Anesthetics change the oral microbial composition of children and increase the abundance of the genus Haemophilus.

Abstract

Background: Oral microbiome homeostasis is important for children's health, and microbial community is affected by anesthetics. The application of anesthetics in children's oral therapy has become a relatively mature method. This study aims to investigate the effect of different anesthesia techniques on children's oral microbiota.

Methods: Sixty children who visited the Department of Stomatology of the Jiangxi Provincial Children's Hospital were recruited. Subjects who did not receive anesthesia during the surgery were divided into non-anesthesia (Noa) group. Other children who accepted anesthesia during the surgery were grouped into lidocaine group, sevoflurane group, and intravenous injection-inhalation (intra-inhalation) group. Subsequently, their saliva samples were collected for 16S rDNA sequencing.

Results: A total of 1,316 operational taxonomic units (OTUs) were identified in overall samples, and 75,275 reads per sample were obtained on average. There were 137 genera were shared among the Noa, lidocaine, sevoflurane, and intra-inhalation groups. The genera Neisseria, Prevotella-7, Streptococcus, and Veillonella had a higher abundance in the four groups. Compared to the Noa group, anesthetics increased the abundance of the genus Haemophilus in the anesthesia groups. Alpha and beta diversity analyses revealed significant differences in the comparisons of Noa vs. sevoflurane and Noa vs. intra-inhalation. In contrast, the difference between the lidocaine and the Noa groups was slight. Linear discriminant analysis effect size (LEfSe) analyses identified 52, 16, and 37 differential microbes in the Noa vs. sevoflurane, Noa vs. lidocaine, and Noa vs. intra-inhalation comparisons, respectively. Notably, Haemophilus genus was significantly enriched in the sevoflurane group compared to the Noa group. When comparing the Noa group with the other three anesthesia groups, between-group pathway differences were found in amino acid metabolism, energy metabolism, biofilm formation, cofactor and vitamin metabolism, and antibiotic synthesis.

Conclusions: This study elucidated oral microbiome characteristics in children under different anesthesia technology and found an enrichment of Haemophilus genus in the sevoflurane group compared to the Noa group. Our findings provide new insights into the effect of anesthetic on oral microbiota of children.