Background: Recent studies of various human microbiome habitats have revealed thousands of bacterial species and the existence of large variation in communities of microorganisms in the same habitats across individual human subjects. Previous efforts to summarize this diversity, notably in the human gut and vagina, have categorized microbiome profiles by clustering them into community state types (CSTs). The functional relevance of specific CSTs has not been established. Objective: We investigate whether CSTs can be used to assess dynamics in the microbiome. Design: We conduct a re-analysis of five sequencing-based microbiome surveys derived from vaginal samples with repeated measures. Results: We observe that detection of a CST transition is largely insensitive to choices in methods for normalization or clustering. We find that healthy subjects persist in a CST for two to three weeks or more on average, while those with evidence of dysbiosis tend to change more often. Changes in CST can be gradual or occur over less than one day. Upcoming CST changes and switches to high-risk CSTs can be predicted with high accuracy in certain scenarios. Finally, we observe that presence of Gardnerella vaginalis is a strong predictor of an upcoming CST change. Conclusion: Overall, our results show that the CST concept is useful for studying microbiome dynamics.

The role of mRNA processing in gene expression variability is poorly characterized. This study investigates the extent of cell-to-cell variability of alternative RNA splicing in mammalian cells using single-molecule imaging of CAPRIN1 and MKNK2 splice isoforms.

Although many proteins are known to function in microRNA (miRNA)-based translational repression, we lack a comprehensive understanding of temporal relationships between the mRNA, miRNA and their constituent proteins. To understand the dynamics of miRNA and protein interactions, we created a synthetic inducible miRNA system in mammalian cells. By visualizing single mRNAs and observing their co-localization with proteins over time, we produced a temporal association map of miRNA-associated factors. Argonaute2, Dcp1a, hedls and Rck co-localize with miRNA-regulated mRNA after 24 h of miRNA induction, and RNAi knockdown of any one of these proteins affected the co-localization of any of the other proteins with miRNA-regulated mRNA, demonstrating that these proteins could interact with each other in a complex. We identified Argonaute2 and hedls as proteins that co-localize and interact with miRNA-regulated mRNA, indicating that processing body components are involved in long-term storage of miRNA-regulated mRNA.