Multi-kingdom microbiota dynamics in exposed saliva: Integrating relative and absolute abundance across bacteria and...

As an important body fluid of the human body, saliva harbors a diverse microbial community, yet the dynamic succession of its microbiota following environmental exposure remains incompletely understood. Most current studies focus solely on relative abundance and community structure derived from sequencing, which may lead to misinterpretation of microbial dynamics. Moreover, existing research has almost exclusively centered on bacterial communities, largely overlooking the role of fungi. In this study, we conducted a 90-day exposure experiment in two environments (an incubator and an indoor setting) and used 16S rRNA gene and ITS absolute quantification sequencing to characterize the structure and abundance of bacterial and fungal communities. Despite prolonged environmental exposure, core bacterial genera in saliva, such as Streptococcus, Actinomyces, Rothia, Neisseria, Veillonella, and Prevotella, persisted in the samples. An interaction between salivary and environmental bacterial communities was observed, which strengthened over time. Relative and absolute abundance analyses revealed different patterns: relative abundance suggested a moderately stable community structure with individual specificity, whereas absolute quantification demonstrated a significant decrease in total bacterial load over time. Fungal communities were nearly undetectable in fresh saliva but became detectable after 25 days of exposure in the incubator and subsequently increased in abundance, dominated by Aspergillus. In contrast to the significant decline in bacterial absolute abundance over time, fungi exhibited a continuous increase, with a negative correlation between the two. Relative abundance was more effective for individual identification, while absolute abundance performed better in time since deposition (TsD) estimation. Further incorporation of fungal data enhanced the accuracy of the TsD prediction model, as indicated by a mean absolute error (MAE) of 7.485 days and an R² of 0.905, highlighting the advantage of multi-kingdom microbial analysis.