The purpose of this study was to identify triclosan tolerant heterotrophic plate count (HPC) bacteria from sewage effluent and to determine cross-resistance to antibiotics. R2 agar supplemented with triclosan was utilised to isolate triclosan resistant bacteria and 16S rRNA gene sequencing was conducted to identify the isolates. Minimum inhibitory concentrations (MICs) of organisms were determined at selected concentrations of triclosan and cross-resistance to various antibiotics was performed. High-performance liquid chromatography was conducted to quantify levels of triclosan in sewage water. Forty-four HPC were isolated and identified as the five main genera, namely, Bacillus, Pseudomonas, Enterococcus, Brevibacillus and Paenibacillus. MIC values of these isolates ranged from 0.125 mg/L to >1 mg/L of triclosan, while combination of antimicrobials indicated synergism or antagonism. Levels of triclosan within the wastewater treatment plant (WWTP) ranged between 0.026 and 1.488 ppb. Triclosan concentrations were reduced by the WWTP, but small concentrations enter receiving freshwater bodies. Results presented indicate that these levels are sufficient to maintain triclosan resistant bacteria under controlled conditions. Further studies are thus needed into the impact of this scenario on such natural receiving water bodies.

INTRODUCTION

Worldwide there is growing concern about the possible effect of widespread use of biocides on antibiotic resistance. Of these biocides, triclosan (2,4,4′-trichloro-2′-hydroxydiphenylether) in particular has received attention in various studies due to its frequent use. Studies have indicated the emergence of triclosan resistance among bacteria (Brenwald & Fraise 2003; Ciusa et al. 2012).

Triclosan is a widely-used bactericide found in a variety of personal care products. It is also used as a stabilizing agent in products such as detergents and cosmetics (Chen et al. 2011). This is a chlorinated aromatic compound that has functional groups representative of both ethers and phenols. In appearance it is a white powder with a slight phenolic odour. Triclosan is only slightly soluble in water, but soluble in ethanol, methanol, diethyl ether and strong basic solutions such as 1 M sodium hydroxide (Tsai et al. 2008). The compound exhibits broad-spectrum antimicrobial properties. At low concentrations triclosan appears bacteriostatic and targets bacteria mainly by inhibiting fatty acid synthesis, while at high concentration ranges triclosan damages cell membranes and disrupts lipid and protein synthesis (Brenwald & Fraise 2003; Middleton & Salierno 2013).

Treated wastewater may serve as a reservoir for environmental antibiotic and biocide resistant bacteria (Middleton & Salierno 2013). Resistant and susceptible bacteria, genetic elements that confer resistance and various chemicals from anthropogenic origins (including antimicrobials and biocides) intermingle within this environment. These chemicals may act as selection pressures for the maintenance of these resistant bacteria (Middleton & Salierno 2013).

Various studies have suggested that exposure to triclosan in the environment may apply selective pressure to bacterial strains to become tolerant or resistant to triclosan. Increased cross-resistance or co-resistance has also been reported (Rodriquez et al. 2007). In particular, resistance to antibiotics such as β-lactams, aminoglycosides, chloramphenicol, fluoroquinones, ampicillins and tetracyclines has been reported alongside tolerance to triclosan (Tattawasart et al. 1999; Aiello & Larson 2003; Tkachenko et al. 2007). However, several other studies have failed to demonstrate such cross-resistance (Middleton & Salierno 2013 and references therein). As a result, the link between triclosan resistance and possible cross-resistance to antibiotics seems challenging to define.

The purpose of this study was to identify triclosan tolerant heterotrophic plate count bacteria from sewage effluent and to determine cross-resistance to antibiotics.

MATERIALS AND METHODS

Sample collection

Water was sampled for heterotrophic plate count (HPC) bacteria at the wastewater treatment plant (WWTP) in Potchefstroom, North West Province, South Africa (26° 44.990′S 27° 5.578′E), from the effluent during the rainy season. One litre grab samples were taken in triplicate (designated A, B and C in isolate identities) in Schott bottles, stored on ice and processed within 4 hours of collection. The WWTP technology is based upon the Bardenpho and modified University of Cape Town (UCT) process. Hydraulic load average is 32 ML per day.

Water samples for triclosan tests were taken from the WWTP in Potchefstroom, North-West province, South Africa at three different sites.

  • 1.

    Inflow – This site is situated after grit removal.

  • 2.

    Before chlorination – Water samples were taken after sedimentation before any chlorination.

  • 3.

    Effluent – This site was sampled twice to include a rainy (indicated as effluent sample 2 in Figure 1) and a dry (indicated as effluent in Figure 1) season.

Triplicate samples were collected at the influent and effluent from the sewage plant. Glass bottles were cleaned with methanol and water before sampling. Water samples (1 L) were centrifuged and filtered. One sample was treated with 500 ppb of triclosan.
Figure 1

Concentration of triclosan measured in the WWTP.

Figure 1

Concentration of triclosan measured in the WWTP.

Isolation and primary characterization of HPC

Triclosan (Irgasan, Sigma, Germany) was dissolved in 95% ethanol and added to R2A (Merck KGaA, Germany). For the initial screening, triclosan was added to the media at the following concentrations (0.25 mg/L, 0.375 mg/L, 0.5 mg/L and 1 mg/L). Bacterial growth was observed at 0.25 mg/L, 0.375 mg/L and 0.5 mg/L; therefore, these triclosan concentrations were used for the rest of the analysis. Water samples were plated onto the triclosan containing R2A media (Merck KGaA, Germany). Colonies observed were selected for further analysis based on morphological features. Selected colonies were then streaked out onto R2A media containing the same concentrations of triclosan. This was repeated at least three times to obtain pure cultures. Gram staining and endospore staining were done, as part of the process is primary characterization and to verify purity of obtained isolates. Isolates were plated onto Cetrimide agar (Biolab Merck, Germany) to determine whether any of the Gram-negative isolates were possibly Pseudomonas species.

Identification of isolates

DNA was isolated using a microwave based process described in Carstens et al. (2014). Amplification of the 16S rRNA gene was performed in 25 μL reaction volumes containing single strength PCR master mix (5 U/μL Taq DNA polymerase (recombinant) in reaction buffer, 2 mM MgCl2, 0.2 mM of each dNTP, Fermentas Life Sciences, Maryland, USA), 50 pmol of each of forward and reverse primers (27F – 5′-AGAGTTTGATCMTGGCTCAG-3′, 1,492 R-5′-TACGGYTACCTTGTTACGACTT-3′) (Lane et al. 1985), 1 μL of target DNA and PCR-grade water (Fermentas Life Sciences, Maryland, USA). Thermal cycling was carried out in a Bio-Rad I-Cycler Thermal Cycler (Bio-Rad Laboratories, Hercules, California, USA). The initial denaturation was at 95 °C for 300 seconds. This was followed by 40 cycles of denaturation at 95 °C for 60 seconds, annealing at 51 °C for 45 seconds and extension at 72 °C for 110 seconds. Final extension was at 72 °C for 300 seconds. Polymerase chain reaction (PCR) successes were evaluated by electrophoresis on 1.5% agarose gels and visualized by ethidium bromide staining and UV illumination.

The BigDye® Terminator v3.1 Cycle Sequencing System (Applied Biosystems Life Technologies, Carlsbad, CA, USA) was used to prepare the PCR amplicons for sequencing. These were then sequenced on a Genetic Analyzer 3130 (Applied Biosystems Life Technologies, Carlsbad, CA, USA). Methods and reagents were used according to manufacturer's instructions. The BLASTN algorithm (NCBI 2017) was used to match obtained sequences to those within the GenBank database.

Minimum inhibitory concentration

Minimum inhibitory concentration (MIC) investigations were conducted to determine whether various triclosan concentrations have an influence on the length of the HPC bacterial lag time (Li et al. 2016). The lag phase of a growth curve (first phase) occurs when a delay in cell growth occurs because of the bacteria adapting to the new environment. Lag time was measured in hours up to where the bacterial growth curve enters the log phase (second phase). Isolates were incubated for 24 h at 37 °C in Mueller Hinton broth (MHB) (Biolab Merck, Germany) at different concentrations of triclosan (0, 0.125, 0.25, 0.375, 0.5, 0.75, 1 mg/L). The control treatment was set up by incubating the isolates in MHB without triclosan. Bacterial growth was accessed by observing the turbidity of the medium by using a microwell plate reader (BioTek Powerwave X, USA) at a wavelength of 520 nm. These tests were performed in 96-well micro-plates (Kaya & Ozbilge 2012). The lag times of the isolates were determined according to the method of Li et al. (2016). This provided some criteria to indicate whether these isolates were susceptible to or inhibited by the different concentrations of triclosan, and this was an indication of the MIC (Li et al. 2016).

Assay for cross-resistance to antibiotics

Seven antibiotics (penicillin G (10 μg), vancomycin (30 μg), streptomycin (25 μg), erythromycin (15 μg), trimethoprim (2.5 μg), tetracycline (30 μg) and amoxycillin (10 μg)) were used to assay the triclosan resistant HPC isolates for cross-resistance to antibiotics. This was done using the Kirby-Bauer method (Boyle et al. 1972). Broth cultures of individual isolates were spread plated onto Mueller Hinton agar (MHA). Antibiotic discs were placed on the MHA (Merck, Germany). These were incubated at 37 °C for 24 hours (Carstens et al. 2014). Inhibition zones were measured after 24 hours and interpreted by using the Performance Standards for Antimicrobial Disk Susceptibility Tests (NCCLS 1999).

Assay for cross-resistance to antibiotics in the presence of triclosan

Three antibiotics were used to assay for cross-resistance to antibiotics in the presence of a variety of triclosan concentrations. Resistance patterns in the presence of triclosan based on preceding results as indicated in this study, protein and cell wall synthesis inhibitor antibiotics indicated more resistance patterns. The following antibiotics were selected: penicillin G (10 μg), vancomycin (30 μg), erythromycin (15 μg). MHA (Merck, Germany) plates were prepared with different concentrations of triclosan (0, 0.125, 0.25, 0.375, 0.5, 0.75, 1 mg/L). Broth cultures of individual isolates were spread plated onto MHA. Antibiotics were placed on the MHA containing the isolates. Isolates were incubated at 37 °C for 24 hours. Inhibition zones were measured after 24 hours and interpreted using the Performance Standards for Antimicrobial Disk Susceptibility Tests (NCCLS 1999).

The three main Gram-positive species (Bacillus spp., Pseudomonas spp., and Paenibacillus spp.), triclosan concentration and antibiotic resistance patterns were used to interpret the results (Tables 13). Results were interpreted as follows. Synergy (S) was noted if the inhibition zone diameter increased when triclosan concentration increased. If the inhibition zone diameter decreased and the triclosan concentration increased, it was noted as antagonism (A). Results were noted as ‘no effect’ (−) if no pronounced effect could be observed between the antibiotic inhibition zone diameter and triclosan concentrations. High triclosan concentration was noted between 0.5 and 1 mg/L and low triclosan concentration between 0.125 and 0.375 mg/L.

Table 1

Antibiotic resistant profiles in the presence of varying concentrations of triclosan indicating synergy/antagonism for the Bacillus spp. group

IsolateID number[Low (0.125–0.375 mg/L)]
[High (0.5–1 mg/L)]
Bacillus spp. EVAPGEVAPG
Bacillus aerius C8 – 
Bacillus aerius C15 – – – – 
Bacillus aerius C17 
Bacillus aerius C20 
Bacillus aerius C22 – – – – – – 
Bacillus cereus C2 – – – 
Bacillus cereus C4 – – – – 
Bacillus cereus C8 – – 
Bacillus cereus C24 – – 
Bacillus licheniformis C47 
Bacillus licheniformis C23 – 
Bacillus licheniformis C28 – – – 
Bacillus licheniformis C30 – 
Bacillus safensis C46 – – 
Bacillus siamensis C3 – 
Bacillus stratosphericus C34 – – – 
Bacillus subtilis C1 
Bacillus tequilensis C5 
Bacillus tequilensis C21 
Bacillus tequilensis C27 
Bacillus tequilensis C38 – – 
Bacillus thuringiensis C9 – – – 
Bacillus thuringiensis C10 – – 
Bacillus thuringiensis C12 – – 
Bacillus thuringiensis C14 – – 
Bacillus thuringiensis C35 – – – 
Bacillus thuringiensis C41 – 
Bacillus thuringiensis C42 – – – – 
Bacillus weihenstephanensis C25 – – 
Brevibacillus parabrevis C6 – 
Enterococcus mundtii C16 
Unknown C39 
IsolateID number[Low (0.125–0.375 mg/L)]
[High (0.5–1 mg/L)]
Bacillus spp. EVAPGEVAPG
Bacillus aerius C8 – 
Bacillus aerius C15 – – – – 
Bacillus aerius C17 
Bacillus aerius C20 
Bacillus aerius C22 – – – – – – 
Bacillus cereus C2 – – – 
Bacillus cereus C4 – – – – 
Bacillus cereus C8 – – 
Bacillus cereus C24 – – 
Bacillus licheniformis C47 
Bacillus licheniformis C23 – 
Bacillus licheniformis C28 – – – 
Bacillus licheniformis C30 – 
Bacillus safensis C46 – – 
Bacillus siamensis C3 – 
Bacillus stratosphericus C34 – – – 
Bacillus subtilis C1 
Bacillus tequilensis C5 
Bacillus tequilensis C21 
Bacillus tequilensis C27 
Bacillus tequilensis C38 – – 
Bacillus thuringiensis C9 – – – 
Bacillus thuringiensis C10 – – 
Bacillus thuringiensis C12 – – 
Bacillus thuringiensis C14 – – 
Bacillus thuringiensis C35 – – – 
Bacillus thuringiensis C41 – 
Bacillus thuringiensis C42 – – – – 
Bacillus weihenstephanensis C25 – – 
Brevibacillus parabrevis C6 – 
Enterococcus mundtii C16 
Unknown C39 

S, synergism; A, antagonism; –, no effect; E, erythromycin; VA, vancomycin; PG, penicillin G.

Table 2

Antibiotic resistance profiles in the presence of varying concentrations of triclosan indicating synergy/antagonism for the Paenibacillus spp. group

IsolateID number[Low (0.125–0.375 mg/L)]
[High (0.5–1 mg/L)]
Paenibacillus spp. EVAPGEVAPG
Paenibacillus cookii C7 – – – – – 
Paenibacillus cookii C33 – – – 
Paenibacillus jamilae C11 – 
IsolateID number[Low (0.125–0.375 mg/L)]
[High (0.5–1 mg/L)]
Paenibacillus spp. EVAPGEVAPG
Paenibacillus cookii C7 – – – – – 
Paenibacillus cookii C33 – – – 
Paenibacillus jamilae C11 – 

S, synergism; A, antagonism; –, no effect; E, erythromycin; VA, vancomycin; PG, penicillin G.

Table 3

Antibiotic resistance profiles in the presence of varying concentrations of triclosan indicating synergy/antagonism for the Pseudomonas spp. group

IsolateID number[Low (0.125–0.375 mg/L)][High (0.5–1 mg/L)]
Pseudomonas spp.EE
Pseudomonas entomophila C26 – 
Pseudomonas mosselii C44 
Pseudomonas mosselii C45 – 
Pseudomonas mosselii C13 – 
Pseudomonas mosselii C32 
Pseudomonas mosselii C29 
Pseudomonas xanthomarina C31 
Pseudomonas xanthomarina C40 
IsolateID number[Low (0.125–0.375 mg/L)][High (0.5–1 mg/L)]
Pseudomonas spp.EE
Pseudomonas entomophila C26 – 
Pseudomonas mosselii C44 
Pseudomonas mosselii C45 – 
Pseudomonas mosselii C13 – 
Pseudomonas mosselii C32 
Pseudomonas mosselii C29 
Pseudomonas xanthomarina C31 
Pseudomonas xanthomarina C40 

S, synergism; A, antagonism; –, no effect; E, erythromycin.

High performance liquid chromatography

High performance liquid chromatography (HPLC) was used to determine the levels of triclosan in influent and effluent of a WWTP, according to the analysis by Xue-fei et al. (2009).

Horizon technology (New Hampshire, USA) provided a method for determining pharmaceuticals and personal care products in water by automated solid phase extraction (SPE). The method used was SPE-DEX 4790 to automatically extract aqueous samples using SPE techniques. The system used for the SPE was the Horizon Technology SPE-DEX® 4790 Automated Extraction System, and the Envision® Platform Controller. Atlantic™ HLB-L Disk was used for extraction purposes.

Eighty milligrams of sodium thiosulfate was added to each sample and acidified with HCl to a pH of between 2 and 3 to reduce biological activity. Each sample was treated with 500 mg of Na4EDTA·2H2O. Samples were equilibrated for 1.5 hours.

The SPE method was then performed according to the Horizon Technologies method 4790. Eluted samples were evaporated by using Horizon technologies DryVap at a temperature of 37 °C. The final volume was 2 mL. This was syringe-filtered before it was injected into the HPLC.

An HPLC system (Agilent 1100) equipped with a UV detector (Agilent 1100) was used. The column was a 250 × 4.6 Venusil XBP C18 (2) 5 μm column (Agela Technologies, USA). The mobile phase was made up of 75% acetonitrile: 25% Milli-Q water. The HPLC conditions were set at a flow rate of 1 mL/min. Twenty microlitres of sample was injected into the column at 25 °C and wavelength of 280 nm (Xue-fei et al. 2009).

Statistical analysis

The inhibition zones of the isolates were used to determine the average and standard error by means of breakdown and one-way analysis of variance (ANOVA), using STATISTICA 10 (StatSoft Inc.©, 2011). Multivariate analysis, specifically redundancy analysis (RDA), was performed on the data using Canoco for Windows 4.56 (Ter Braak & Smilauer 1998). For the RDA, the antibiotic susceptibility data (inhibition zones) served as ‘species data’ and were related to phenotypical characteristics, triclosan concentration from which isolates were obtained and growth kinetics (measurement of the lag time), which served as explanatory variables.

RESULTS AND DISCUSSION

HPLC analysis

The influent samples had high levels (1.488 ppb) of triclosan (Figure 1). According to Reiss et al. (2002), 95% of uses for triclosan are in consumer products and personal care products and end up in wastewater systems. Thus, triclosan in the WWTP of Tlokwe/Potchefstroom could be from pharmaceutical personal care products (PPCPs). It was reported by Chen et al. (2011) that triclosan concentrations between 1 and 10 ppb enter WWTPs. This will be dependent on the usage patterns of PPCPs that contain triclosan. The levels of triclosan in the influent at the Tlokwe WWTP were relatively low. This was even lower during the rainy season, when the level was 0.058 ppb. Such low levels could potentially be ascribed to dilution by the storm water entering the system. Results presented here indicate that 96% of triclosan was removed by the WWTP processes. This is not uncommon, since removal efficiencies of up to 90% had been reported for conventional activated sludge processes (Adolfsson-Erici et al. 2002; Lindström et al. 2002; Singer et al. 2002; Chen et al. 2011). However, whether the triclosan had been degraded by the activated sludge system was not tested. It may be that triclosan was trapped in the sludge. Literature also stipulates that triclosan can react with chlorine through photo-degradation to form end products such as dioxins and dibenzofurans (Aranami & Readman 2007). Further investigation is required to clarify the fate of triclosan in the water at the Tlokwe WWTP.

Triclosan resistant isolates

A total of 44 HPC isolates were obtained. Amongst the 44 isolates, 27 were Gram positive and 17 were Gram negative. Five main genera of bacteria were identified. These included Bacillus (29 isolates), Pseudomonas (eight isolates), Paenibacillus (four isolates), Brevibacillus (one isolate) and Enterococcus (one isolate). Similarity to GenBank for the HPC isolated varied between 81 and 99%; seven of the isolates remained in the 81–96% gap. The isolates with id scores between 81% and 96% can be regarded as potential novel genera or species. Additional classification was not further explored, as this was not the purpose of the study.

Minimum inhibitory concentration

The HPC isolates tested indicated lag times for the control group (0 mg/L triclosan) between 0.5 hours and 7 hours. Lag times at 0.125 mg/L triclosan remained the same as the control or were slightly longer. Bacillus aerius (C15), Bacillus licheniformis (C28) and Bacillus tequilensis (C38) indicated no change in optical density over a period of 24 hours at 1 mg/L triclosan. Since no growth had occurred after a 24-hour period at this concentration, the latter (1 mg/L) was used as the MIC for that isolate. Bacillus aerius (C20), Bacillus thuringiensis (C41) and Pseudomonas xanthomarina (C31) indicated no change in the lag times measured from 0.375 mg/L up to 1 mg/L over 24 hours. This is an indication that the MIC value for these isolates is probably 0.375 mg/L triclosan. Paenibacillus cookii (C33) had the lowest MIC value (0.125 mg/L). It can be speculated that the remaining isolates had a MIC value above 1 mg/L triclosan.

Clear MICs were observed for isolates C15, C28 and C38 (<1 mg/L), C20, C41 and C31 (<0.375 mg/L), and C33 (<0.125 mg/L) and presented in Table 4. Conflicting results were observed for C21, which showed no growth in triclosan concentrations of 0.125 mg/L, 0.375 mg/L and 0.5 mg/L. However, growth was observed at 0.25 mg/L, 0.75 mg/L and 1 mg/L. There were also other examples (Table 5).

Table 4

Lag time (hours) measured from growth curves and MIC value (concentrations are in mg/L)

IsolateID number[0][0.125][0.25][0.375][0.5][0.75][1]
Bacillus aerius C15 24 10 11 11 14 24 
Bacillus aerius C20 6.5 17.5 11.5 24 24 24 24 
Bacillus licheniformis C28 2.5 24 16 24 16 24 
Bacillus tequilensis C21 24 15 24 24 
Bacillus tequilensis C38 2.5 16 16 24 20 24 
Bacillus thuringiensis C41 24 24 24 24 24 
Paenibacillus cookii C33 2.5 24 24 24 24 24 24 
Pseudomonas xanthomarina C31 17 12 24 24 24 24 
IsolateID number[0][0.125][0.25][0.375][0.5][0.75][1]
Bacillus aerius C15 24 10 11 11 14 24 
Bacillus aerius C20 6.5 17.5 11.5 24 24 24 24 
Bacillus licheniformis C28 2.5 24 16 24 16 24 
Bacillus tequilensis C21 24 15 24 24 
Bacillus tequilensis C38 2.5 16 16 24 20 24 
Bacillus thuringiensis C41 24 24 24 24 24 
Paenibacillus cookii C33 2.5 24 24 24 24 24 24 
Pseudomonas xanthomarina C31 17 12 24 24 24 24 
Table 5

Lag time (hours) measured from growth curves and minimum inhibitory concentration value (concentrations are in mg/L).

IsolateID number[0][0.125][0.25][0.375][0.5][0.75][1]
Bacillus aerius C8 2.5 17 7.5 7.5 
Bacillus aerius C17 2.5 15 2.5 15 
Bacillus aerius C22 24 10 10 15 20 
Bacillus cereus C2 0.5 0.5 0.5 0.5 0.5 0.5 
Bacillus cereus C4 
Bacillus cereus C8 2.5 2.5 2.5 2.5 2.5 2.5 2.5 
Bacillus cereus C24 24 
Bacillus licheniformis C47 14 12 14 15 
Bacillus licheniformis C23 0.5 
Bacillus licheniformis C30 16 12 13 15 15 20 
Bacillus safensis C46 12 10 12 
Bacillus siamensis C3 12.5 4.5 10 11.5 12.5 22 
Bacillus stratosphericus C34 
Bacillus subtilis C1 1.5 15 24 15 11 15 15 
Bacillus tequilensis C5 0.5 1.5 0.5 0.5 1.5 0.5 1.5 
Bacillus tequilensis C27 24 24 10 15 
Bacillus thuringiensis C9 1.5 1.5 1.5 1.5 1.5 1.5 1.5 
Bacillus thuringiensis C10 
Bacillus thuringiensis C12 1.5 14 1.5 1.5 1.5 1.5 1.5 
Bacillus thuringiensis C14 0.5 24 
Bacillus thuringiensis C35 1.5 1.5 1.5 1.5 1.5 1.5 1.5 
Bacillus thuringiensis C42 15 11 11 13 
Bacillus weihenstephanensis C25 2.5 2.5 
Brevibacillus parabrevis C6 15 15 12.5 10 
Enterococcus mundtii C16 1.5 1.5 1.5 1.5 1.5 1.5 1.5 
Paenibacillus cookii C7 11 15 
Paenibacillus jamilae C11 
Pseudomonas entomophila C26 15 12 15 16 16 14 
Pseudomonas mosselii C44 18 10 17 15 10 
Pseudomonas mosselii C45 12 13 15 13 
Pseudomonas mosselii C13 0.5 15 5.5 15 11.5 14.5 19.5 
Pseudomonas mosselii C32 15 15 15 24 24 15 
Pseudomonas mosselii C29 
Pseudomonas xanthomarina C40 2.5 18 16 24 24 18 
Unknown C39 2.5 2.5 2.5 2.5 2.5 2.5 2.5 
IsolateID number[0][0.125][0.25][0.375][0.5][0.75][1]
Bacillus aerius C8 2.5 17 7.5 7.5 
Bacillus aerius C17 2.5 15 2.5 15 
Bacillus aerius C22 24 10 10 15 20 
Bacillus cereus C2 0.5 0.5 0.5 0.5 0.5 0.5 
Bacillus cereus C4 
Bacillus cereus C8 2.5 2.5 2.5 2.5 2.5 2.5 2.5 
Bacillus cereus C24 24 
Bacillus licheniformis C47 14 12 14 15 
Bacillus licheniformis C23 0.5 
Bacillus licheniformis C30 16 12 13 15 15 20 
Bacillus safensis C46 12 10 12 
Bacillus siamensis C3 12.5 4.5 10 11.5 12.5 22 
Bacillus stratosphericus C34 
Bacillus subtilis C1 1.5 15 24 15 11 15 15 
Bacillus tequilensis C5 0.5 1.5 0.5 0.5 1.5 0.5 1.5 
Bacillus tequilensis C27 24 24 10 15 
Bacillus thuringiensis C9 1.5 1.5 1.5 1.5 1.5 1.5 1.5 
Bacillus thuringiensis C10 
Bacillus thuringiensis C12 1.5 14 1.5 1.5 1.5 1.5 1.5 
Bacillus thuringiensis C14 0.5 24 
Bacillus thuringiensis C35 1.5 1.5 1.5 1.5 1.5 1.5 1.5 
Bacillus thuringiensis C42 15 11 11 13 
Bacillus weihenstephanensis C25 2.5 2.5 
Brevibacillus parabrevis C6 15 15 12.5 10 
Enterococcus mundtii C16 1.5 1.5 1.5 1.5 1.5 1.5 1.5 
Paenibacillus cookii C7 11 15 
Paenibacillus jamilae C11 
Pseudomonas entomophila C26 15 12 15 16 16 14 
Pseudomonas mosselii C44 18 10 17 15 10 
Pseudomonas mosselii C45 12 13 15 13 
Pseudomonas mosselii C13 0.5 15 5.5 15 11.5 14.5 19.5 
Pseudomonas mosselii C32 15 15 15 24 24 15 
Pseudomonas mosselii C29 
Pseudomonas xanthomarina C40 2.5 18 16 24 24 18 
Unknown C39 2.5 2.5 2.5 2.5 2.5 2.5 2.5 

Overall, the MICs of the organisms indicate the ability to survive in the presence of varying concentrations of triclosan. The MICs of most of the isolates were greater than 1 mg/L triclosan. Different organisms react differently to a specific concentration of triclosan, and therefore the precise concentration needs to be determined to ensure correct application of antibiotics (McMurry et al. 1998). Bacteria are able to use efflux pumps, and in the presence of unwanted substances more efflux pumps can be activated (McBain & Gilbert 2011). The more the bacteria are exposed to the antimicrobials, the more likely they become to acquire resistance mechanisms (Rodriquez et al. 2007), and it was stated by Aiello & Larson (2003) that triclosan acts as a substrate for multi-drug efflux pumps and selection of pump mutations.

Cross-resistance to antibiotics

Eighty per cent of Gram-positive isolates were resistant to penicillin G and 68% of all isolates were resistant to amoxicillin. Only 9% of all isolates were resistant to streptomycin. Thirty-four per cent of the isolates tested had reduced inhibition zone measurements to tetracycline and 30% to erythromycin. Antibiotic susceptibility data (inhibition zone values) and parameters obtained from the growth curves were analysed by RDA. Figure 2 is an example of one of the RDAs and the legends contain the parameters used.
Figure 2

RDA triplot – antibiotic susceptibility and triclosan effects on bacterial isolates (black arrows indicate antibiotics used, e.g. PG10 – penicillin G, VA30 – vancomycin, A10 – amoxycillin, E15 – erythromycin, S25 – streptomycin, TM2.5 – trimethoprim, T30 – tetracycline. Red arrows indicate other variables, e.g. Gram – Gram staining, MIC – minimum inhibitory concentration, Cetr – cetrimide agar, Morph – cell morphology, Endo – endospore, C[nr] – HPC bacteria).

Figure 2

RDA triplot – antibiotic susceptibility and triclosan effects on bacterial isolates (black arrows indicate antibiotics used, e.g. PG10 – penicillin G, VA30 – vancomycin, A10 – amoxycillin, E15 – erythromycin, S25 – streptomycin, TM2.5 – trimethoprim, T30 – tetracycline. Red arrows indicate other variables, e.g. Gram – Gram staining, MIC – minimum inhibitory concentration, Cetr – cetrimide agar, Morph – cell morphology, Endo – endospore, C[nr] – HPC bacteria).

Isolates resistant to vancomycin and penicillin G (cell-wall synthesis inhibitors) are grouped in the first and second quadrant of the RDA, which then correlates to the increase in the applied triclosan concentration. This correlation is indicated with a red circle on the RDA (Figure 2). Isolates susceptible to vancomycin and penicillin were scattered across the RDA and indicated no correlation with triclosan concentration. These patterns were not as apparent with erythromycin and tetracycline (protein synthesis inhibitor), trimethoprim (antimetabolite) and streptomycin (aminoglycoside), which can be observed in the third quadrant.

Cross-resistance to antibiotics in the presence of triclosan

At low concentrations (0 mg/L to 0.375 mg/L) a synergistic effect was observed for Bacillus spp. (Table 1) in the presence of triclosan and erythromycin. For higher triclosan concentrations (0.375 mg/L to 1 mg/L) results were conflicting, as both synergism and antagonism were observed. Synergistic effects were observed when Bacillus spp. were exposed to low triclosan concentrations (0 mg/L to 0.375 mg/L) in the presence of vancomycin. Antagonistic effects were observed at high triclosan concentrations (0.375 mg/L to 1 mg/L) and in the presence of vancomycin. This bacterial genus (Bacillus spp.) also displayed similar effects to triclosan and penicillin G concentrations.

The Paenibacillus spp. group (Table 2) indicated that there was generally a ‘no effect’ trend compared with the conflicting synergistic or antagonistic effects, but more synergy could be observed at lower triclosan concentrations (0 mg/L to 0.375 mg/L) and antagonism at higher triclosan concentrations (0.375 mg/L to 1 mg/L) and in the presence of vancomycin. The Pseudomonas spp. group (Table 3) indicated synergy at lower triclosan concentrations (0 mg/L to 0.375 mg/L) in the presence of erythromycin and antagonism at higher triclosan concentrations (0.375 mg/L to 1 mg/L).

Overall, it was demonstrated that at low concentrations triclosan had a synergistic effect on antibiotics action. However, at high triclosan concentrations the effect was the opposite, i.e. antagonistic. This could be due to the fact that resistance development rate is increased in the presence of more than one antimicrobial. McMurry et al. (1998) explained that sub-lethal concentrations of triclosan result in microbial resistance. A study by Brenwald & Fraise (2003) indicated that at low concentrations, triclosan appears to be bacteriostatic and that isolates of MRSA with a low triclosan resistance had an MIC value between 2 mg/L and 4 mg/L. However, Tuffnell et al. (1987) stated that MRSA used in their study was sensitive to lower concentrations of triclosan (0.1–2 mg/L).

Literature indicates that triclosan acts as a biocide with multiple cytoplasmic and membrane targets. There are two specific cellular targets: firstly, a single mutation by blocking the lipid synthesis inducing the mutation in the fabI gene. The fabI gene encodes the enol reductase for fatty acid synthesis (Brenwald & Fraise 2003; McBain & Gilbert 2011). Secondly, at low concentrations of triclosan, bacteria might use efflux pumps to transfer these substances out of the cell (Escalada et al. 2005). Pseudomonas aeruginosa is intrinsically resistant to triclosan due to the presence of efflux pumps that are induced by the presence of the biocide. Additional efflux pumps could be installed during higher exposure concentrations (Schweizer 2001; McBain & Gilbert 2011). Similar mechanisms could thus exist in other bacterial species such as the ones isolated in the present study. In addition, the present study also demonstrated that resistance towards selected antibiotics was enhanced in the presence of triclosan. It is possible that efflux pumps could be responsible for this observation.

Due to continuous exposure to sub-application levels of antimicrobials such as triclosan, the probability exists that environmental bacteria may be exposed to selective pressures resulting in the maintenance and spread of antimicrobial resistance characteristics (Rodriquez et al. 2007). According to Aiello & Larson (2003), triclosan acts as a substrate for multi-drug efflux pumps and selection of pump mutations. Furthermore, Rodriquez et al. (2007) emphasized the importance of the correct use of antimicrobials and that the applied concentration of these products is of great importance. These authors also argued that incorrect concentration use will result in antimicrobial resistance development (Rodriquez et al. 2007). The results obtained in the present study are thus supported by findings reported in previous work.

Conclusions

Triclosan tolerant heterotrophic plate count bacteria were isolated at the effluent of the Tlokwe WWTP in Potchefstroom, South Africa. These bacterial species are resistant to high concentrations of triclosan and were able to grow in the presence of triclosan up to concentrations of 0.5 mg/L. Five main genera were identified, namely Bacillus, Paenibacillus, Pseudomonas, Brevibacillus and Enterococcus. However, a large number (82%) of the HPC bacteria isolated from the WWTP had MICs greater than 1 mg/L triclosan. Three isolates had a MIC of 1 mg/L, three had a MIC of 0.375 mg/L and one isolate indicated a MIC of 0.125 mg/L triclosan. It is thus recommended that further investigation be conducted to determine the precise MIC of each isolate.

Antibiotic resistance patterns observed indicated that resistance to selected antibiotics is increased in the presence of high concentrations (0.5 mg/L to 1 mg/L) of triclosan. This was particularly the case with the cell wall synthesis inhibitor antibiotics used.

Triclosan levels were reduced by the Tlokwe WWTP. However, some residual triclosan was present in the effluent that was discharged into the environmental water. Such levels may be sufficient to act as selective pressure for the maintenance of triclosan resistant bacteria emanating from the sewage treatment processes. Further studies need to be conducted to find possible methods to remove triclosan and other antimicrobial agents completely from WWTP before the water is released into the environment.

ACKNOWLEDGEMENTS

The authors would like to thank Ms L. Bothma for assistance with sampling at the WWTP, the National Research Foundation of South Africa for a bursary to IC, and Mr J. Hendricks with assistance with HPLC analysis, as well as Dr K. Jordaan and Ms H. Venter for assistance with sequencing and molecular work.

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