Quantifying live microbial load in human saliva samples over time reveals stable composition and dynamic load. SRS study

abstract: Background: Human saliva contains a distinct and rich community of microorganisms. While the microbial composition of saliva has been documented, the number of microorganisms present in saliva and how this number changes over time remains unclear. Furthermore, the viability of these microorganisms over time is also unknown. Here we present a novel method to characterize live microbial load in parallel with microbiome sequencing. We apply this method to unstimulated saliva samples collected in two distinct experiments; one collected longitudinally throughout the entire course of an ordinary day and the other collected across an acute perturbation. Results: We found that salivary flow rate is inversely correlated with microbial load. The number of microorganisms in saliva changed by orders of magnitude throughout the day, highlighting the importance of using computational tools that account for the inherent compositional nature of microbiome sequencing data. Removing relic DNA with PMA treatment improved resolution across longitudinally collected samples. A decrease in microbial load following alcohol-free mouthwash use was only detectable following PMA treatment. Despite large fluctuations in microbial load, we found that saliva microbial composition is remarkably stable and highly host-specific. Conclusions: The results of this analysis provide novel insight about the salivary microbiome, will help inform the design and analysis of future saliva microbiome studies, and together provide a community resource that will be useful for studies benchmarking new computational tools for the analysis of compositional datasets.