Hospital wastewater is a major “breeding” ground for various pathogens, antibiotic resistance bacteria (ARB) and antibiotic resistance genes (ARGs), and has generated continued environmental health concerns (Rizzo et al., 2013). The major reasons for the concerns are that the wastewater facilitated ARG-exchange events among bacteria and generation of multi-drug resistant (MDR) bacteria (Bondarczuk et al., 2016). However, similar concerns for dental waste water (DWW) have not been specifically investigated.

The DWW has some specific differences from that of hospital sewage. For example, certain oral bacteria (i.e., Pseudomonas. gingivalis) were associated with development of oral and gastrointestinal cancers (Ahn et al., 2012; Olsen and Yilmaz, 2019). DWW contains non-infectious toxic wastes that include acrylic resin scraps, metal alloys, porcelain, gypsum and dental amalgam, as well as abundant heavy metals, such as mercury, silver, tin, zinc, and copper which have toxic properties (Clarkson et al., 2003; Jones, 2004; Kao et al., 2004; Vandeven and McGinnis, 2004). Consequently, most investigations on health hazards from DWW have been focused onto amalgam and other metals (Al-Khatib and Darwish, 2004; Muhamedagic et al., 2009), and acrylic resin filling materials (Binner et al., 2022). However, investigations using holistic and more sophisticated technologies have not been reported yet.

Metals and biocides may co-select for antimicrobial resistance (AMR; Gelalcha et al., 2017; Pal et al., 2017). Metal contaminations have been reported to significantly influence the diversity, abundance and mobility potential of a broad spectrum of ARGs in urban soils (Song et al., 2017; Zhao et al., 2019). In addition, co-selections of antibiotic-and metal-resistance have been associated with arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn) (Pal et al., 2015; Song et al., 2017; Zhao et al., 2019). Another study showed that metal contamination in soil increased the potential for horizontal gene transfer (HGT) of ARGs via co-selection of ARGs and MGEs, thereby generating a pool of high-risk mobile ARGs (Martínez et al., 2015). With the presence of heavy metals in DWW as opposed to hospital waste water, DWW may involve novel mechanisms for ARGs evolution, HGT development and transmission of AMR. Unfortunately, there has not been a report on such investigation, especially using resistome and mobilome.

Standard handling and disposal of potentially infectious and toxic DWW has been implemented. Many dental clinics have chair-side primary and secondary filter traps which remove approximately 60% of large particles from discharges (Westman and Tuominen, 2000; Johnson and Pichay, 2001; Adegbembo et al., 2002). In addition, membrane bioreactors (MBR) in combination with biological degradation and membrane separation, have been used to remove infectious and non-infectious agents from effluents (Diehl and LaPara, 2010; Ju et al., 2016). To our knowledge, there has been no reports simultaneously identifying the bacterial communities, resistome and mobilome in DWW. Thus, the overall aim of our study was to investigate the abundance and components of bacterial communities, ARGs and MGEs in treated and untreated DWW from a single dental department. The investigation utilized advanced metagenomic and bioinformatic methods to provide in-depth characterizations of the DWW. Our investigation provides novel information on AMR evolution under high metal pressure and on environmental health concerns.

Studies on hospital waste waters have shown strong associations between their contaminants (ARG, MGE, and antibiotic resistant microbes) and environmental health problems (Su et al., 2017; Quintela-Baluja et al., 2019; Cai et al., 2021). DWW may contain the similar types of contaminants as found in hospital waste but also a substantial amount of heavy metals which may influence interactions among ARG, MGE and microbes. Since metals increase the potential for ARGs spread via co-selection of ARGs and MGEs, co-existence of the metals and ARGs would make the DWW to be a novel niche for studying AMR emergence and environmental health concerns. However, there have been very limited reports on environmental health hazards with DWW, especially with new technology such as resistome and mobilome in our investigation. By using a metagenomics approach, DWW samples from one major dental department were found to have resistome which included 1,208 types of ARGs belonging to 29 antibiotic types/subtypes. The most abundant ones were ARGs of multidrug resistance, followed by ARGs of Aminoglycoside, Cephalosporin, Fluoroquinolone, Tetracycline, Peptide, Cephamycin, Phenicol, Glycopeptide, Carbapenem, Diaminopyrimidine, Rifamycin, Macrolide, Penam, MLS, and Fosfomycin. Importantly, all of the mentioned resistance was to antibiotics which were commonly used in clinical practice in the hospital but were less frequently used in the dental department where the waste water samples were collected. Our results are intriguing as well as meaningful because DWW was thought to be rarely involved in the transmission of AMR. Furthermore, a wide variety of ARGs were unexpectedly found in DWW which might have been influenced by the abundant metals. These unique features need to be further investigation in order to better understand mechanisms and to develop more effective prevention strategies.

Microbiomes have been considered as an important driver for ARG disseminations in the environment (Baym et al., 2016; Jia et al., 2017; Chen et al., 2019; Yu et al., 2020). The source of ARGs in the DWW may come from oral microbiome. Indeed, our collected DWW samples included 1,514 types of bacteria, 37 types of fungi, 11 types of phages, 7 types of Archaea, and 5 types of viruses. Among them, bacteria were the majority while the most abundant phyla and genus were Proteobacteria (76.4%), and Pseudomonas (25.67%), particularly Pseudomonas putida, Pseudomonas sp. LTGT-11-2Z, and Pseudomonas aeruginosa. Importantly, they also belonged to the important pathogens found in dental clinic. A previous study revealed that composition of the microbial community in waste water was associated with 68.2% of the variations in ARGs (Zhang et al., 2016). Using the association data from our metagenomic analyses, network and binning analyses were conducted as shown in other reports (Guo et al., 2017; Liu et al., 2019; Sun et al., 2021). Our analyses revealed a complicated co-occurrence network which contained 88 nodes and 101 edges, and which involved 27 bacteria and 95 ARGs subtypes. Specifically, Pseudomonas putida, Pseudomonas aeruginosa, Chryseobacterium indologenes, and Sphingomonas laterariae were located in the central hubs of the network and involved with abundant ARGs referring to various antibiotics. Some of the ARBs which were associated with resistance to multiple drugs have been reported to contribute to increased morbidity and mortality among patients (Morrison and Zembower, 2020). Therefore, understanding existence of networks for ARGs and bacteria would provide valuable information in predicting novel ARB and in designing prevention protocols against emerging AMR (Chng et al., 2020).

Mobilome is defined as all detectable HGT elements within a given metagenomic dataset and these elements included plasmids, integrative conjugative elements (ICE), transposons, and insertional repeat sequences (Pal et al., 2015; Ju et al., 2019; Yun et al., 2021). In this study, mobilome of the DWW was composed of 93 MGE subtypes belonging to 8 MGE types. Among them, transposases were the most frequently detected MGEs. With our correlation analyses, most of ARGs showed significant correlations with total abundance of MGEs. The co-occurrence network consisted of 109 nodes and 175 edges. Among all MGEs, ISCrsp1, and tnpA.5/4/11 were located in the central hubs of the network and might serve as links to different ARG types. With the large number of ARGs connected to them, they took on the active role of ARG dissemination. Previous studies indicate that most co-occurring ARGs with metals also co-occurred with MGEs (Song et al., 2017; Zhao et al., 2019).

Heavy metals can promote resistance to antibiotics either via cross-resistance (a single genetic unit conferred resistant to both metals and antibiotics), co-resistance (both metal resistant genes (MRGs) and ARGs are associated with same MGEs), or co-regulation (both metal and antibiotic resistance shared their regulatory systems; Baker-Austin et al., 2006; Imran et al., 2019). Moreover, the relative MRGs and ARGs abundances would increase with increasing metals concentration (Hu et al., 2017). The metal-driven selection of AMR is markedly greater when both MRGs and ARGs are situated on the same MGEs (e.g., plasmids, transposons, and integrons; Di Cesare et al., 2016; Hu et al., 2017). For example, int1 has been closely associated with MRG czcA, coding for cobalt (Co), zinc (Zn), and cadmium (Cd) resistance, and beta-lactamase resistance (Stokes et al., 2006; Gillings et al., 2008), indicating that MRGs and ARGs may be transferred simultaneously to host bacteria via int1 in the HGT process (Gupta et al., 2022). Transformation is the main pathway of HGT, which can take place in more than 80 naturally competent bacterial species with distant phylogenetical backgrounds, even consisting of human pathogens (Thomas and Nielsen, 2005; Maeusli et al., 2020). Due to the prevalence of extracellular ARGs, antibiotics and naturally competent bacteria, the environmental transformation of ARGs is estimated to be quite frequent and is one of the predominant pathways to spread AMR (de Aldecoa et al., 2017). Ag, CuO and ZnO-based NPs/ions could promote the natural transformation of plasmids harboring ARGs (Zhang et al., 2022), and the promoting effect can occur at clinically relevant concentrations (Hernandez-Sierra et al., 2008; Mohler et al., 2018) or realistic concentrations within aquatic environments (Brunetti et al., 2015). On the other hand, heavy metals pollution has altered bacterial diversity and abundance, as the bacterial population is sensitive to heavy metals (Chen et al., 2018), and the long-term presence of high concentrations of metals in polluted water may increase heavy metal resistance in a variety of bacteria (Gupta et al., 2022). These observations suggest an underlying metal-driven co-selection process which was linked with existence of cross-resistance (Li et al., 2017; Zhao et al., 2019). Furthermore, MGEs are actively involved in HGT of ARGs in neighboring microbial communities (Gupta et al., 2018). Consequently, when DWW are released into the environment, it becomes very difficult to efficiently eliminate the generation of ARB (Rakita et al., 2020).

In our study, the main limitation is that metal concentrations were not determined due to our limitations of analytical techniques. Theoretically, a large amount of heavy metals discharged from clinical practice in every day will inevitably lead to a large amount of heavy metals in DWW. On the other hand, previous reports indicate the presence of high levels of Cu, Zn, Hg and MeHg in DWW (Rani et al., 2015). Thus, co-selection and cross-resistance would occur in DWW. If ARGs and MRG is found on the same MGEs, and this physical linkage results in co-resistance. Cross-resistance is another co-selection mechanism which occurred when single genes encoded resistance to both antibiotics and metals (Li et al., 2017; Zhao et al., 2019). Better understanding of how metals influence formation of ARGs and MGEs would provide insights into novel mechanisms of HGT and emergence of ARB in the future.

The generation and mobility of clinically relevant ARGs in waste waters post significant risk to human health (Carvalho and Santos, 2016; Liu et al., 2018b; Slizovskiy et al., 2020). Our data clearly show the abundance of ARGs and MGEs in the DWW, therefore more effective treatment of the waste water is of great importance. Unfortunately, few existing processes have been designed to remove ARGs, and our data as well as others indicate that such processes were not highly effective (Mao et al., 2015; Bengtsson-Palme et al., 2016; Di Cesare et al., 2016; Pazda et al., 2019; Vinzelj et al., 2020; Li et al., 2022). The treatment process in our dental department utilized ozone, which reacts directly or indirectly via a hydroxyl radical mechanism to reduce organic and inorganic materials to become more biodegradable, and which efficiently inactivate a wide range of microorganisms (Tripathi and Tripathi, 2011). Our results show that only a few bacteria with clearance rate higher than 30% were observed. On the contrary, some others were increased. Considering that metagenomics only detects bacterial DNA, the data do not represent activity and integrity of bacteria. Thus, clearance or abundance of bacteria should be reconfirmed via bacterial isolates.

As to resistome and mobilome, our data show that ozone treatment had no obvious effects in changing the abundance of resistome and mobilome, although a previous study revealed that antibiotic-resistant hosts and resistant genes were significantly inactivated by ozone treatments (Pei et al., 2016), as well as a significant portion of only MLS and tetracycline genes (Raza et al., 2022). On the other hand, beta lactam ARGs were increased by UV-, chlorine-, and ozone-based treatment strategies (Guo et al., 2013; Alexander et al., 2016; Ferro et al., 2017; Liu et al., 2018a). These different observations are likely due to the use of different experimental designs, sample sizes and technologies. More systematic studies are needed to identify efficacy of waste water treatment protocols.

ARGs and MGEs have been listed as serious and emerging environmental pollutants and health problems from hospital waste waters (Gillings et al., 2008; Xu et al., 2016; Chen et al., 2019). Our data strengthened the addition of DWW to the list of concerns. Our study reveals that DWW harbored a significant and diversity of microbes, ARGs, and MGEs, providing a persistent selection pressure (in the presence of heavy metals) and possibly resulting in the occurrence or emergence of novel antimicrobial determinants. Our observations provide evidence which underscore the need for improved disinfection methods, and for monitoring the waste prior to disposal. Effective effort would lead to reducing the spread of drug resistant bacteria into hospitals and communities.

The proposal was approved by the institutional review board of the First Affiliated Hospital of Shantou University Medical College.

The dataset presented in this study are deposited and can be found in an online repository. The name of the repository and accession number(s) can be found below: NCBI repository - https://www.ncbi.nlm.nih.gov/, PRJNA869027.

The studies involving human participants were reviewed and approved by First Affiliated Hospital of Shantou University Medical College. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

XJ and WG contributed equally to this manuscript. YX and WG carried out the sample collection, experimental studies, and drafted the manuscript. FYa, QX, LC, FYu, and PY participated in the innovative design of the study. XL, MZ, YY, XG, and MW, performed the statistical analysis. QZ and XJ conceived the study, participated in its design and coordination, and helped to revise the manuscript. All authors contributed to the article and approved the submitted version.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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