines the clinical utility of the data. Recently with advances in sequencing technologies “long-read sequencing” has become cost effective and allows species-level resolution [7]. Platforms such as Pacific Biosciences and Oxford Nanopore sequence native DNA molecules directly, producing long reads that overcome the ambiguities of short-read data [8]. This shift is not merely technical—it is conceptual. Species-level identification allows clinicians and researchers to move beyond generalized genus-level associations and toward nuanced, clinically relevant microbial insights. To highlight these improvements in technology, patients were consented under UNC IRB 17-2677. Prior to clinical evaluation or surgical procedures nasal epithelial lining fluid was collected, using Leukosorb strips from the middle meatus, from 46 patients – 21 with CRSsNP, 8 with CRSwNP, and 17 healthy controls. Samples were collected during routine visits with no exacerbations or antibiotics within the last 6 weeks. RNA was isolated and full-length 16S rRNA sequencing was performed with third generation sequencing technology as previously described [8, 9]. Microbiome composition was analyzed using PERMANOVA and relative abundance profiling at genus and species levels. Diversity metrics and overall bacterial composition did not differ significantly between groups. However, long-read sequencing revealed meaningful species-level trends (Figure 1). In the CRSsNP cohort, relative abundance of Streptococcus pneumoniae and Staphylococcus epidermidis appeared higher compared with other groups. In the CRSwNP cohort, we observed greater representation of Moraxella catarrhalis, Moraxella nonliquefaciens, Dolosigranulum pigrum, and Corynebacterium accolens, with lower Staphylococcus aureus and Cutibacterium acnes. These species-level patterns likely reflect inter-individual variability rather than statistically confirmed differences but demonstrate the capacity of long-read sequencing to resolve nuanced microbial trends that merit further study. While formal differential abundance testing using ANCOM-BC2 did not identify statistically significant differences between CRS phenotypes, this likely reflects both substantial inter-individual variability and the modest cohort size, which together limit statistical power. Nonetheless, these descriptive patterns highlight the biological and potential clinical insights uniquely accessible through species-level analysis. Future studies will specifically target patients with refractory or purulent CRS to determine whether active infection alters species-level community structure. The implications of third-generation sequencing for rhinology are substantial. Species-level resolution enables a more comprehensive understanding of how microbial community shifts relate to patient symptoms and influence epithelial function. These data can support the development of targeted interventions—such as probiotics, bacteriotherapies, or other microbiome-based therapeutics—tailored to specific patterns of dysbiosis. Importantly, these community-level changes do not imply inherent pathogenicity or commensalism of individual species; rather, they reflect complex, context-dependent interactions among microbes and between the microbiota and host immunity. Challenges remain before these approaches can be widely adopted in clinical practice. Long-read sequencing requires bioinformatics expertise and lacks standardized protocols as a clinical diagnostic test. Yet the pace of technological improvement suggests that these barriers will not persist indefinitely [10]. As sequencing becomes faster, cheaper, and more accessible, species-level microbiome profiling will likely transition from a research tool to a standard element of clinical care. Culture-based methods and short-read sequencing have served rhinology well, but they are insufficient for the future of microbiome-driven science. Long-read sequencing provides the species-level clarity that clinicians and researchers need, distinguishing pathogens from commensals and revealing microbial shifts that matter for patient outcomes. We believe that the next era of sinonasal microbiome research and diagnostics depends on embracing long-read technologies, not as a replacement for culture but as a transformative adjunct that will redefine how we understand and manage sinonasal disease.