Variations in the oral microbiome and metabolome of methamphetamine users.

Drug addiction can seriously damage human physical and mental health, while detoxification is a long and difficult process. Although studies have reported changes in the oral microbiome of methamphetamine (METH) users, the role that the microbiome plays in the process of drug addiction is still unknown. This study aims to explore the function of the microbiome based on analysis of the variations in the oral microbiome and metabolome of METH users. We performed the 16S rRNA sequencing analysis based on the oral saliva samples collected from 278 METH users and 105 healthy controls (CTL). In addition, the untargeted metabolomic profiling was conducted based on 220 samples. Compared to the CTL group, alpha diversity was reduced in the group of METH users and the relative abundances of Peptostreptococcus and Gemella were significantly increased, while the relative abundances of Campylobacter and Aggregatibacter were significantly decreased. Variations were also detected in oral metabolic pathways, including enhanced tryptophan metabolism, lysine biosynthesis, purine metabolism, and steroid biosynthesis. Conversely, the metabolic pathways of porphyrin metabolism, glutathione metabolism, and pentose phosphate were significantly reduced. It was speculated that four key microbial taxa, i.e., Peptostreptococcus , Gemella , Campylobacter , and Aggregatibacter , could be involved in the toxicity and addiction mechanisms of METH by affecting the above metabolic pathways. It was found that with the increase of drug use years, the content of tryptamine associated with neuropsychiatric disorders was gradually increased. Our study provides novel insights into exploring the toxic damage and addiction mechanisms underlying the METH addiction.IMPORTANCEIt was found that with the increase of drug use years, the content of tryptamine associated with neuropsychiatric disorders gradually increased. The prediction models based on oral microbiome and metabolome could effectively predict the methamphetamine (METH) smoking. Our study provides novel insights into the exploration of the molecular mechanisms regulating the toxic damage and addiction of METH as well as new ideas for early prevention and treatment strategies of METH addiction.