Presence and Levels of Antibiotic Resistance Genes in Saliva from Dental Students in Tromsø. Investigation of cfxA and erm(B) in Saliva Samples - Christensen, Tone Mohini; Sørensen, Torunn Kvalvik (UiT Norges arktiske universitet, 2016)
Abstract Antibiotic resistance is a global health problem that threatens humankind. Extensive use of antibiotics has led to an increase in the prevalence of resistant bacterial strains. Aims: The aim of this study is to investigate the prevalence and levels of antimicrobial resistance genes, i.e. cfxA and erm(B), in saliva obtained from dental students, and to assess the relationship between the prevalence of these genes and commitment to hygiene procedures and habits by dental students in the clinics. Materials and method: A questionnaire was used to report the demographic data, attitudes and hygiene practices of 1st- and 5th-year dental students. Together with the questionnaire whole saliva samples were collected from the study subjects. DNA was extracted from the samples followed by amplification and quantification of the resistance genes using droplet digital PCR (ddPCR). Results: We detected the resistance genes in almost all the participants, with cfxA detected in 100% of the samples and erm(B) detected in 94%. However, our result suggested that there is no significant difference in level of resistance genes between the 1st- and 5th-year dental students. On the other hand, significant difference was found between participant who had a history of taking antibiotics in the past and levels of erm(B) resistance gene in their saliva. Conclusion: It seems that the use of saliva samples as a biological sample companied with the sensitivity of ddPCR could be used as a diagnostic tool to reveal the presence and levels of resistance genes in a given individual. It also seems that the high levels of cfxA compared to that of erm(B) reflect the use of β-lactam antibiotics in the society. What we still do not know is the clinical aspect regarding the resistance gene. At what level of a particular resistance gene one could predict a failure of an antibiotic treatment aiming to affect a bacteria with that gene.