TY - JOUR
AU - Imbert, Christine
AB - Chemical disinfectants are widely advocated to reduce the microbial contamination in dental unit waterlines (DUWL). However, until now their efficacy has been poorly examined after long-term application. In this study, through quantitative PCR and high-throughput sequencing, both bacterial and fungal communities were profiled from 8- to 12-year-old DUWL treated with disinfectants commonly used by European dentists. Water was collected from the tap water supplying units to the output exposure point of the turbine handpiece following a stagnation period and dental care activity. Results showed that (i) the unit itself is the principal source of microbial contamination and (ii) water stagnation, DU maintenance practices and quality of water supplying DU appeared as parameters driving the water quality. Despite disinfecting treatment combined to flushing process, the microbial contamination remained relevant in the studied output water, in association with a high bacterial and fungal diversity. The occurrence of potentially pathogenic microorganisms in these treated DUWL demonstrated a potential infectious risk for both patients and dental staff. A disinfectant shock before a prolonged stagnation period could limit the microbial proliferation inside DUWL. Necessity to proceed to regular water quality control of DUWL was highlighted. dental unit waterlines (DUWL), disinfection, Oxygenal 6©, Calbenium©, pyrosequencing, pathogens INTRODUCTION Dental unit waterlines (DUWL) provide an environment conducive to microbial attachment and biofilm formation (Walker et al.2000; Szymańska 2005b; Szymańska, Sitkowska and Dutkiewicz 2008; Puttaiah et al.2012). DUWL are predominantly colonized by environmental microorganisms including bacteria, fungi and protozoa. However, some microorganisms commonly found in the oral cavity, such as oral streptococci, or on skin, such as Staphylococcus aureus, have been also identified in DUWL (Petti and Tarsitani 2006; Petti et al.2013; Porteous et al.2014; Costa et al.2015). This suggests various origins from microbial contamination: microorganisms can be provided by the water supplying the dental chair unit, or through the suck back of biological fluids from oral cavity of patients resulting of a malfunction of antiretraction devices; finally, the continuous biofilm detachment or fragmentation also participates in this contamination (Pankhurst 2003; Wirthlin, Marshall and Rowland 2003; Coleman et al.2009; O'Donnell et al.2011). Therefore, many studies are focused on the microbial contamination of DUWL (Szymańska 2005a,b; Szymańska, Sitkowska and Dutkiewicz 2008; Kumar et al.2010; Arvand and Hack 2013; Petti et al.2013; Costa et al.2015). Infections associated with this contamination are rarely reported (Martin 1987; Ricci et al.2012) maybe because of the difficulty to prove that the exposure to contaminated DUWL is at the origin of the infection or maybe because of the usually limited clinical significance of such infections that do not result in case reports. Thus, infections related to contaminated dental output water may be more frequent than the number of corresponding case reports. In fact, both patients and dental staff are regularly exposed to this infectious risk due to inhalation of aerosols produced during dental cares. In addition, dental unit water (DUW) may be ingested or may contaminate surgical wounds. Moreover, the quality of DUW is of importance since vulnerable patients (such as elderly, diabetics or immunocompromised patients) are frequent. The assessment of risks related to DUW is taken into account in guidelines from governmental agencies such as the American Dental Association (ADA) and/or the Center for Disease Control and Prevention, and the current recommendation is that the dental output water as water delivered to dental unit (DU) be kept at or below existing standards for potable drinking water, i.e. with aerobic heterotrophic microbial density inferior to 500 CFU per mL (colony-forming units per millilitre) (American Dental Association 2012; Coleman et al.2014). Unexpectedly, in France as in most European countries, no standard defines the microbial quality of the dental output water delivered to patients. Some non-chemical methods are recommended to reduce microbial contamination in DUWL output water such as the use of microbial filters and/or antiretraction valves, the achievement of regular flushing of DUWL or the sterilization of handpieces (Direction Générale de la Santé 2006; O'Donnell et al.2011; Dallolio et al.2014; Smith and Smith 2014). In addition, an efficient way to reduce microbial contamination and control biofilms in DUWL is the use of chemical treatments, especially based on hydrogen peroxide and silver ions, chlorine dioxide, chlorhexidine, peracetic acid or citric acid (Schel et al.2006; Szymańska 2006). These agents can be used intermittently (e.g. daily or once to twice weekly) or continuously in DUWL supply water (O'Donnell et al.2011). Even if a number of studies have evaluated the efficacy of disinfectant agents to control the microbiological water quality inside DUWL, only a few were performed in real practice conditions after long-term application. The aim of this study was to investigate both bacterial and fungal communities in DUWL treated with a disinfectant in real conditions, in actual daily working DUs and according to the flow from the water supply (incoming water) to the outer exposure point (output water). This study focused on DUWL subjected to Calbenium© or Oxygenal 6©, two disinfectants commonly used by European dentists, for which no or a limited number of studies were reported (Walker et al.2003; Schel et al.2006; Szymańska 2006). METHODS DUs and disinfectants Three 8- to 12-year-old DUs (named Unit 1 to 3) in operation in Poitiers (France) used daily for dental care to patients were investigated. The tubing was never changed in the DUs displayed in this study. All the DUWL were supplied from the municipal water system of Poitiers, France (Supporting Information, Table SA) and subjected to flushing at the start of each day to reduce microbial accumulation subsequently to overnight stagnation. In addition, as presented in the Table 1, DUWL of Units 1 and 2 were continuously treated with 2% of Calbenium (Airel-Quetin, Champigny-sur-Marne, France) and DUWL of Unit 3 were continuously treated with 0.3% of Oxygenal 6 (KaVo, Biberach, Germany). Importantly, for Unit 3, an additional treatment was implemented each week (on Friday) before the long water stagnation period consequently to the inactivity of the weekend. The procedure consisted of a cycle of 45 min with Oxygenal 6 at 3% (v/v) circulated inside DUWL. Calbenium is a complex mixture based on ethylene diamine tetreacetic acid, benzalkonium chloride, sodium tosylchloramide, allantoin, aspartam, sorbitol and spearmint or lemon aroma, whereas Oxygenal 6 is composed of hydrogen peroxide and silver ions. Table 1. Description of the DUs.   Origin  Age (years)  IW treatment  OW treatment  Concentration  Unit 1  Public clinic  12  Softener  Calbenium  Continuous 2.0% v/v  Unit 2  Public clinic  8  None  Calbenium  Continuous 2.0% v/v  Unit 3  Hospital  12  None  Oxygenal 6  Continuous 0.3% v/v + each week            (Friday) for 45 min 3.0% v/v    Origin  Age (years)  IW treatment  OW treatment  Concentration  Unit 1  Public clinic  12  Softener  Calbenium  Continuous 2.0% v/v  Unit 2  Public clinic  8  None  Calbenium  Continuous 2.0% v/v  Unit 3  Hospital  12  None  Oxygenal 6  Continuous 0.3% v/v + each week            (Friday) for 45 min 3.0% v/v  View Large Table 1. Description of the DUs.   Origin  Age (years)  IW treatment  OW treatment  Concentration  Unit 1  Public clinic  12  Softener  Calbenium  Continuous 2.0% v/v  Unit 2  Public clinic  8  None  Calbenium  Continuous 2.0% v/v  Unit 3  Hospital  12  None  Oxygenal 6  Continuous 0.3% v/v + each week            (Friday) for 45 min 3.0% v/v    Origin  Age (years)  IW treatment  OW treatment  Concentration  Unit 1  Public clinic  12  Softener  Calbenium  Continuous 2.0% v/v  Unit 2  Public clinic  8  None  Calbenium  Continuous 2.0% v/v  Unit 3  Hospital  12  None  Oxygenal 6  Continuous 0.3% v/v + each week            (Friday) for 45 min 3.0% v/v  View Large Water sampling DUW samples (1 L) were collected at two different time periods in routine dental practices from (i) tap water upstream from the unit (here named incoming water or IW); (ii) turbine handpiece output water after a 48-h stagnation period (after the weekend), on Monday morning and before the beginning of the working day (named output water after stagnation or OWS); and (iii) turbine handpiece output water immediately after dental care of the last patient of the sampling day (named output water after activity or OWA). In order to neutralize the residual disinfectant, water samples were stored in sterile bottles with 3 mL of sodium thiosulfate (18 g L−1) at 4°C for no longer than 24 h before analysis. During sampling, care measures were taken to ensure that the microorganisms did not originate from the sampler. Total aerobic and aero-tolerant cultivable microbial biomass in DUW Each DUW sample was analyzed by direct plate spread in duplicate using a WASP 2 spiral plater (Biomerieux, Marcy l'Etoile, France) on R2A (Difco, BD, Le Pont de Claix, France), medium specifically recommended in standard methods for heterotrophic plate counts of treated potable water (Reasoner and Geldreich 1985). The number of CFU was counted 7 days after plate incubation under aerobic conditions at 28°C, as recommended by the manufacturer. Total water DNA extraction DNA was directly extracted from the DUWL samples filtered over a sterile 0.22-μm polycarbonate membrane (Sartorius, Dourdan, France) under laminar flow hood, as described by Costa et al. (2015). DNA extraction from water guaranteed DNA and RNA free filtered on polycarbonate membrane in the same conditions as for DUW samples was performed as negative control. DNA concentrations of extracts were quantified in duplicate using SYBR Green I dye (Invitrogen, Villebon-sur-Yvette, France) and a standard curve of HindIII-digested λ DNA fragments (Promega, Charbonnières-les-Bains, France) on a LightCycler 480 Instrument (Roche Applied Science, Meylan, France). Aliquots of 0.05 ng μL−1 diluted DNA were stored at –20°C ready for molecular applications. Quantitative polymerase chain reaction Quantitative polymerase chain reaction (qPCR) was performed in a LightCycler FastStart DNA MasterPLUS Sybr Green I mix (Roche Applied Science) in a LightCycler 480 Instrument (Roche Applied Science). All qPCR reactions were performed in duplicate for each DUW sample using the epMotion® 5070 pipetting robot (Eppendorf, Montesson, France). The 10 μL reaction mixture contained 0.5 μM of each primer, 1X of LightCycler FastStart DNA MasterPLUS Sybr Green I mix (Roche Applied Science), 5 μL of H2O and 2 μL of a 0.05 ng μL−1 DNA-diluted template. The copy number of the bacterial 16S rRNA gene was quantified using the 341F–515R primer set (Baker, Smith and Cowan 2003) as described in Costa et al. (2015). The FF390—FR1 primer set was used to access the copy number of the fungal 18S rRNA gene according to the amplification protocol previously described by Chemidlin Prévost-Bouré et al. (2011). A standard curve was generated by performing serial dilutions of a known amount of a standard sample containing a fragment of the 18S rRNA gene of Candida albicans ATCC 3153. The standard curve encompassed 2 × 102 to 2 × 106 copies of the target sequence per well. No-template control was run for each qPCR assay. The number of bacterial and fungal rRNA copies derived from the qPCR measurements was normalized to account for the filtered volume of water for each respective sample. Pyrosequencing of 16S and 18S rRNA gene sequences Bacterial and fungal diversities were determined for each DUW sample by 454 pyrosequencing of ribosomal genes. Extracted DNA from each duplicated DUW sample was pooled prior to the pyrosequencing. Each sample was prepared from the same DNA input quantity in order to normalize the libraries and achieve even representation of each library in the pyrosequencing results. The V3–V5 region of the bacterial 16S rRNA genes was amplified using the 341F and 926R primers (Baker, Smith and Cowan 2003) as described in Costa et al. (2015). The fungal 18S rRNA genes were amplified using the FF390 and FR1 primers as described by Terrat et al. (2015). The PCRs were performed in triplicate for each sample and pooled before purification of the PCR products using the PCR clean-up kit according to the manufacturer's instructions (Macherey-Nagel, Hoerdt, France) and quantification using SYBR Green I dye (Invitrogen). Purified PCR products were then specifically tagged in a second PCR of seven cycles, conducted under similar amplification conditions, using primers containing pyrosequencing adaptors and 10 base pair multiplex identifiers barcode added to one primer at the 5′ position to specifically identify each sample. Finally, bacterial and fungal PCR products were purified and quantified using the Quant-iT PicoGreen® dsDNA Assay Kit (Life Technologies, Saint-Aubin, France). In addition, size and purity of amplicons were checked using the MultiNA bioanalyzer (Shimadzu, Marne-la-Vallée, France). Preparation of PCR amplicon library from negative controls of DNA extraction and amplification failed, excluding contamination bias. Equimolar PCR products (1 × 109 molecules μL−1) were pooled for a single sequencing reaction run for each community (i.e. bacteria and fungi). The Lib-L kit (Roche Applied Science) was used for emPCR and the unidirectional sequencing of the amplicon library. The two pyrosequencing runs were conducted in a GS Junior 454 Sequencer (Roche Applied Science) following the manufacturer's recommendations. The raw datasets are available on the EBI database system in the Sequence Read Archive, under study accession number PRJEB12425 (http://www.ebi.ac.uk/ena). Bioinformatics analysis of 16S and 18S rRNA gene sequences Pyrosequencing data were analyzed using the GnS-PIPE (version 1.1.11) pipeline described by Terrat et al. (2015), based on the parameters detailed in SM (Supporting Information, Table SB). Briefly, raw reads were sorted according to identifier sequences. All reads with mismatches in the primer sequence, ambiguities in the sequence or sequences inferior to a minimal length were discarded. Rigorous dereplication (i.e. clustering of strictly identical sequences) was performed using a PERL program. The retained dereplicated reads were then aligned using INFERNAL alignment (Cole et al.2009) and clustered into operational taxonomic units (OTU) as described by Terrat et al. (2015). All the retained high-quality reads were taxonomically assigned according to the Silva r114 reference database (Quast et al.2013). OTUs were clustered with 5% sequence dissimilarity cut-off at the genus level to obtain reliable representation of bacterial and fungal communities through taxonomic classification as previously explained in Costa et al. (2015). During the analysis, all singletons corresponding to reads detected only once and not clustered (that might be artefacts such as PCR chimeras and large sequencing errors produced by the PCR and the pyrosequencing) were checked taking into account the quality of their taxonomic assignments (Terrat et al.2015). In order to avoid biased community comparisons, the sample reads were reduced by random selection closed to the lowest datasets. The retained high-quality reads were used for taxonomy-independent analyses including estimation of diversity indices and taxonomy-based analyses using similarity approaches against Silva r114 reference databases and post-processed using R package (R Development Core Team 2004). Heatmaps were built up from the relative abundance values of the most dominant bacterial and fungal genera across the samples (relative abundance >1%) using the gplots R package (Warnes et al.2015). Statistical analysis CFU and qPCR data were analyzed using non-parametric tests with significance assessed at the level of P < 0.05. All statistical analyses were performed under R project (R Development Core Team 2004). RESULTS AND DISCUSSION Dental microbiological water quality investigations were performed thanks to the voluntary participation of 10 practitioners from hospitals and public dental clinics of the region of Poitiers (France). Among the DU put at our disposal, three 8- to 12-year-old DUs were continuously treated with disinfectants (Calbenium or Oxygenal 6). Except for the disinfectant application, the three offices presented similar features in terms of type of dental cares carried out and sterilization procedures that limited the influence to other parameters than disinfectant on the microbial community encountered inside DUWL. These DUs were sampled to investigate occurrence and diversity of both bacterial and fungal communities during routine dental practice and accordingly to the flow from the water supply (incoming water: IW) to the outer exposure point (output water after stagnation period: OWS and output water after activity period: OWA). The IW analysis reflected the microbiological quality of the water supplying DUs. As water stagnation promotes growth and the proliferation of biofilm within DUWL (Kumar et al.2010), the OWS can be considered as an indicator of the microorganisms present in the biofilm in the absence of feasibility to collect DUWL tubing. Microorganisms present in both OW samples (OWS and OWA) may originate from IW or from the retraction of oral fluids in DUWL. Contrary to the OWS, the OWA was exposed all day long to a chemically treated water flow and consequently was considered as an indicator of the treatment efficiency. Bacterial and fungal abundances in DUWL: influence of disinfectant Occurrence of bacterial and fungal communities was estimated by quantitative PCR targeting the 16S rRNA and 18S rRNA genes, respectively. Results sustained colonization by both bacteria and fungi in the DUWL, with levels varying according to each DU and to the water flow inside DU (Table 2a and b). Based on the number of rRNA gene copy in microbial genomes, fungi would be less prevalent and significantly less abundant than bacteria in sampled DUWL. Interestingly, 18S rRNA gene copies from Amoebae spp. were also recovered from our samples by qPCR (Supporting Information, Table SC) based on the protocol from Le Calvez et al. (2012). Due to their encystment ability, free-living amoebae (FLA) may protect some microorganisms from environmental stress, as already described for Legionella pneumophila (Greub and Raoult 2004; Dey et al.2009), Candida spp (Barbot et al.2014) or Mycobacterium spp (Delafont et al.2014). Thus, occurrence of FLA may contribute to the propagation of microorganisms able to resist or even escape to phagocytosis, including pathogens, and to their efficient recolonization elsewhere in DUWL. Altogether, qPCR investigations showed the colonization of DUWL by a wide range of microorganisms including bacteria, fungi and protists despite flushing process and disinfecting treatment performed in the working DU. Higher 16S and 18S rRNA gene copy number per 100 mL of water was quantified in OWS compared to IW (P < 0.05) in the studied DU, with the exception of the bacterial colonization in OWS of Unit 3 (Table 2a and b). This highlights the critical influence of the stagnation period that significantly increases microbial abundance inside DUWL, as previously reported (Santiago et al.1994; Arvand and Hack 2013; Costa et al.2015). Remarkably, the number of rRNA gene copy per 100 mL of water recovered in OWA remained unexpectedly higher than in IW (P < 0.05) in all studied DUs, whereas OWA was exposed all day long to a chemically treated water flow. Table 2. Bacterial (a) and fungal (b) abundance in DUW estimated using 16S rRNA and 18S rRNA gene quantification by qPCR, respectively. Each DUW sampled at two different time periods was analyzed in triplicate. Each value represents the mean ± standard deviation.     Bacterial 16S rRNA gene copies 100 mL−1 of water    Treatment  IW  OWS  OWA  (a)  Unit 1  Calbenium  6.58 (±0.39) × 103  3.42 (±0.73) × 106a  9.16 (±2.70) × 106b  Unit 2  Calbenium  4.51 (±1.35) × 102  4.32 (±0.16) × 105a  9.42 (±10.40) × 102b  Unit 3  Oxygenal 6  1.93 (±0.30) × 106  7.00 (±0.77) × 105a  2.92 (±0.10) × 106b  (b)  Unit 1  Calbenium  ND  1.34 (±0.00) × 103a  1.69 (±0.63) × 104b  Unit 2  Calbenium  2.59 (±0.20) × 102  5.05 (±0.53) × 103a  9.50 (±6.83) × 102b  Unit 3  Oxygenal 6  4.59 (±2.71) × 102  1.37 (±0.32) × 104a  2.47 (±0.18) × 104b      Bacterial 16S rRNA gene copies 100 mL−1 of water    Treatment  IW  OWS  OWA  (a)  Unit 1  Calbenium  6.58 (±0.39) × 103  3.42 (±0.73) × 106a  9.16 (±2.70) × 106b  Unit 2  Calbenium  4.51 (±1.35) × 102  4.32 (±0.16) × 105a  9.42 (±10.40) × 102b  Unit 3  Oxygenal 6  1.93 (±0.30) × 106  7.00 (±0.77) × 105a  2.92 (±0.10) × 106b  (b)  Unit 1  Calbenium  ND  1.34 (±0.00) × 103a  1.69 (±0.63) × 104b  Unit 2  Calbenium  2.59 (±0.20) × 102  5.05 (±0.53) × 103a  9.50 (±6.83) × 102b  Unit 3  Oxygenal 6  4.59 (±2.71) × 102  1.37 (±0.32) × 104a  2.47 (±0.18) × 104b  ND: not detected. a Value significantly different from the corresponding IW values (Mann-Whitney test, P < 0.05). b Value significantly different from the corresponding OWS values (Mann-Whitney test, P < 0.05). View Large Table 2. Bacterial (a) and fungal (b) abundance in DUW estimated using 16S rRNA and 18S rRNA gene quantification by qPCR, respectively. Each DUW sampled at two different time periods was analyzed in triplicate. Each value represents the mean ± standard deviation.     Bacterial 16S rRNA gene copies 100 mL−1 of water    Treatment  IW  OWS  OWA  (a)  Unit 1  Calbenium  6.58 (±0.39) × 103  3.42 (±0.73) × 106a  9.16 (±2.70) × 106b  Unit 2  Calbenium  4.51 (±1.35) × 102  4.32 (±0.16) × 105a  9.42 (±10.40) × 102b  Unit 3  Oxygenal 6  1.93 (±0.30) × 106  7.00 (±0.77) × 105a  2.92 (±0.10) × 106b  (b)  Unit 1  Calbenium  ND  1.34 (±0.00) × 103a  1.69 (±0.63) × 104b  Unit 2  Calbenium  2.59 (±0.20) × 102  5.05 (±0.53) × 103a  9.50 (±6.83) × 102b  Unit 3  Oxygenal 6  4.59 (±2.71) × 102  1.37 (±0.32) × 104a  2.47 (±0.18) × 104b      Bacterial 16S rRNA gene copies 100 mL−1 of water    Treatment  IW  OWS  OWA  (a)  Unit 1  Calbenium  6.58 (±0.39) × 103  3.42 (±0.73) × 106a  9.16 (±2.70) × 106b  Unit 2  Calbenium  4.51 (±1.35) × 102  4.32 (±0.16) × 105a  9.42 (±10.40) × 102b  Unit 3  Oxygenal 6  1.93 (±0.30) × 106  7.00 (±0.77) × 105a  2.92 (±0.10) × 106b  (b)  Unit 1  Calbenium  ND  1.34 (±0.00) × 103a  1.69 (±0.63) × 104b  Unit 2  Calbenium  2.59 (±0.20) × 102  5.05 (±0.53) × 103a  9.50 (±6.83) × 102b  Unit 3  Oxygenal 6  4.59 (±2.71) × 102  1.37 (±0.32) × 104a  2.47 (±0.18) × 104b  ND: not detected. a Value significantly different from the corresponding IW values (Mann-Whitney test, P < 0.05). b Value significantly different from the corresponding OWS values (Mann-Whitney test, P < 0.05). View Large Surprisingly, the IW of Unit 3 showed a discrepancy in the number of 16S rRNA gene copy per 100 mL of water, significantly higher (P < 0.05) than the ones from the two other DUs. After biological analyses and new in situ plumbing investigations, this bacterial contamination could be attributed to a local degradation of the water distribution pipe, confirming the interest of regular water quality control of DUWL. All molecular results were consistent with the plate counts in current use that reflected only the aerobic and aero-tolerant culturable fraction of the DUW microbial communities. Although two DUs displayed less than 500 CFU per mL in IW (Table 3), none of the DUWL reached the microbial water quality level recommended by the ADA for OW (American Dental Association 2012), even if all DUWL were submitted to disinfection. Table 3. Total aerobic and aero-tolerant cultivable microbial biomass in DUW using plate count on R2A medium. Each DUW sampled at two different time periods was analyzed in duplicate, as recommended by the manufacturer of the WASP 2 spiral plater (Biomerieux). Each value represents the mean ± standard deviation.     CFU mL−1 of water    Treatment  IW  OWS  OWA  Unit 1  Calbenium  ≤500  7.10 (±1.60) × 103  4.90 (±0.54) × 103  Unit 2  Calbenium  ≤500  7.13 (±1.16) × 103  4.33 (±0,15) × 103  Unit 3  Oxygenal 6  7.60 (±0.30) × 103  2.60 (±0.40) × 104  >5.00 × 104a      CFU mL−1 of water    Treatment  IW  OWS  OWA  Unit 1  Calbenium  ≤500  7.10 (±1.60) × 103  4.90 (±0.54) × 103  Unit 2  Calbenium  ≤500  7.13 (±1.16) × 103  4.33 (±0,15) × 103  Unit 3  Oxygenal 6  7.60 (±0.30) × 103  2.60 (±0.40) × 104  >5.00 × 104a  a Upper limit of quantification. View Large Table 3. Total aerobic and aero-tolerant cultivable microbial biomass in DUW using plate count on R2A medium. Each DUW sampled at two different time periods was analyzed in duplicate, as recommended by the manufacturer of the WASP 2 spiral plater (Biomerieux). Each value represents the mean ± standard deviation.     CFU mL−1 of water    Treatment  IW  OWS  OWA  Unit 1  Calbenium  ≤500  7.10 (±1.60) × 103  4.90 (±0.54) × 103  Unit 2  Calbenium  ≤500  7.13 (±1.16) × 103  4.33 (±0,15) × 103  Unit 3  Oxygenal 6  7.60 (±0.30) × 103  2.60 (±0.40) × 104  >5.00 × 104a      CFU mL−1 of water    Treatment  IW  OWS  OWA  Unit 1  Calbenium  ≤500  7.10 (±1.60) × 103  4.90 (±0.54) × 103  Unit 2  Calbenium  ≤500  7.13 (±1.16) × 103  4.33 (±0,15) × 103  Unit 3  Oxygenal 6  7.60 (±0.30) × 103  2.60 (±0.40) × 104  >5.00 × 104a  a Upper limit of quantification. View Large Altogether, qPCR and CFU analyses combined approaches showed that the microbial colonization of DUWL changed accordingly to the water circulation within the DU and that stagnation was a significant contributory factor in the contamination of output water (O'Donnell et al.2011; Coleman et al.2014). Remarkably, for Unit 1 and Unit 3, subjected to Calbenium and Oxygenal 6 disinfectants respectively, the number of bacterial and fungal rRNA gene copy per 100 mL of water were higher in OWA than in OWS (P < 0.05) whereas in Unit 2, also treated with Calbenium, a significant decrease was observed between OWS and OWA (P < 0.05). These inconsistent results suggested that a range of factors inherent to each DU may limit or interfere with the activity of the disinfectant. For example, suck back of oral fluids or deterioration of the microbial quality of the supplying water may be an additional source of microorganisms in DUWL (Walker and Marsh 2007; O'Donnell et al.2011; Coleman et al.2014). Until now, to our knowledge, no comprehensive evaluation of the efficacy of Calbenium in DUWL under routine dental practices was done. However, Walker et al. (2003) showed that an overnight Oxygenal 6 treatment on a laboratory DUW 14-day-old biofilm model resulted in a loss of 100% of plate count microorganisms and in a reduction of 99.2% of biofilm coverage of dental tubing. In general dental practices, Schel et al. (2006) have demonstrated the efficacy of Oxygenal 6 application in a continuous mode over six other disinfectants to maintain a water quality level consistent with ADA guidelines in 91% of the treated DUWL studied. However, no information about the characteristics of the studied DUWL was provided, such as the DU origin and age that may confound comparisons of results. Consequently, the present study reinforces current interests in evaluating the efficacy of treatments under routine dental practices after long-term application of disinfectant, such as Calbenium or Oxygenal 6 since they are commonly used by European dentists. Bacterial and fungal genus richness, diversity and evenness indices in DUWL: influence of disinfectant Pyrosequencing was used to characterize both bacterial and fungal communities according to the water route inside DUWL treated with a disinfectant. A total sum of 37 010 (with a mean length of 385 bases) and 28 619 reads (with a mean length of 316 bp) for bacteria and fungi, respectively, were obtained from the nine samples (IW, OWS and OWA for each studied DU) after 454 pyrosequencing quality filtering. After bioinformatic filters and a homogenization step, a total of 252 and 81 different representative bacterial and fungi genera, respectively, were assigned, indicating a high microbial diversity in DUWL. The complexity of the bacterial and fungal communities in the three water groups from the three DUWL was investigated based on richness (number of genus-level OTUs), Shannon and Evenness indices (Table 4a and b). Table 4. Bacterial (a) and fungal (b) genus richness, diversity and evenness indices in DUW. Duplicate extracted DNA from each DUWL sample was pooled according to the water group prior to the pyrosequencing.     Number of genus  Shannon  Evenness    Treatment  IW  OWS  OWA  IW  OWS  OWA  IW  OWS  OWA  (a)  Unit 1  Calbenium  82  126  89  2.79  2.43  1.46  0.63  0.50  0.32  Unit 2  Calbenium  69  139  89  2.65  3.48  2.96  0.63  0.70  0.66  Unit 3  Oxygenal 6  225  94  200  3.87  2.42  3.56  0.71  0.53  0.67  (b)  Unit 1  Calbenium  21  30  58  2.14  2.43  2.20  0.70  0.71  0.54  Unit 2  Calbenium  51  9  14  2.92  1.20  0.91  0.74  0.55  0.34  Unit 3  Oxygenal 6  35  14  27  2.19  0.68  1.17  0.61  0.26  0.35      Number of genus  Shannon  Evenness    Treatment  IW  OWS  OWA  IW  OWS  OWA  IW  OWS  OWA  (a)  Unit 1  Calbenium  82  126  89  2.79  2.43  1.46  0.63  0.50  0.32  Unit 2  Calbenium  69  139  89  2.65  3.48  2.96  0.63  0.70  0.66  Unit 3  Oxygenal 6  225  94  200  3.87  2.42  3.56  0.71  0.53  0.67  (b)  Unit 1  Calbenium  21  30  58  2.14  2.43  2.20  0.70  0.71  0.54  Unit 2  Calbenium  51  9  14  2.92  1.20  0.91  0.74  0.55  0.34  Unit 3  Oxygenal 6  35  14  27  2.19  0.68  1.17  0.61  0.26  0.35  View Large Table 4. Bacterial (a) and fungal (b) genus richness, diversity and evenness indices in DUW. Duplicate extracted DNA from each DUWL sample was pooled according to the water group prior to the pyrosequencing.     Number of genus  Shannon  Evenness    Treatment  IW  OWS  OWA  IW  OWS  OWA  IW  OWS  OWA  (a)  Unit 1  Calbenium  82  126  89  2.79  2.43  1.46  0.63  0.50  0.32  Unit 2  Calbenium  69  139  89  2.65  3.48  2.96  0.63  0.70  0.66  Unit 3  Oxygenal 6  225  94  200  3.87  2.42  3.56  0.71  0.53  0.67  (b)  Unit 1  Calbenium  21  30  58  2.14  2.43  2.20  0.70  0.71  0.54  Unit 2  Calbenium  51  9  14  2.92  1.20  0.91  0.74  0.55  0.34  Unit 3  Oxygenal 6  35  14  27  2.19  0.68  1.17  0.61  0.26  0.35      Number of genus  Shannon  Evenness    Treatment  IW  OWS  OWA  IW  OWS  OWA  IW  OWS  OWA  (a)  Unit 1  Calbenium  82  126  89  2.79  2.43  1.46  0.63  0.50  0.32  Unit 2  Calbenium  69  139  89  2.65  3.48  2.96  0.63  0.70  0.66  Unit 3  Oxygenal 6  225  94  200  3.87  2.42  3.56  0.71  0.53  0.67  (b)  Unit 1  Calbenium  21  30  58  2.14  2.43  2.20  0.70  0.71  0.54  Unit 2  Calbenium  51  9  14  2.92  1.20  0.91  0.74  0.55  0.34  Unit 3  Oxygenal 6  35  14  27  2.19  0.68  1.17  0.61  0.26  0.35  View Large In both Calbenium-treated Units 1 and 2, significant decreases of the number of bacterial genera and Shannon index were observed in the OWA samples compared to the OWS ones suggest efficacy of Calbenium to minimize the bacterial diversity in DUWL. While a constant decrease of Shannon and Evenness indices was observed in Unit 1 from IW to OWA, Evenness index remained stable in Unit 2, suggesting a distinct influence of Calbenium on the bacterial community of these two DUs, in favor of a few but highly dominant bacterial species in Unit 1. Considering bacterial biomass and diversity metrics, a similarity was shown in IW of Units 1 and 2, even if Unit 1 was equipped with a water softener unlike Unit 2 (Table 1). This observation is in agreement with the results of Hambsch, Sacré and Wagner (2004) suggesting that a water softener would not be a constant source of microbial contamination of DUWL. Remarkably, for the Oxygenal-treated Unit 3, the observed bacterial richness in the IW was the highest observed among the three studied DUs. A 58.2% decrease of the bacterial genera was observed in OWS compared to IW. Nevertheless, genus richness, Shannon and Evenness indices observed in the OWA reverted to values close to the ones observed in the IW. This result suggested that Oxygenal 6 used as a shock cycle for 45 min before the weekend could be effective to control the negative influence of water stagnation on the bacterial diversity in DUWL. It also highlighted the impact of contaminated supplying water on the OWA water microbial quality and, in this context, the subsequent limited efficacy of Oxygenal 6 to reduce the bacterial load in OW. The fungal community analyses showed different results in both Calbenium-treated Units 1 and 2. A reduction of the fungal genus number was observed in OWS compared to IW only in Unit 2, suggesting a lower fungal diversity in the output water only for this Unit. In Unit 1, a 2-fold increase of the number of fungal genera was observed in OWA compared to OWS. Evenness and Shannon evolution patterns suggested a dominance of a few fungal species in both OW (mainly in OWA) in Unit 2 instead of in Unit 1. Thus, this discrepancy observed in diversity metrics suggested that the efficacy of Calbenium may be affected by different factors such as the quality of the supply water and the presence of biofilms in DUWL tubing. Remarkably, for the Oxygenal 6-treated Unit 3, a similar evolution pattern was observed for both bacterial and fungal diversity indices, highlighting the interest of shock treatment before a long water stagnation period and the influence of the microbial quality of the water supplying this DUWL. Through these three distinct case studies, our results confirmed that microbial richness and diversity may be strongly linked to technical, maintenance and practice characteristics of each DU but also dependent on the microbial quality of the water supplying the DU. Inconsistent results observed from the indices of both bacterial and fungal community diversity clearly suggested that the long-term disinfection efficacy should be optimized to reduce both density and diversity of the microbial communities in DUWL. Bacterial and fungal communities’ composition in DUWL: influence of disinfectants Proteobacteria was a prevalent bacterial phylum in each studied DUWL representing over 60% of the total sequences, although with levels varying according to the DU and to water flow inside DUs (Supporting Information, Table SD). This phylum was commonly detected in drinking water and distribution system (Shi et al.2013; Holinger et al.2014; Huang et al.2014); their relative abundance may be due to a higher tolerance to chlorine compared to other phyla (Huang et al.2014). Members of Actinobacteria, Firmicutes, Bacteroidetes and Chlamydia were also found as previously observed in DUWL (Costa et al.2015). At the class level, Gammaproteobacteria, Alphaproteobacteria, Betaproteobacteria and Actinobacteria were the most represented in the studied DUWL. Ascomycota and Basidiomycota were dominant at fungal phyla level and Saccharomycetes, Dothideomycetes, Sordariomycetes, Agaricomycetes and Tremellomycetes at the class level, also in varying proportions according to the DU and location (Supporting Information, Table SD). Bacterial and fungal genera representing at least 1% of the total abundance of one of the three studied water groups were considered in each condition (Figs 1 and 2). In Unit 1, subjected to continuous Calbenium treatment, Halomonas (27% of the total sequences), Shewanella (13%), Propionibacterium (12%) and Sphingomonas (12%) were dominant bacterial genera detected in IW (Fig. 1). Stenotrophomonas was the sole dominant genus in both OW, representing 42% and 76% of the total bacterial sequences in OWS and OWA, respectively (Fig. 1). Concerning the fungal contamination, Mortierella (13%), Saccharomyces (13%) and Galactomyces (8%) were dominant in IW (Fig. 2). The detection of the genus Candida, which was also dominant in IW (31% of the total sequences), varied according to the water flow inside DUWL; Candida represented 12% of the total sequences in OWS and decreased to 5% in OWA. Phoma (20%) and Flammulina (28%) were also dominant in OWS and OWA, respectively. Nevertheless, unknown fungi represented 16% and 37% of the total sequences and unclassified fungi, 34% and 20% of the total sequences in OWS and OWA, respectively (Fig. 2). Figure 1. View largeDownload slide Heatmap representing relative abundance of bacterial communities in IW, OWS and OWA collected in the three studied DUs. Only genera representing at least 1% of relative abundance from the total sequences list in at least one condition (IW, OWS or OWA) for each DU were represented. Figure 1. View largeDownload slide Heatmap representing relative abundance of bacterial communities in IW, OWS and OWA collected in the three studied DUs. Only genera representing at least 1% of relative abundance from the total sequences list in at least one condition (IW, OWS or OWA) for each DU were represented. Figure 2. View largeDownload slide Heatmap representing relative abundance of fungal communities in IW, OWS and OWA collected in the three studied DUs. Only genera representing at least 1% of relative abundance from the total sequences list in at least one condition (IW, OWS or OWA) for each DU were represented. Figure 2. View largeDownload slide Heatmap representing relative abundance of fungal communities in IW, OWS and OWA collected in the three studied DUs. Only genera representing at least 1% of relative abundance from the total sequences list in at least one condition (IW, OWS or OWA) for each DU were represented. In Unit 2, also subjected to continuous Calbenium treatment, Halomonas (30%), Propionibacterium (18%) and Shewanella (14%) were still the three dominant bacterial genera detected in IW, as observed in Unit 1 (Fig. 1). These genera were also highly detected in OWS (Halomonas 23%, Propionibacterium 20% and Shewanella 14% of the total sequences), whereas Parvularcula (14%), Barnesiella (14%), Sphingomonas (10%) and Sphingobium (9%) were dominant in OWS. Regarding the fungal contamination, Mortierella (26%) and Malassezia (6%) genera were dominant in IW, Mrakia (50%) and Sporobolomyces (18%) in OWS, and Pseudallescheria (10%) and Cladosporium (6%) in OWA (Fig. 2). Contrary to previous observation concerning Unit 1, Candida genus represented 14% of the total sequences in IW of Unit 2 and its prevalence increased according to the water flow inside DUWL, representing 27% of the total sequence in OWS and reaching 77% in OWA. Regarding Unit 3 subjected to both continuous and intermittent Oxygenal 6 treatments, the IW was dominated by Pseudomonas (12% of the total sequences), Chlorobacterium (11%), Sphingomonas (7%) and Sphingobium (7%) genera (Fig. 1). This observation evidenced that, in this DU, the bacterial community composition of IW differed from that detected in the two other studied DUs. While 36% of the total sequences detected in OWS were affiliated to Legionella, this genus was not dominant in OWA. Both OW were dominated by Sphingomonas, representing 22% and 17% of the total sequences in OWS and OWA, respectively, and Sphingobium genera (14% and 17%). Regarding the fungal contamination, the majority of the sequences were affiliated to unknown fungi (47%), Mrakia (22%) and Candida (8%) in IW; to environmental fungi (88%) in OWS; and to Mrakia (54%), environmental fungi (11%) and Candida (3%) in OWA (Fig. 2). For the first time, a next-generation DNA sequencing was used to concurrently investigate both bacterial and fungal communities in DUWL. Results showed that large and diverse bacterial and fungal communities were associated from the water supply to the outer exposure point of the three DUs. Despite flushing and disinfectant applications, more than 80 distinct fungal genera could colonize the DUWL, mainly belonging to Ascomycota and Basidiomycota phyla. Results showed that the Saccharomycetes class was dominant in the core fungal microbiome of DUWL The Candida genera occurred in the three studied DUWL, whereas, until recently, this genus has been recovered only occasionally from DUWL (Walker et al.2004; Szymańska 2005). The infectious risk associated with Candida albicans is well documented, whereas other members of the Candida species are also involved in increasing number of infections (Arendrup 2013). In contrast, Aspergillus and Penicillium, previously described as prevalent in drinking water and DUWL, were not detected in our DUWL (Walker et al.2004; Szymańska 2005; Sammon et al.2010; Mesquita-Rocha et al.2013; Oliveira et al.2013). Occurrence of these two genera like Cladosporium may result from environmental contamination, as they are ubiquitously present on walls and ceilings, for example (Gniadek and Macura 2007). Our results highlighted the critical influence of the water stagnation on the microbial contamination and probably the associated influence of the biofilm developed inside DUWL. Indeed, especially in the OWS condition, variable and partially specific bacterial and fungal communities were observed in each sampled DU whereas the bacterial and fungal communities present in the IW condition were closer (in particular for Units 1 and 2); this suggest the development of a specific biofilm inside each DU and, consequently the singularity of each studied case. Moreover, results highlighted that OWA condition was influenced by the microbial community from both IW and OWS and consequently, by the own biofilm of each DU. In addition, the occurrence of potentially pathogenic bacterial and fungal genera such as Stenotrophomonas, Propionibacterium, Legionella, Halomonas, Pseudomonas, Shewanella, Candida, Cladosporium and Fusarium in DUWL even subjected to a disinfectant reinforced the interest to control the microbiological water quality in dental output water. The studied continuous disinfecting protocols seemed partially effective to reduce the microbial density and diversity in DUWL after long-term application; however, their activity was insufficient to reach the microbial quality CFU threshold defined by the ADA in output waters (Puttaiah et al.2012). Results also suggested distinct and variable disinfectant activity on the bacterial and fungal communities inhabiting DUWL. Interestingly, a shock treatment before a long water stagnation period may limit the microbial colonization of DUWL. Also, a lack of efficacy of disinfecting treatments in DUWL may be explained by a short exposure time and frequency, an inadequate disinfectant and/or concentration, a malfunction of devices or a lack of compliance to disinfectant protocols (Montebugnoli et al.2005; O'Donnell et al.2007; Coleman et al.2014). The exopolysaccharide polymers excreted from microorganisms attached to the internal tubing and growing as a biofilm may also form a protective matrix to chemical water treatments as well as the stratification of the biofilm may reduce the exposure of all the microorganisms to disinfectants (Costerton, Stewart and Greenberg 1999; O'Donnell et al.2011; Ramage et al.2012). Results from O'Donnell et al. (2007) showed that the lesser efficacy of some disinfectants based on hydrogen peroxide may result from the selection of disinfectant-tolerant species and especially, from the production by microorganisms of enzymes such as catalase that degrade the active agent. Interestingly, in Unit 3 treated with hydrogen peroxide (active agent of Oxygenal 6), the prevalence of two catalase positive bacterial genera (e.g. Sphingomonas and Sphingobium) was higher in OW than in IW suggesting a selection of these species after exposure to disinfectant. Altogether, our results may suggest that different disinfection strategies are needed to improve the microbial quality of the DUWL output water. CONCLUSION The present study indicated that each DUWL develop a heterogeneous and complex ecological system with bacterial and fungal assemblages in populations, influenced by the conjunction of a range of factors. Through these three distinct case studies, results clearly suggested that patients and dental staff remained exposed to a potential infectious risk relevant even though DUWL were submitted to disinfectant associated to flushing processes. Also, our study demonstrated the necessity and importance of considering concurrent approaches targeting density but also diversity of both bacterial and fungal communities for the evaluation of DUWL disinfectant efficacy. Despite the limited number of studied DUs, our results clearly claim and support local management efforts, the definition of European standards for DUWL output water, regular microbial water quality investigations of DUWL during routine general dental practice and the compliance with existing preventive recommendations in offices. SUPPLEMENTARY DATA Supplementary Data. Authors gratefully acknowledge the practitioners from hospitals and public dental clinics of the region of Poitiers for their voluntary participation to our studies on the evaluation of the dental water quality. Authors are sincerely thankful for the scientific supports provided by S. Terrat and colleagues from the GenoSol platform (INRA, Dijon, France, www2.dijon.inra.fr/plateforme_genosol/) for the development of the 454 pyrosequencing. They also thank D. Debail for revision of the original English-language document. FUNDING This work was partly supported by the following 2015–2020 programs: the State-Region Planning Contracts (CPER) and the European Regional Development Fund (FEDER). Conflict of interest. None declared. REFERENCES American Dental Association (ADA) 2012 Statement on Dental Unit Waterlines  http://www.ada.org/en/member-center/oral-health-topics/dental-unit-waterlines (20 December 2015, date last accessed) Arendrup MC Candida and candidaemia. 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TI - Occurrence and diversity of both bacterial and fungal communities in dental unit waterlines subjected to disinfectants
JF - Pathogens and Disease
DO - 10.1093/femspd/ftw094
DA - 2016-10-01
UR - https://www.deepdyve.com/lp/oxford-university-press/occurrence-and-diversity-of-both-bacterial-and-fungal-communities-in-2nshjqR6bN
SP - ftw094
VL - 74
IS - 7
DP - DeepDyve
ER -