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Official websites use. Share sensitive information only on official, secure websites. Author order was determined by contributions toward study design and editing. This is an open-access article distributed under the terms of the Creative Commons Attribution 4. Drug addiction can powerfully and chronically damage human health. Detoxification contributes to health recovery of the body. It is well established that drug abuse is associated with poor oral health in terms of dental caries and periodontal diseases. We supposed that drug addiction and detoxification might have significant effects on the oral microbiota. The oral microbial compositions differed between non-users, current and former drug users. Lower alpha diversities were observed in current drug users, with no significant differences between non-users and former drug users. Heroin and METH addiction can cause consistent variations in several specific phyla, such as the enrichment of Acidobacteria and depletion of Proteobacteria and Tenericutes. Current drug users had significantly lower relative abundances of Neisseria subflava and Haemophilus parainfluenzae compared to non-users and former drug users. The result of random forest prediction model suggested that the oral microbiota has a powerful classification potential for distinguishing current drug users from non-users and former drug users. A cooccurrence network analysis showed that current drug users had more complex oral microbial networks and lower functional modularity. Overall, our study suggested that drug addiction may damage the balance of the oral microbiota. These results may have benefits for further understanding the effects of addiction-related oral microbiota on the health of drug users and promoting the microbiota to serve as a potential tool for accurate forensic identification. The evidence indicates that drug abuse can cause poor oral health. In the current study, we observed that drug addiction caused oral microbial dysbiosis. Detoxication have positive effects on the recovery of oral microbial community structures to some extent. Understanding the effects of drug addiction and detoxification on oral microbial communities will promote a more rational approach for recovering the oral function and health of drug users. Furthermore, specific microbial species might be considered biomarkers that could provide information regarding drug abuse status for saliva left at crime scenes. To the best of our knowledge, this is the first report on the role of the oral microbiota in drug addiction and detoxification. Our findings give new clues to understand the association between drug addiction and oral health. The human oral cavity is colonized by over different bacterial species and other microorganisms 1. These microbes are involved in diverse functions and play a crucial role in human health 2. Previous studies have shown that oral microbiome dysbiosis is not only related to oral diseases 3 — 5 but is also potentially related to systemic diseases 6 — 9. Hence, the oral microbiome has been considered to provide essential information for the understanding of oral health and systemic diseases. The evidence indicates that cigarette smoking 10 and alcohol consumption 11 could alter the oral microbiota and potentially lead to increased colonization by pathogenic bacteria that are associated with smoking-related and alcohol-related diseases, respectively. Drug addiction can powerfully and chronically weaken human health In particular, drug abuse can affect adaptive immunity The characteristics of the adaptive immune system are important determinants for interactions between the microbiome and hosts On the other hand, drug abuse can cause poor oral health in terms of dental caries and periodontal diseases It has been well established that oral microbial community structures vary between healthy host populations and populations with dental caries or periodontal disease 3 — 5. Furthermore, drug abuse can change the environment of the saliva, such as the pH levels and salivary flow rates 16 and in general, drug abusers have poor lifestyle habits and oral cleanliness Based on the findings, we hypothesized that drug addiction could change the oral microbial community structure. Detoxification is the process of disengaging a person from drug abuse in a safe and effective manner and involves the recovery of bodily health If the hypothesis that drug addiction could change the oral microbial community structure is true, detoxification might have positive effects on the recovery of the oral microbial community structure to some extent. There is another possibility that detoxification could increase the differences in oral microbial community structures between drug users and non-users. This possibility may be attributed to the high sugar consumption during the process of detoxification, especially for oral methadone solutions that are used to manage heroin withdrawal However, these are merely our speculations, and the effects of drug addiction and detoxification on the oral microbiota are poorly known. Understanding the effects of drug addiction and detoxification on oral microbial communities will promote a more rational approach for recovering the oral function of drug users. On the other hand, specific microbial species might be considered biomarkers that could provide information regarding drug abuse status and for saliva left at crime scenes. This is helpful for finding investigation clues, shrinking investigation scopes, clearing people of criminal suspicion or identifying criminal suspects. Heroin and methamphetamine METH are commonly abused drugs that pose a significant economic burden 13 , To test the hypothesis, we assessed the microbial community compositions and taxon abundances of oral wash samples, including those obtained from heroin and METH drug user, before and after detoxification by the use of bacterial 16S rRNA gene sequencing Fig. To the best of our knowledge, we present the first available evidence on the effects of these two drugs on the oral microbial ecology. Graphical abstract. Drug addiction may change the human oral microbial composition and damage the balance of the oral health microbiota. A total of 38,, high-quality above Q20 sequences were obtained. Each sample contained 77, sequences. Then, 1, OTUs were identified as bacteria from our salivary samples. The standard sampling size calculations Fig. The alpha diversities of the oral bacterial communities decreased caused by drug addiction and increased after drug detoxification Fig. Specifically, all three alpha-diversity indices of current heroin users were significantly lower than those of non-users and former heroin users. All three indices increased significantly after detoxification for METH users. The alpha diversities of former drug users were very close to those of non-users. In addition, heroin had a greater effect on oral microbial alpha diversities compared to METH, all three alpha-diversity indices were significantly higher in current METH user than in current heroin users. After detoxification, only the richness was still significantly higher in METH users than in heroin users. The pairwise tests were also performed for current and former drug users and obtained similar results with those of all samples Fig. The statistical differences were analyzed using Wilcoxon tests. A—C were plotted based on the alpha diversities of all samples. Overall, drug addiction decreased the alpha diversities of the oral bacterial communities, and detoxification increased those of drug users. The statistical differences were analyzed using pairwise Wilcoxon tests. The results of pairwise statistical tests were consistent with those of all samples. The tests only including pairwise data also showed that current and former drug users had significant differences in oral microbial community structure Table S3. Furthermore, the microbial communities of former drug users were more similar to those of non-users than to those of current drug users Fig. S3, Tables S1 and S2. We further compared the within-group distances for all addiction categories, and the results showed that the oral microbial communities of current drug users were more heterogeneous than those of non-users and former drug users Fig. The results show that the distribution of current drug users separated from that of non-users, former drug users located between current drug users and non-users. A comparison of the between A and B and within C and D group distances A and C for the Bray—Curtis distances, B and D for the Weighted UniFrac distances for all addiction categories indicated that non-users and former drug users were more alike. The microbial communities of former drug users are more similar to those of non-users than to those of current drug users A and B. The oral microbial communities of current drug users are more heterogeneous than those of non-users and former drug users C and D. Additionally, the age of drug users had a significant influence on the oral microbial communities of former drug users but had no significant influence on those of current drug users Table S4. The frequency of drug addiction had little influence on the oral microbial communities of drug users Table S5. At the phylum level Fig. S4 , Bacteroidetes was the dominant taxon, which was followed by Firmicutes and Proteobacteria. Acidobacteria, Actinobacteria, Bacteroidetes, and Firmicutes had higher relative abundances, while Elusimicrobia, Epsilonbacteraeota, Fusobacteria, Patescibacteria, Proteobacteria, and Tenericutes had relatively lower abundances in current heroin users than in non-users. These taxa of former heroin users returned to higher relative abundances that were similar to those of non-users. In addition, lower relative abundances of Acidobacteria, Patescibacteria, Planctomycetes, and Synergistetes, as well as higher relative abundances of Proteobacteria and Tenericutes, were observed in non-users and in former METH users than in current METH users. The species whose absolute differences in relative abundances were significantly greater than 0. There were six and seven species with significantly lower relative abundances in current heroin users compared to non-users and former heroin users, respectively. Among these decreased species, Neisseria subflava , Fusobacterium periodonticum , and Haemophilus parainfluenzae were shared in the comparisons. There were three species with significantly higher relative abundances in current heroin users compared to non-users and former heroin users, respectively. Veillonella atypica and Prevotella histicola were shared in the two comparisons Fig. The decreases of N. Only V. Current drug users had significantly lower relative abundances of Neisseria subflava and Haemophilus parainfluenzae comparing to non-users and former drug users, no matter for heroin users A and C or METH users B and D. We then performed a differential OTU abundance analysis based on the raw abundances by fitting a negative binomial generalized linear model Fig. For heroin users, OTUs were significantly enriched, and OTUs were significantly depleted in current users compared to non-users, of these enriched OTUs significantly decreased, and of these depleted OTUs significantly increased after detoxification Fig. These results suggested that a significant percentage of changed OTUs due to addiction can be recovered by drug detoxification. In the ternary plots, each circle depicts one individual OTU. The circle sizes reflect the relative abundances. The results of random forest model showed that 22 Fig. S6A , 45 Fig. S7A and 26 Fig. Meanwhile, 31 Fig. S9A , Fig. S10A and 64 Fig. These results suggested that the oral microbial communities could provide a powerful diagnostic potential for distinguishing never, former and current addicting statuses. ROC curves depicting the classification performance of the drug A for heroin and B for METH addiction categories by using the relative abundances of species based on random forest models. The random forest classifiers provide extremely high prediction accuracies AUC values range from 0. Among the selected optimal markers, besides N. Most species had lower relative abundances in current drug users compared to non-users or former drug users at the top 20 important biomarker taxa. All of the taxa had higher relative abundances in non-users than in current heroin users Fig. S6 , and only 2 taxa Brevundimonas diminuta and Peptostreptococcus stomatis had lower relative abundances in non-users than in current METH users among the top 20 important biomarkers Fig. A large portion of these depleted taxa caused by drug addiction were also observed in the comparisons between former drug users and current drug users Fig. S7 and S Furthermore, B. Overall, more complex cooccurrence networks of the oral microbial communities were observed in current drug users than those in non-user and former drug users Fig. The oral cavities of current heroin users had the most complex microbial networks with an average degree of The remaining networks had similar scales and complexities. The node colors indicate different phyla. The lines connecting the nodes edges represent positive gray or negative red cooccurrence relationships. The oral microbial networks of current drug users have a higher complexity and more negative links compared to those of non-users or former drug users. Furthermore, there was a larger proportion of positive correlations in the salivary networks of non-users and former drug users than in those of current drug users. The proportions of positive correlations were Correspondingly, the network of current heroin users had the highest proportion of negative correlations Furthermore, the networks of non-users 0. In fact, we did observe more ecological modules e. These results suggested that drug addiction could decrease the modularity of the oral microbial community, especially for heroin addiction. In this large-scale study, we observed that the oral bacterial community compositions of drug users differed substantially from those of non-users. Regarding drug administration via nasal inhalation, smoking and direct smearing on the oral mucosa 21 , drugs could have direct contact and cytotoxic effects on the oral microbial microbes. On the other hand, heroin and METH could change the oral environment, such as causing xerostomia and decreasing oral pH levels 16 , In addition, drug abuse may impair host immunity 23 , The immune system regulates relationships between the microbiota and the host, the presence of an immune system disorder can shift the microbiota by disrupting mutual or commensal relationships These factors might result in changes in the bacterial community compositions and reductions in the alpha diversities in the oral cavity. The oral microbial communities of non-users and former drug users were relatively conserved compared to current drug users. Previous studies have also shown that healthy individuals had more similar oral bacterial communities than cigarette smokers 26 and patients with dental caries 3. The damage to the oral microbial community caused by drug abuse was not permanent. The oral microbiota of drug users could partially recover. It is well established that the oral cavity can provide highly heterogeneous ecological niches for microbes This property could provide tolerance and resilience to many adverse conditions The study of Wu et al. However, there were still significant differences between non-users and former drug users in their oral microbial community structures. This result may imply some lingering effects of drug addiction. The descriptions in previous studies regarding the effects of heroin and METH on oral health were similar, such as xerostomia and decreases in oral pH levels This may result in consistent changes in the microbial community to some extent. However, heroin had a greater effect on the oral microbial abundances and community structures. There are still differences in the oral characteristics between those two drug users. Heroin is an opiate drug, and METH is a stimulant The direct toxicities of the two drugs to the oral-specific microbial taxa may be different. These influencing mechanisms might result in distinct microbial community structures. The ages of drug user had no significant effects on the oral microbial communities before detoxication but had a significant effect after detoxication. These findings indicated that the period of drug abuse tends to influence the resilience of the oral microbial community. A previous study observed reductions in Proteobacteria and increases in the relative abundances of Actinobacteria and Firmicutes in current cigarettes and opium smokers compared with nonsmokers 10 , Cigarette and cannabis smoking could decrease oral aerobes such as Neisseria and Haemophilus Similar results were also observed in current heroin users compared to non-users and former heroin users. Heroin administration causes statistically significant reductions in the oxygen saturation rate METH neurotoxicity may also be linked to changes in O 2 levels This may imply that the poor oral health status caused by different habits could exhibit similar changes in the abundances of some specific taxa. The microbiota of population with more teeth with dental caries showed significantly lower relative abundances of N. These decreases were also observed in the comparisons of current drug users versus non-users or former drug users. Additionally, caries-associated microbial taxa such as P. These oral microbial characteristics of current drug users might increase risk of dental caries. However, the decreases of S. Streptococcus , especially for S. This suggested that the pathogenesis of dental caries among drug users might be distinguished from non-users. In our study, most of non-users have dental caries. Further study needs to include more participants with good oral health to test the hypothesis. The study of Lee et al. Different oral sites and administration routes might be reasons to explain the opposite results. It is possible that the decreases are due to specific drug tolerance. Our study is only an observational investigation, those changed taxa whether are directly affected by drug need further exploration. The oral microbiota has powerful classification potential for distinguishing current drug users from non-users and former drug users. The recent study of Kosciolek et al. Large numbers of crime cases are committed under the influence of drug abuse The saliva strains found in crime scenes are important forensic materials Our findings might provide information on the drug abuse status of individuals who left saliva in crime scene. The ecological interactions among host-associated microbial inhabitants could influence host health and disease and would correspondingly change with the host health and disease status More complex relationships were observed in the oral microbial networks of current drug users, especially the lower alpha-diversities, which suggested that drug abuse increased the interactions among microbial communities. In general, enriched resources decrease the frequency of microbial-microbial interactions and allow more microbes to maintain free-living patterns The primary sources of nutrition for salivary microbial growth are not obtained from the food ingested by the host but consist of glycoproteins that are obtained from the gingival crevicular fluid and saliva Therefore, the nutritional status of the host could influence the oral microbial community. The higher sugar consumption of drug users could not increase salivary nutrition since the sugar in food is quickly removed through the actions of swallowing and salivary flow Drug abuse could interfere with human nutrient absorption The poor nutritional status of drug users increases the interactions of the salivary microbial community. On the other hand, anaerobic metabolism with lower energy yields requires the concerted activities of various species to perform chemical transformations Therefore, the oral microbial communities in the oral anaerobic environments of drug users might exhibit higher densities of interactions. In ecological cooccurrence networks, positive correlations generally indicate synergistic such as cooperative or syntrophic relationships, while negative correlations indicate antagonistic such as competitive or predation relationships The negative correlations increased by an even greater proportion in current drug users compared to non-users and former drug users. Greater nutrient limitations could increase competition Violle et al. In cooccurrence networks, modularity contains some highly connected microbes that cluster into a group In general, the nodes in various modules perform different functions The networks of current drug users had the lowest modularity values and the fewest highly connected modules, which suggest that drug abuse destroyed the healthy oral microbial ecological functions and that detoxication might contribute to the functional recovery of the oral microbial community. In summary, we investigated the effects of drug addiction and detoxification on the oral microbial community. We observed that drug addiction may decrease the oral microbial alpha diversity and damage the balance of the oral microbial ecology. Detoxication may have positive effects on the recovery of oral microbial community structures to some extent. The strengths of this study include a sufficiently large sample size and the control of potential confounders. We collected as many samples of current drug users as possible. In our study, participants could withdraw from the study at any time if they wish. So, we did not know if we can get samples of all these participants after detoxification 3 months. This resulted in imbalanced sampling sizes for different groups. However, we performed pairwise tests to deal with potentially bias caused by imbalanced grouping and obtained similar results with those of all samples. Additionally, synthetic train data were generated to deal with overfitting problem of imbalanced binary classification in random forest model. In addition, the current study still has some limitations. First of all, the small size of female sample was a limitation of our study, especially for former drug users. Second, all participants are cigarette smokers, most of them have oral diseases. However, we failed to get the more detailed data such as prevalence rate of decayed and filled teeth and the mean decayed and filled teeth score. Future studies should cover a larger of samples, including more females and oral health populations. And more detailed oral health status was essential to explore the relationships between drug addicting, oral health status and oral microbiota. Finally, the current study is only an observational investigation and is not sufficient to determine the functional and gene contents of bacteria that are altered by drug addiction and detoxification. Further studies should explore the impacts of drug addiction and detoxification on the oral microbiome by using metagenomic data and whether addiction-related oral microbiomes mediate the health of individuals with drug addiction. The participants were obtained from Chongqing. All participants gave written informed consent to participation in the study. Oral wash samples were collected from heroin users and METH users before detoxification. We also collected oral wash samples from drug users after detoxification 71 heroin users and 79 METH users. Among them, there were 55 heroin users and 61 METH users who had samples, including both before and after detoxification Fig. The heroin formulation in our study is powder. The main routes of heroin administration were smoking and injection. All injecting drug users were also smoking ones. And the route of METH in our study were smoking. In addition, 50 non-users were recruited from the local region for use as controls. We recorded the age, sex, height, weight, BMI, cigarette smoking status, and oral health status of the participants Table 1. All participants in our study are cigarette smokers. Oral health status, including statuses of dental caries and periodontal disease, were directly examined by the dentists at the sampling site. The status of dental caries was categorized as having caries or not. And periodontal status was classified as suspected of having periodontitis or not. Parameters, including age, sex, height, weight, BMI, smoking status, oral health status, addicting age and frequency of different groups a. BMI, body mass index. Frequency of cigarette smoking and frequency of drug addiction are the data of recent six mouths. The participants were asked to collect saliva samples using a sterile specimen tube by the simple drooling method. We excluded those individuals who reported antibiotic or prescribed probiotic use in the previous 3 months. Negative controls consisting of sterile water were included during DNA extraction and sequencing. Following these steps, the OTU sequences were obtained. The data analyses were conducted using the R software platform. The standard sampling sizes were estimated based on Cohen D values of alpha diversity phylogenetic diversity, PD as the method of Casals-Pascual et al. The beta diversities were determined by the Bray—Curtis and weighted UniFrac distances. The significant differences in taxa-relative abundances, alpha diversities and beta diversities among various groups were tested by using the Wilcoxon test with P values adjusted according to the Benjamini-Hochberg method. A permutational multivariate analyses of variance PERMANOVA based on the Bray—Curtis and weighted UniFrac distances was used to determine the differences in bacterial compositions across the drug addiction status categories and were adjusted for age, sex, height, weight, BMI, cigarette smoking status and oral health status. The ROSE package was employed to generate synthetic train data for dealing with overfitting problem of imbalanced binary classification according to a bootstrapping approach The species were ranked in order of their feature importance in the random forest model by using iterations. Five repeats of fold cross-validation were performed to select the optimal classifiers. Then, random forest models were established based on the selected optimal classifiers. ROC curves were obtained for evaluations of the random forest models based on the selected optimal markers Network construction was accomplished with the Cytoscape plugin CoNet 68 by using an ensemble-based approach that combined two measures of correlation e. Then, we requested the top- and bottom-ranking links for each statistical measure. The statistical significances were calculated by obtaining the method- and edge-specific permutation and bootstrap score distributions using iterations for each distribution. This work was supported by the National Natural Science Foundation of China , and Jun Zhang, W. Jun Zhang analyzed the data and wrote the manuscript. All authors contributed to the article and approved the submitted version. This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplemental material. Download spectrum. As a library, NLM provides access to scientific literature. Microbiol Spectr. 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