Translational frameshifting involves the repositioning of ribosomes on their messages into decoding frames that differ from those dictated during initiation. Some messenger RNAs (mRNAs) contain motifs that promote deliberate frameshifting to regulate production of the encoded proteins. The mechanisms of frameshifting have been investigated in many systems, and the resulting models generally involve single ribosomes responding to stimulator sequences in their engaged mRNAs. We discovered that the abundance of ribosomes on messages containing the IS3, dnaX, and prfB frameshift motifs significantly influences the levels of frameshifting. We show that this phenomenon results from ribosome collisions that occur during translational stalling, which can alter frameshifting in both the stalled and trailing ribosomes. Bacteria missing ribosomal protein bL9 are known to exhibit a reduction in reading frame maintenance and to have a strong dependence on elongation factor P (EFP). We discovered that ribosomes lacking bL9 become compacted closer together during collisions and that the E-sites of the stalled ribosomes appear to become blocked, which suggests subsequent transpeptidation in transiently stalled ribosomes may become compromised in the absence of bL9. In addition, we determined that bL9 can suppress frameshifting of its host ribosome, likely by regulating E-site dynamics. These findings provide mechanistic insight into the behavior of colliding ribosomes during translation and suggest naturally occurring frameshift elements may be regulated by the abundance of ribosomes relative to an mRNA pool. Significance Ribosomes move along mRNAs in 3-nucleotide steps as they interpret codons that specify which amino acid is required at each position in the protein. There are multiple examples of genes with DNA sequences that do not match the produced proteins because ribosomes move to a new reading frame in the message before finishing translation (so-called frameshifting). This report shows that, when ribosomes stall at mRNA regions prone to cause frameshifting events, trailing ribosomes that collide with them can significantly change the outcome and potentially regulate protein production. This work highlights the principle that biological macromolecules do not function in isolation, and it provides an example of how physical interactions between neighboring complexes can be used to augment their performance.

Quantitative polymerase chain reactions (qPCR) are used to monitor relative changes in very small amounts of DNA. One drawback to qPCR is reproducibility: measuring the same sample multiple times can yield data that is so noisy that important differences can be dismissed. Numerous analytical methods have been employed that can extract the relative template abundance between samples. However, each method is sensitive to baseline assignment and to the unique shape profiles of individual reactions, which gives rise to increased variance stemming from the analytical procedure itself. We developed a simple mathematical model that accurately describes the entire PCR reaction profile using only two reaction variables that depict the maximum capacity of the reaction and feedback inhibition. This model allows quantification that is more accurate than existing methods and takes advantage of the brighter fluorescence signals from later cycles. Because the model describes the entire reaction, the influences of baseline adjustment errors, reaction efficiencies, template abundance, and signal loss per cycle could be formalized. We determined that the common cycle-threshold method of data analysis introduces unnecessary variance because of inappropriate baseline adjustments, a dynamic reaction efficiency, and also a reliance on data with a low signal-to-noise ratio. Using our model, fits to raw data can be used to determine template abundance with high precision, even when the data contains baseline and signal loss defects. This improvement reduces the time and cost associated with qPCR and should be applicable in a variety of academic, clinical, and biotechnological settings.

Our study shows that e-cigarette aerosol exposure of selected bacteria known to be residents of the oral cavity hinders the growth of two streptococcal commensals while enhancing biofilm formation, hydrophobicity, and attachment for the pathogen S. mutans . These results indicate that e-cigarette vaping could open a niche for opportunistic bacteria such as S. mutans to colonize the oral cavity and affect oral health.

E-cigarette (e-cig) vapor has been shown to play a pathological role in oral health and alter the oral microbiota, providing growth advantages for opportunistic pathogens. Enrichment of Staphylococcus aureus, a commensal resident in the oral cavity, correlates with the progression of periodontal disease, suggesting a role as an opportunistic pathogen. Environmental conditions, such as cigarette smoke, are known to increase S. aureus virulence, yet the role of S. aureus in periodontitis and oral preneoplasia is unknown. We exposed oral epithelial cells to e-cig aerosols and showed a dose-dependent cell viability reduction, regardless of nicotine content, in a possible attempt to repair DNA damage, as measured by pH2AX. S. aureus attachment to oral epithelial cells and bacterial biofilm formation were enhanced upon e-cig exposure, indicating an increased capacity for oral colonization. Mechanistically, e-cig aerosol exposure resulted in an immunosuppression, as determined by a reduction in IL8, IL6, and IL1β secretion by oral epithelial cells during co-culture with S. aureus. Consistent with this, e-cig vape reduced the oral epithelial cell clearance of S. aureus. Furthermore, we observed an increased expression of the inflammatory regulator COX2. This work suggests that e-cigs promote S. aureus colonization and modulate the oral inflammatory response, possibly promoting oral periodontitis and preneoplasia.

The loss of the large ribosomal protein L9 causes a reduction in translation fidelity by an unknown mechanism. To identify pathways affected by L9, we identified mutants of E. coli that require L9 for fitness. In a prior study, we characterized L9-dependent mutations in the essential GTPase Der (EngA). Here, we describe a second class of L9-dependent mutations that either compromise or inactivate elongation factor P (EF-P, eIF5A in eukaryotes). Without L9, Δefp cells are practically inviable. Cell fractionation studies revealed that, in both the Der and EF-P mutant cases, L9's activity reduces immature 16S rRNA in 30S particles and partially restores the abundance of monosomes. Inspired by these findings, we discovered that L9 also enhances 16S maturation in wild-type cells. Surprisingly, although the amount of immature 16S in 30S particles was found to be elevated in ΔrplI cells, the amount in polysomes was low and inversely correlated with the immature 16S abundance. These findings provide an explanation for the observed fitness increases afforded by L9 in these mutants and reveal particular physiological conditions in which L9 becomes critical. Additionally, L9 may affect the partitioning of small subunits containing immature 16S rRNA.

This study reevaluates the notion that 16S rRNA gene variable region sequences are uninformative for intra-genus classification and that single nucleotide variations within them have no consequence to strains that bear them. We demonstrated that the performance of 16S rRNAs in Escherichia coli can be negatively impacted by sequence changes in variable regions, even for single nucleotide changes that are native to closely related Escherichia and Shigella species; thus, biological performance is likely constraining the evolution of variable regions in bacteria.