Background: High-speed dental instruments produce aerosols, which can contribute to the transmission of pathogenic microorganisms. The aim of this study is to describe the microbial load and – composition and spatial distribution of aerosols in dental clinics. Methods: In four dental clinics active and passive sampling methods were used before, during and after treatment and at different locations. Retrieved colony forming units (CFU) were sequenced for taxon identification. Results: The samples contained up to 655 CFU/plate/30 minutes and 418 CFU/m³/30 minutes during dental treatment for active and passive sampling, respectively. The level of contamination after treatment and at 1.5 m distance from the patient’s head was similar to the start of the day. The highest contamination was found at the patient’s chest area. The aerosols consisted of 52 different taxa from human origin and 36 from water. Conclusion: Contamination in dental clinics due to aerosols is mainly low, although high level of contamination with taxa from both human and water origin was found within 80 cm around the head of the patient. Our results stress the importance of infection control measures on surfaces in close proximity to the head of the patient as well as in dental water lines.

Dental health care workers are in close contact to their patients and are therefore at higher risk for contracting airborne infectious diseases. The transmission rates of airborne pathogens from patient to dental health care workers are unknown. With the outbreaks of infectious diseases, such as seasonal influenza, occasional outbreaks of measles and tuberculosis, and the current pandemic of the coronavirus disease COVID-19, it is important to estimate the risks for dental health care workers. Therefore, the transmission probability of these airborne infectious diseases was estimated via mathematical modeling. The transmission probability was modeled for Mycobacterium tuberculosis, Legionella pneumophila, measles virus, influenza virus, and coronaviruses per a modified version of the Wells-Riley equation. This equation incorporated the indoor air quality by using carbon dioxide as a proxy and added the respiratory protection rate from medical face masks and N95 respirators. Scenario-specific analyses, uncertainty analyses, and sensitivity analyses were run to produce probability rates. A high transmission probability was characterized by high patient infectiousness, the absence of respiratory protection, and poor indoor air quality. The highest transmission probabilities were estimated for measles virus (100%), coronaviruses (99.4%), influenza virus (89.4%), and M. tuberculosis (84.0%). The low-risk scenario leads to transmission probabilities of 4.5% for measles virus and 0% for the other pathogens. From the sensitivity analysis, it shows that the transmission probability is strongly driven by indoor air quality, followed by patient infectiousness, and the least by respiratory protection from medical face mask use. Airborne infection transmission of pathogens such as measles virus and coronaviruses is likely to occur in the dental practice. The risk magnitude, however, is highly dependent on specific conditions in each dental clinic. Improved indoor air quality by ventilation, which reduces carbon dioxide, is the most important factor that will either strongly increase or decrease the probability of the transmission of a pathogen.

The aim of this prospective, two center study was to investigate the dynamics of the microbial changes in relation to the development of ulcerative oral mucositis in autologous SCT (autoSCT) recipients. Fifty-one patients were diagnosed with multiple myeloma and treated with high-dose melphalan followed by autoSCT. They were evaluated before, three times weekly during hospitalization, and three months after autoSCT. At each time point an oral rinse was collected and the presence or absence of ulcerative oral mucositis (UOM) was scored (WHO scale). Oral microbiome was determined by using 16S rRNA amplicon sequencing and fungal load by qPCR. Twenty patients (39%) developed UOM. The oral microbiome changed significantly after autoSCT and returned to pre-autoSCT composition after three months. However, changes in microbial diversity and similarity were more pronounced and rapid in patients who developed UOM compared to patients who did not. Already before autoSCT, different taxa discriminated between the 2 groups, suggesting microbially-driven risk factors. Samples with high fungal load (>0.1%) had a significantly different microbial profile from samples without fungi. In conclusion, autoSCT induced significant and reversible changes in the oral microbiome, while patients who did not develop ulcerative oral mucositis had a more resilient microbial ecosystem.

Oral mucositis (OM) is a common and impactful toxicity of standard cancer therapy, affecting up to 80% of patients. Its aetiology centres on the initial destruction of epithelial cells and the increase in inflammatory signals. These changes in the oral mucosa create a hostile environment for resident microbes, with oral infections co-occurring with OM, especially at sites of ulceration. Increasing evidence suggests that oral microbiome changes occur beyond opportunistic infection, with a growing appreciation for the potential role of the microbiome in OM development and severity. This review collects the latest articles indexed in the PubMed electronic database which analyse the bacterial shift through 16S rRNA gene sequencing methodology in cancer patients under treatment with oral mucositis. The aims are to assess whether changes in the oral and gut microbiome causally contribute to oral mucositis or if they are simply a consequence of the mucosal injury. Further, we explore the emerging role of a patient’s microbial fingerprint in OM development and prediction. The maintenance of resident bacteria via microbial target therapy is under constant improvement and should be considered in the OM treatment.

Oral ulcerations often arise as a side effect from chemo- and radiation therapy. In a previous clinical study,Porphyromonas gingivaliswas identified as a positive predictor for oral ulcerations after hematopoetic stem cell transplantation, possibly incriminatingP. gingivalisin delayed healing of the ulcerations. Therefore, it was tested whetherP. gingivalisand its secreted products could inhibit the migration of oral epithelial cells in anin vitroscratch assay. To compare, the oral bacteriaPrevotella nigrescens,Prevotella intermedia,Tannerella forsythia, andStreptococcus mitiswere included. A standardized scratch was made in a confluent layer of human oral epithelial cells. The epithelial cells were challenged with bacterial cells and with medium containing secretions of these bacteria. Closure of the scratch was measured after 17 h using a phase contrast microscope.P. gingivalis,P. nigrescens, and secretions ofP. gingivalisstrongly inhibited cell migration. A challenge with 1000 heat-killed bacteria versus 1 epithelial cell resulted in a relative closure of the scratch of 25% forP. gingivalisand 20% forP. nigrescens. Weaker inhibitory effects were found for the other bacteria. The results confirmed our hypothesis that the oral bacteria may be involved in delayed wound healing.

Objectives: The human oral microbiome may play a role in the development of oral squamous cell carcinoma. The aim of this scoping review was to examine microbial diversity and differences in the composition of the oral microbiome between OSCC patients and healthy controls.Methods: A literature search (in PubMed and Embase.com) was performed on January 9, 2023. The outcome variables used from the included studies of this review were alpha- and beta diversity and oral microbiome composition profiles for each taxonomic level (phylum-, class-, order-, genus- and species level).Results: Thirteen out of 423 studies were included in this review compromising 1,677 subjects, of which 905 (54.0%) were OSCC patients and 772 (46.0%) were healthy controls. Most studies found a higher alpha diversity in the OSCC patient group and significantly different beta diversities between OSCC patient samples and healthy control samples. Studies reported more abundant Fusobacteria (on phylum level), Fusobacterium (on genus level), Fusobacterium nucleatum, Porphyromonas endodontalis and Prevotella intermedia (on species level) in OSCC patients. The healthy control group had more abundant Actinobacteria (on phylum level), Streptococcus and Veilonella (on genus level) and Veilonella parvula (on species level) according to most studies.Conclusions: Our findings show differences in oral microbiome diversity and composition in OSCC patients. Clinical implications demand continuing study. Development of internationally accepted standard procedures for oral sample collection and oral microbiota analysis is needed for more conclusive and clinically relevant comparisons in future research.