Abstract

Exposure to antibiotics, biocides, chemical preservatives, and heavy metals in different settings such as wastewater treatment plants (WWTPs) may apply selective pressure resulting in the enrichment of multiple resistant, co- and cross-resistant strains of bacteria. The purpose of this study was to identify and characterize potentially pathogenic triclosan (TCS) - and/or, chloroxylenol (PCMX) tolerant bacteria from sewage and river water in the North-West, Potchefstroom, South Africa. Several potential pathogens were identified, with Aeromonas isolates being most abundant. Clonal relationships between Aeromonas isolates found at various sampling points were elucidated using ERIC-PCR. Selected isolates were characterized for their minimum inhibitory concentrations against the biocides, as well as antibiotic resistance profiles, followed by an evaluation of synergistic and antagonistic interactions between various antimicrobials. Isolates were also screened for the presence of extracellular enzymes associated with virulence. High-performance liquid chromatography revealed the presence of both biocides in the wastewater, but fingerprinting methods did not reveal whether the WWTP is the source from which these organisms enter the environment. Isolates exhibited various levels of resistance to antimicrobials as well as several occurrences of synergy and antagonisms between the biocides and select antibiotics. Several isolates had a very high potential for virulence but further study is required to identify the specific virulence and resistance genes associated with the isolates in question.

INTRODUCTION

Multi-drug resistant bacteria remain a major health concern, driven by selection pressure from antibiotics as well as co-selection due to exposure to biocides, chemical preservatives, and heavy metals (Wales & Davies 2015). Wastewater treatment plants (WWTPs) are sites where bacteria may be exposed to substances applying selective pressure and thus select for resistant strains which may disseminate into the receiving river systems (Hrenovic et al. 2017). Large amounts of personal care products (PCPs) including antimicrobials frequently enter WWTPs, which in turn act as a point source of pollution from which these substances can enter the environment along with bacteria exposed to these substances during the wastewater treatment process (Capkin et al. 2017).

Triclosan (TCS) and chloroxylenol (PCMX) are both broad-spectrum antimicrobial agents often used in various PCPs the majority of which end up in municipal wastewater (Capkin et al. 2017). Exposure to TCS leading to increased resistance and resistance to several antibiotics has previously been reported (Chuanchuen et al. 2001). Chloroxylenol has not been as extensively studied as TCS, but it is a very widely used antimicrobial that has been shown to be present in wastewater effluent as well as in the receiving river systems. Thus the possibility of long-term exposure to this compound may drive selective enrichment of antimicrobial resistant strains of bacteria (Kasprzyk-Hordern et al. 2009).

Identifying anthropogenic inputs contributing to the spread of resistant bacteria, and resistance genes, will aid in developing strategies to combat antibiotic resistance (Romero et al. 2017). A large portion of South Africa's population still utilize untreated water leading to an increased risk of infection due to waterborne pathogens, and it is therefore important to further examine any direct connections between antibiotic and biocide resistance and whether the presence of these biocides can possibly lead to selection for multi-drug resistant potentially pathogenic bacteria (Momba et al. 2006).

MATERIALS AND METHODS

Sample collection

For microbiological tests water was sampled at the WWTP plant in the North-West province, South Africa. Samples were collected at the treatment plant pre- and post-chlorination, and at the wetlands outflow through which the effluent flows before entering the receiving river. An up- and downstream sample was also collected from the receiving river. Samples were collected in triplicate, stored on ice and processed immediately. Water samples for high-performance liquid chromatography (HPLC) analyses were collected from all sites except the wetlands outflow. In total two sampling runs were included, one at the end of the rainy season and one at the end of the dry season. Water samples (1 L) were collected in triplicate using Schott bottles cleaned with methanol and double distilled water before sampling.

High-performance liquid chromatography

Horizon Technology (NH, USA) provided a method for the determination of pharmaceuticals and PCPs in water by automated solid phase extraction. The system used was the Horizon Technology SPE-DEX® 4790 Automated Extraction System, and the Envision® Platform Controller. Atlantic™ HLB-L Disks were used for extraction purposes.

Sample preparation and solid phase extraction (SPE) were performed according to the Horizon Technologies method 4790 (NH, USA). Following SPE the eluted samples were concentrated using a TurboVap II (Caliper Lifesciences, USA). Concentrated samples were resuspended in 75% acetonitrile to a final volume of 1 mL and syringe filtered before injection into the HPLC. HPLC with a UV detector was used with a 250 × 4.6 Venusil XBP C18 (2) 5u column. The mobile phase was made up of 75% acetonitrile, 10 μl of the sample was injected into the column at 25 °C and the wavelength was set to 280 nm (Zhou et al. 2009).

Isolation and screening for biocide tolerant potential pathogens

For the initial screening, nutrient agar (Merck, Germany) was supplemented with either TCS (0.25, 0.375, 0.5 and 1 mg/L) or PCMX (10, 20, 30 and 40 mg/L). Water samples (100 μl) were plated onto the biocide-containing nutrient agar (Merck, Germany) by the spread plate method, and colonies observed were selected for further analysis based on morphological features. Isolates were inoculated onto blood agar to test for haemolysis, as a screening process for potential pathogens (Ahmad et al. 2010). Isolates testing positive for haemolysis were streaked onto nutrient agar containing the same concentration of TCS or PCMX that they were isolated from to obtain pure cultures. Isolates not testing positive for either alpha or beta haemolysis were discarded. Isolates retained were labelled as follows: T (Triclosan) or C (Chloroxylenol), which indicated the supplement added to the nutrient agar followed by the concentration. Sampling points were indicated as either Pre (Pre-chlorination), Post (Post-chlorination), U (Upstream), W (Wetland), or D (Downstream) and numbers were added to represent the colony obtained from the original plate.

Identification of isolates

For identification purposes, DNA extraction was carried out according to the manufacturer's instruction using the Chemagic DNA Bacteria Kit (Perkin Elmer, Germany). Extraction was followed by polymerase chain reaction (PCR) amplification of the 16S rRNA region using universal primers 27F and 1492R. The 16S amplicons were then sequenced by Sanger sequencing (ABI 3130 genetic analyser, Applied Biosystems, USA) (Jiang et al. 2006).

DNA fingerprinting

PCR amplification of the enterobacterial repetitive intergenic consensus (ERIC) sequences was completed to determine the clonal relationship of Aeromonas isolates. Primers which are specific for ERIC-sequences bind to several loci yielding a unique DNA fingerprint. Amplification of the ERIC sequences was done using primers and thermal cycling conditions described by Szczuka & Kaznowski (2004). The final gel product was analysed and clustering analysis was performed with the aid of Phoretix 1D pro (Total Labs: Version 1.0). Clustering analysis was based on the Dice similarity coefficient and the unweighted pair group method with arithmetic mean (UPGMA).

Extracellular enzyme production

Media containing sub-rates specific for certain enzymes to assess extracellular enzyme production was prepared using the media and according to protocols found in Table 1.

Table 1

Media preparation for extracellular enzyme tests

Extracellular enzyme Media Reference 
Proteinase Mueller Hinton Agar (Oxoid, England) + 3% skimmed milk (Merck, Germany) Patidar et al. (2013)  
Gelatinase Tryptone soya agar + 3% gelatine Pavlov et al. (2004); Patidar et al. (2013
Lipase Tryptone soya agar (Merck, Germany) supplemented with 1% Tween-80 Georgescu et al. (2016)  
Lecithinase Tryptone soya agar (Merck, Germany) supplemented with 100 mL 50% egg yolk emulsion Georgescu et al. (2016
DNase DNase agar (Oxoid, UK) Pavlov et al. (2004
Hyaluronidase and chondroitinase Brain heart infusion broth
Noble agar (Conda, Spain), supplemented with either 4 mg/mL chondroitin sulphate (Roth, Germany) or 2 mg/mL hyaluronic acid (Merck, Germany), along with 5% bovine albumin fraction V (Hyclone Labs, USA) 
de Assis et al. (2003
Extracellular enzyme Media Reference 
Proteinase Mueller Hinton Agar (Oxoid, England) + 3% skimmed milk (Merck, Germany) Patidar et al. (2013)  
Gelatinase Tryptone soya agar + 3% gelatine Pavlov et al. (2004); Patidar et al. (2013
Lipase Tryptone soya agar (Merck, Germany) supplemented with 1% Tween-80 Georgescu et al. (2016)  
Lecithinase Tryptone soya agar (Merck, Germany) supplemented with 100 mL 50% egg yolk emulsion Georgescu et al. (2016
DNase DNase agar (Oxoid, UK) Pavlov et al. (2004
Hyaluronidase and chondroitinase Brain heart infusion broth
Noble agar (Conda, Spain), supplemented with either 4 mg/mL chondroitin sulphate (Roth, Germany) or 2 mg/mL hyaluronic acid (Merck, Germany), along with 5% bovine albumin fraction V (Hyclone Labs, USA) 
de Assis et al. (2003

Antimicrobial susceptibility

The following section will describe the tests that were conducted to evaluate antimicrobial susceptibility: these include tests to evaluate antibiotic resistance profiles, minimum inhibitory concentrations (MICs) to the selected biocides, and synergistic/antagonistic effects between the selected antibiotics and biocides in question.

Assay for cross-resistance to antibiotics

Cross-resistance to antibiotics was assessed using the Kirby–Bauer disk diffusion susceptibility test protocol. Antibiotics selected included: vancomycin (30 μg), kanamycin (30 μg), trimethoprim (5 μg), oxytetracycline (30 μg), amoxicillin (10 μg) and chloramphenicol (30 μg). Isolates were spread out using the spread plate method onto Mueller–Hinton agar (Merck, Germany). Inhibition zones were measured after 24 hours and divided into three groups, classifying the isolates as resistant, susceptible or inhibited, by using the Performance Standards for Antimicrobial Disk Susceptibility Tests (CLSI 2015).

Minimum inhibitory concentration

Minimum inhibitory concentrations (MICs) were conducted to determine lag time measurement, and TCS and PCMX MICs. Selected isolates showing similar antibiotic resistance patterns were incubated for 24 hours at 37 °C in Mueller–Hinton broth (MHB), at different concentrations of TCS (0, 0.125, 0.25, 0.5, 0.75, 1 and 2 mg/L) or PCMX (0, 10, 20, 30, 50, 75, and 100 mg/L). Bacterial growth was assessed by observing the turbidity of the medium by using a microwell plate reader (BioTek Power Wave HT) (Kaya & Özbilge 2012).

Checkerboard assay

A checkerboard assay was designed to determine if there were any synergistic or antagonistic effects between antibiotics at subinhibitory concentrations of TCS or PCMX. Concentrations and isolate to be tested were determined by examining the results of antibiotic resistance profiles according to the CLSI standard as well as MICs to the biocides in question (CLSI 2015). Isolates were thus inoculated in MHB, at different concentrations of TCS (0, 0.25, 0.5, 1 and 2 mg/L), and PCMX (0, 10, 20, 30 and 40 mg/L), with the addition of antibiotics at varying concentrations (0, 1, 2, 4, 8, 16, 32 and 64 μg/mL). Bacterial growth was assessed by the observation of visual growth after isolates were incubated for 24 hours at 37 °C.

Pathogenic potential

The outcomes of tests to determine antibiotic resistance profiles and extracellular enzyme production were combined to create a pathogenic potential index (Table 2). The goal of this index was to determine and compare the degree to which these organisms may potentially cause disease (Horn et al. 2016). Isolates exhibiting haemolysis were allocated scores of 1 for alpha and 1.2 for beta-haemolysis. Beta-haemolysis causes the complete lysis of red blood cells and is thus attributed a more significant score, as it may be regarded as having more severe effects on the host (Pakshir et al. 2013). A score of 1 was allocated for a positive test for the presence of each extracellular enzyme. Scores were also assigned based on antibiotic resistance profiles; if an isolate tested resistant, a score of 1 was assigned, and a score of 0.5 was assigned if the isolated was inhibited.

Table 2

Identification and virulence characteristics of each isolate

Isolates Haemolysis Virulence characteristics
 
Antibiotic resistance
 
Pathogen score 
Le Hy Ch Dn Ge Pr Li V30 A10 K30 C30 T5 O30 
Pathogen weights: β = 1.2; α = 1 X = 1 R = 1; I = 0.5; NA = 0.2  
T-0.5-Pre-1B(MG015902) A. caviae β  NA 8.2 
T-1-U-3(MG015903) A. caviae β NA 8.9 
T-1-Pre-2(MG015904) A. veronii β   NA 7.2 
T-1-Pre-3(MG015905) A. veronii β  NA 8.4 
T-1-Post-4(MG015906) A. veronii β  NA 7.4 
T-1-W-3(MG015907) A. veronii β NA 8.9 
T-1-D-6(MG015910) A. veronii β   NA 8.4 
T-1-D-8(MG015911) A. veronii β   NA 6.4 
C-30-D-3(MG015912) A. veronii β  NA 8.9 
C-30-D-5(MG015913) A. veronii β NA 8.9 
C-10-D-2B(MG015914) A. veronii β NA 8.4 
C-40-W-1(MG015908) A. veronii β  NA 8.4 
C-40-W-2(MG015909) A. veronii β  NA 7.4 
C-10-D-3(MG015917) B. cereus β    7.7 
T-0.5-Post-4(MG015915) B. cereus β   
C-10-Post-4(MG015916) B. cereus α    7.5 
C-40-U-1(MG015919) B. subtilis β   5.2 
C-40-Pre-5(MG015929) K. oxytoca β      NA 3.4 
C-20-Post-2(MG015932) P. alcaligenes β       NA 3.2 
C-40-Post-2(MG015931) P. alcaligenes β      NA 5.4 
C-20-Post-4(MG015933) P. alcaligenes α       NA 1.2 
T-0.25-Pre-1(MG015930) P. aeruginosa β  NA 10.4 
T-0.5-Pre-1A(MG015934) P. monteleii β       NA 4.4 
Isolates Haemolysis Virulence characteristics
 
Antibiotic resistance
 
Pathogen score 
Le Hy Ch Dn Ge Pr Li V30 A10 K30 C30 T5 O30 
Pathogen weights: β = 1.2; α = 1 X = 1 R = 1; I = 0.5; NA = 0.2  
T-0.5-Pre-1B(MG015902) A. caviae β  NA 8.2 
T-1-U-3(MG015903) A. caviae β NA 8.9 
T-1-Pre-2(MG015904) A. veronii β   NA 7.2 
T-1-Pre-3(MG015905) A. veronii β  NA 8.4 
T-1-Post-4(MG015906) A. veronii β  NA 7.4 
T-1-W-3(MG015907) A. veronii β NA 8.9 
T-1-D-6(MG015910) A. veronii β   NA 8.4 
T-1-D-8(MG015911) A. veronii β   NA 6.4 
C-30-D-3(MG015912) A. veronii β  NA 8.9 
C-30-D-5(MG015913) A. veronii β NA 8.9 
C-10-D-2B(MG015914) A. veronii β NA 8.4 
C-40-W-1(MG015908) A. veronii β  NA 8.4 
C-40-W-2(MG015909) A. veronii β  NA 7.4 
C-10-D-3(MG015917) B. cereus β    7.7 
T-0.5-Post-4(MG015915) B. cereus β   
C-10-Post-4(MG015916) B. cereus α    7.5 
C-40-U-1(MG015919) B. subtilis β   5.2 
C-40-Pre-5(MG015929) K. oxytoca β      NA 3.4 
C-20-Post-2(MG015932) P. alcaligenes β       NA 3.2 
C-40-Post-2(MG015931) P. alcaligenes β      NA 5.4 
C-20-Post-4(MG015933) P. alcaligenes α       NA 1.2 
T-0.25-Pre-1(MG015930) P. aeruginosa β  NA 10.4 
T-0.5-Pre-1A(MG015934) P. monteleii β       NA 4.4 

Ch, chondroitinase; Dn, DNase; Hy, hyaluronidase; Le, lecithinase; Li, lipase; Pr, proteinase; Ge, gelatinase; V30, vancomycin; A10, amoxicillin; K30, kanamycin; C30, chloramphenicol; T5, trimethoprim; O30, oxytetracycline.

RESULTS AND DISCUSSION

HPLC analysis

TCS and PCMX have both previously been described as being extensively biodegraded, and removed during the wastewater treatment process, but this is highly dependent on the operation of the WWTP (Yueh & Tukey 2016). Effluent and up- and downstream samples did not indicate the presence of either TCS or PCMX. Influent samples had an average concentration of 2.67 μg/L ±0.95 (end of wet season) and 12.74 ± 8.43 μg/L (end of the dry season) for TCS; and 27.2 ± 8.39 μg/L (end of wet season) and 105.44 ± 29.19 μg/L (end of the dry season) for PCMX respectively. Biocide concentrations at the end of the dry season were higher than those taken at the end of the wet season. During the wet season, rainfall may dilute PCPs. The higher temperatures occurring during the wet season may also play an important role in improved removal of PCPs; thus lower concentrations of PCPs in the influent may be due to improved rates of biodegradation (Sui et al. 2011). Current results suggest that TCS and PCMX are effectively removed by the WWTP, but their presence in the influent of the WWTP should still remain a concern. Bacteria entering the WWTP are exposed to these antimicrobials during the process of entering the WWTP, and possibly during certain stages of the wastewater treatment process.

Triclosan and/or chloroxylenol resistant potentially pathogenic isolates

Biocide tolerant bacteria were found at all sampling points. Thirty-five isolates with an average ID of 100% were identified by sequencing of the 16S rRNA region, and these included Klebsiella, Bacillus, Pseudomonas, Aeromonas, Exiguobacterium and Shewanella spp. The 16S rRNA gene sequences were submitted to GenBank and given accession numbers (Table 2). Of the isolates identified by 16S sequencing Aeromonas, Pseudomonas, Bacillus and Klebsiella spp. are well described opportunistic pathogens.

Among the Pseudomonas spp. found, P. aeruginosa is considered to be the most important species as it is difficult to frequently attach pathogenic significance to any of the other Pseudomonas species. P. aeruginosa exhibits the most consistent resistance to antimicrobials of all medically important bacteria (Guida et al. 2016). Only one Klebsiella isolate was obtained during the course of this study. According to Hagiwara et al. (2013), Klebsiella are opportunistic pathogens involved in a variety of diseases such as bacteraemia. K. oxytoca has been isolated to a much lesser degree than various other Klebsiella spp. from human clinical specimens, but there have been several cases of infection where K. oyxtoca has been identified as the causative agent. Of the Bacillus isolates found, three were identified as Bacillus cereus, and one as Bacillus subtilis. Both Bacillus cereus and subtilis are known to produce infection, especially in immunocompromised individuals, with B. cereus being said to be the most likely to cause opportunistic infection (Ahmad et al. 2010).

A total of 11 isolates were identified as either Aeromonas veronii or Aeromonas caviae. These emerging pathogens are uncommon, but highly virulent causes of infections. Human infections caused by Aeromonas most often occur in the community settings, but are becoming more frequent in healthcare settings ranging from wound infections, and diarrhoea to septicaemia in immunocompromised patients (Janda & Abbott 2010; Chen et al. 2014).

DNA fingerprinting

A large portion of South Africa's population still rely on surface water as their primary source of water, and many still utilize untreated water (Momba et al. 2006). It was thus important during the course of this study to determine if the WWTP is the source of the Aeromonas isolates obtained at various sampling points. DNA fingerprinting by means of ERIC-PCR has been described as an effective method to determine the clonal relationship and genetic similarity between isolates of the same species, and has previously been used to type Aeromonas spp. (Szczuka & Kaznowski 2004).

Figure 1 represents the ERIC fingerprint pattern and cluster analyses obtained for Aeromonas isolates. ERIC-PCR yielded two to more than 18 PCR products, ranging in size from around 100 bp to over 10,000 bp. According to ERIC-PCR analysis, seven major clusters labelled A–G were defined among Aeromonas (A.v) isolates. Based on visual and clustering analysis it is clear that the Aeromonas isolates found during the course of this study do not share any clonal relation. The visual and clustering analysis performed on select isolates may indicate various strains but that does not rule out the possibility that these isolates may share common ancestry (Berglund 2015). Visual and clustering analysis did not yield any conclusive results, but the fact that Aeromonas spp. were found at pre- and post-chlorination sampling points, as well as downstream from the WWTP, indicates that the possibility remains that the WWTP is the source from which these organisms enter the environment.

Figure 1

Cluster analysis by ERIC-PCR fingerprint of 11 Aeromonas veronii isolates and two Aeromonas caviae isolates. Clustering analysis was performed with the aid of Phoretix 1D pro (Total Labs: Version 1.0) and based on Dice similarity coefficient and the unweighted pair group method with arithmetic mean (UPGMA).

Figure 1

Cluster analysis by ERIC-PCR fingerprint of 11 Aeromonas veronii isolates and two Aeromonas caviae isolates. Clustering analysis was performed with the aid of Phoretix 1D pro (Total Labs: Version 1.0) and based on Dice similarity coefficient and the unweighted pair group method with arithmetic mean (UPGMA).

Extracellular enzyme production

All isolates were examined for haemolytic activity, and the presence of extracellular enzymes associated with virulence (Pavlov et al. 2004). All Bacillus cereus isolates tested positive for the presence of three or more extracellular enzymes, while the B. subtilis isolate tested positive for four. The pathogenicity of B. cereus is said to be intimately related to the production of tissue-destructive extracellular enzymes, such as proteases, phospholipases and haemolysins (Bottone 2010). Pseudomonas spp. tested positive for the presence of both the most and least amount of extracellular enzymes. The pathogenicity of Pseudomonas spp. has previously been stated to be dependent on the secretion of various virulence factors such as proteases and elastases, especially during the early stages of infection (van ‘t Wout et al. 2015). The Klebsiella isolate tested positive for only one extracellular enzyme. According to Pereira & Vanetti (2015), the primary factors contributing to Klebsiella spp. pathogenicity include the production of siderophores, fimbrial adhesins, serum resistance properties, and particular capsular types. Aeromonas isolates tested positive for protease, gelatinase and DNase activity, 11 tested positive for lipase and chondroitinase activity, ten tested positive for lecithinase and none tested positive for the presence of hyaluronidase. Aeromonas spp. have previously been described to produce a broad range of extracellular enzymes, many of which contribute to pathogenicity; despite the presence of several virulence factors the virulence mechanisms of Aeromonas spp. still remain vague (Igbinosa et al. 2012).

Antimicrobial susceptibility

Assay for cross-resistance to antibiotics

When examining the Pseudomonas spp. isolates obtained, the P. monteleii isolate showed resistance or intermediate resistance to all antibiotics tested except kanamycin, while the P. aeruginosa isolate showed resistance to all antibiotics tested. Multidrug-resistance to amoxicillin, tetracycline, chloramphenicol, trimethoprim and aminoglycosides among various strains of P. aeruginosa has been well documented (Ahmad et al. 2010). Multidrug-resistance among P. aeruginosa strains has previously been attributed to Mex drug efflux pumps, AmpC beta-lactamase and the porin OprD (Dumas et al. 2006). Efflux systems have been said to contribute significantly to multidrug-resistance among P. aeruginosa isolates, and several efflux systems of the resistance nodulation division (RND) family have been well categorized (Henrichfreise et al. 2007). The P. alcaligenes isolate obtained showed resistance to amoxicillin, and intermediate resistance to both trimethoprim and oxytetracycline. According to Arslan et al. (2011) several Pseudomonas spp. show resistance to trimethoprim, but there is no direct reference to P. alcaligenes isolates exhibiting resistance to this drug.

B. cereus isolates showed resistance to amoxicillin and trimethoprim, and varying levels of resistance to vancomycin, kanamycin and oxytetracycline, while the B. subtilis isolate found showed resistance to none of the antibiotics tested. B. cereus is known to express marked resistance to penicillin and other beta-lactam antibiotics (Bottone 2010). The resistance of B. cereus to several other antibiotics such as cephalosporins, trimethoprim, chloramphenicol, vancomycin, aminoglycosides and tetracycline has also previously been reported (Turnbull et al. 2004). Efflux mechanisms have also said to be present in certain Bacillus spp., and may thus also contribute to multiple drug resistance (Li & Nikaido 2009). The K. oxytoca isolate found during this study exhibited resistance only to oxytetracycline. It has previously been documented that the majority of K. oxytoca strains produce K1 extended-spectrum beta-lactamase (Arakawa et al. 1989). According to Fenosa et al. (2009), K. oxytoca is often resistant to multiple antibiotics, including tetracycline, and they go on to state that these effects are most likely due to efflux mechanisms such as the AcrAB efflux mechanisms, and a Tolc-like protein.

As indicated in Table 2, all Aeromonas isolates except one showed resistance to amoxicillin, and varying resistance could be seen to oxytetracycline and trimethoprim. According to Ahmad et al. (2010), resistance to penicillin and cephalosporin are not unusual and most strains show susceptibility to tetracycline with variable susceptibility to aminoglycosides. Trimethoprim resistance has been documented among Aeromonas spp. due to the action of cassette-borne resistance genes such as drfA and drfB located in class 1 integrons (Kadlec et al. 2011). Multidrug non-susceptible patterns among Aeromonas spp. including A. veronii and A. caviae are not uncommon and studies have indicated varying resistance patterns to several antibiotics. A study by Odeyemi & Ahmad (2017) also found that Aeromonas spp. exhibit resistance to multiple antibiotics including kanamycin, oxytetracycline, trimethoprim and chloramphenicol. Efflux mechanisms responsible for resistance have been documented in Aeromonas spp. and may contribute to resistance to multiple antibiotics. Resistance profiles, in general, seem to depend largely on the particular aquatic environment but it is evident that Aeromonas spp. may exhibit resistance to multiple antibiotics. Resistance may also be conferred by plasmids carrying a number of different determinants contributing to antimicrobial resistance (Piotrowska & Popowska 2015).

Minimum inhibitory concentration

Biocide concentration is said to be one of the most important factors regarding its effectiveness, and several reports on the emergence of biocide resistance are based on the determination of MICs. Previous studies have indicated the occurrence of TCS resistance in microorganisms including some of clinical concern, contributing to the concern that TCS resistance may contribute to a decrease in susceptibility of clinically important antimicrobials possibly due to co-resistance, or cross-resistance mechanisms (Yazdankhah et al. 2006). Isolates showing similar patterns of antibiotic susceptibility were selected to determine MICs. Isolates were grouped according to antibiotic susceptibility patterns and one isolate from each group was selected for MICs. Thus, in total nine isolates were selected for a determination of MICs. In the case of TCS, lag times varied between 0.5 and 8.5 hours; thereafter lag times varied or remained the same. It can thus be assumed that all isolates had an MIC value above 2 mg/L TCS. The isolates incubated with PCMX indicated lag times for the control group between 0.5 and 16.5 hours, after which lag times varied, or remained the same. The majority of isolates indicated no change in optical density over 24 hours when exposed to 50, 75 and 100 mg/L of PCMX, indicating an average MIC for PCMX between 30 and 50 mg/L (Table 3). By examining Table 3 a pattern of fluctuation between the average observed lag times as biocide concentrations increased was seen for various isolates (highlighted in bold), suggesting the possible induction of an efflux related system to expel the biocide from the cell (Jeannot et al. 2005). In the cases where no induction effect was evident a dose-related increase in lag time can be observed.

Table 3

Lag times observed

Isolate group ID TCS
 
PCMX
 
0.125 0.25 0.5 0.75 10 20 30 50 75 100 
T-1-Pre-2; T-1-Pre-3; T-1-Post-4 A. veronii 8.5 13.5 10 15 12.5 14 – 16.5 6.5 16.5 10 – – – 
T-1-W-3; C-40-W-1; C-40-W-2 A. veronii 0.5 0.5 0.5 0.5 0.5 0.5 0.5 – – – 
T-1-D-6 A. veronii 11.5 14 11 7.5 7.5 16 – – – 
T-1-D-8; C-30-D-3; C-30-D-5; C-10-D-2B A. veronii 0.5 0.5 0.5 0.5 0.5 0.5 0.5 7.5 7.5 7.5 7.5 – – – 
T-0.5-Pre-1B; T-1-U-3; C-10-D-2B A. caviae 1.5 1.5 1.5 6.5 6.5 6.5 7.5 6.5 – – – 
T-0.5-Pre-1A P. monteleii 1.5 1.5 1.5 1.5 0.5 1.5 1.5 6.5 – – 
T-0.25-Pre-1 P. aeruginosa 1.5 1.5 1.5 2.5 2.5 2.5 1.5 – – – 
C-40-Post-2; C-20-Post-2; C-20-Post-4 P. alcaligenes 0.5 11.5 0.5 – – – 
T-0.5-Post-4; C-10-D-3 B. cereus 0.5 2.5 2.5 2.5 0.5 1.5 0.5 0.5 0.5 0.5 – – – 
Isolate group ID TCS
 
PCMX
 
0.125 0.25 0.5 0.75 10 20 30 50 75 100 
T-1-Pre-2; T-1-Pre-3; T-1-Post-4 A. veronii 8.5 13.5 10 15 12.5 14 – 16.5 6.5 16.5 10 – – – 
T-1-W-3; C-40-W-1; C-40-W-2 A. veronii 0.5 0.5 0.5 0.5 0.5 0.5 0.5 – – – 
T-1-D-6 A. veronii 11.5 14 11 7.5 7.5 16 – – – 
T-1-D-8; C-30-D-3; C-30-D-5; C-10-D-2B A. veronii 0.5 0.5 0.5 0.5 0.5 0.5 0.5 7.5 7.5 7.5 7.5 – – – 
T-0.5-Pre-1B; T-1-U-3; C-10-D-2B A. caviae 1.5 1.5 1.5 6.5 6.5 6.5 7.5 6.5 – – – 
T-0.5-Pre-1A P. monteleii 1.5 1.5 1.5 1.5 0.5 1.5 1.5 6.5 – – 
T-0.25-Pre-1 P. aeruginosa 1.5 1.5 1.5 2.5 2.5 2.5 1.5 – – – 
C-40-Post-2; C-20-Post-2; C-20-Post-4 P. alcaligenes 0.5 11.5 0.5 – – – 
T-0.5-Post-4; C-10-D-3 B. cereus 0.5 2.5 2.5 2.5 0.5 1.5 0.5 0.5 0.5 0.5 – – – 

– indicates no change in lag time over 24 hours.

Efflux pumps have been identified to play a role in TCS resistance and in some cases antibiotic cross-resistance (Chuanchuen et al. 2001). PCMX has not been as extensively studied as TCS as far as resistance to the biocide is concerned, but there is the potential that as with many biocides PCMX resistance may also be due to efflux mechanisms, or mutations altering the target of the biocide. Pseudomonas, Bacillus and Klebsiella spp. found during this study have all previously been described as possessing efflux mechanisms (Li & Nikaido 2009). Current results indicate that the MIC for PCMX averages between 30 and 50 mg/L, for the majority of isolates. All isolates showed MIC values for TCS of more than 2 mg/L of TCS, thus further study is required to determine exact TCS MICs. Results also indicate that certain concentrations induced an increased level of resistance to either TCS or PCMX. This observation may be due to the fact that exposure to certain antimicrobials may trigger changes in gene expression (Haaber et al. 2015). As previously stated, the antimicrobial resistance observed among the isolates in this study may be due to efflux mechanisms and it may be possible that certain levels of the selected antimicrobials may trigger expression, or overexpression, of these efflux mechanisms (Yılmaz & Özcengiz 2017).

Checkerboard assay

Synergy and antagonism between TCS/PCMX and selected antibiotics was evaluated by the checkerboard method. Based on antibiotic resistance profiles the following isolates were selected: T-0.25-Pre-1 (P. aeruginosa), C-40-Post-2 (P. alcaligenes), T-0.5-Post-4 (B. cereus), T-0.5-Pre-1B (A. caviae) and T-1-D-6 (A. veronii). Table 4 indicates the various patterns of synergy and antagonism observed. Among Pseudomonas isolates, the interaction was observed only with tetracycline for P. aeruginosa, and only with amoxicillin and trimethoprim for P. alcaligenes. Both Bacillus spp. isolates showed interaction with kanamycin, tetracycline and chloramphenicol. Looking at the selected Aeromonas isolates, synergy and antagonism were observed to varying degrees in relation to all antibiotics tested except for trimethoprim, which showed no interaction. Examining the A. caviae isolate, antagonistic effects could be seen between TCS and kanamycin as well as chloramphenicol, and antagonism was also observed between PCMX and tetracycline. Synergistic effects could be observed between TCS and tetracycline as well as between PCMX and kanamycin, tetracycline and chloramphenicol. When looking at the A. veronii isolate certain similarities could be seen, synergy was observed between PCMX and tetracycline as well as kanamycin, and synergistic effects could also be seen between TCS and tetracycline, while antagonistic effects were also observed between TCS and kanamycin. The A. veronii isolate further exhibited synergistic effects between TCS and chloramphenicol as well as PCMX and amoxicillin.

Table 4

Synergy and antagonism observed

Biocide concentration: T-0.5-Pre-1B (A. caviae)
 
T-1-D-6 (A. veronii)
 
TCS
 
PCMX
 
TCS
 
PCMX
 
0.25 0.5 10 20 30 40 0.25 0.5 10 20 30 40 
Kanamycin – – – A/S 
Trimethoprim – – – – – – – – – – – – – – – – 
Tetracycline – – – – – – – 
Chloramphenicol – – – – – – – 
Amoxicillin – – – – – – – – – – – – – – – 
 T-0.25-Pre-1 (P. aeruginosa)
 
C-40-Post-2 (P. alcaligenes)
 
Kanamycin – – – – – – – – – – – – – – – – 
Trimethoprim – – – – – – – – – 
Tetracycline – – – – – – – – – – 
Chloramphenicol – – – – – – – – – – – – – – – – 
Amoxicillin – – – – – – – – – – – – – 
 T-0.5-Post-4 (B. cereus)
 
        
Kanamycin         
Trimethoprim – – – – – – – –         
Tetracycline         
Chloramphenicol         
Amoxicillin – – – – – – – –         
Biocide concentration: T-0.5-Pre-1B (A. caviae)
 
T-1-D-6 (A. veronii)
 
TCS
 
PCMX
 
TCS
 
PCMX
 
0.25 0.5 10 20 30 40 0.25 0.5 10 20 30 40 
Kanamycin – – – A/S 
Trimethoprim – – – – – – – – – – – – – – – – 
Tetracycline – – – – – – – 
Chloramphenicol – – – – – – – 
Amoxicillin – – – – – – – – – – – – – – – 
 T-0.25-Pre-1 (P. aeruginosa)
 
C-40-Post-2 (P. alcaligenes)
 
Kanamycin – – – – – – – – – – – – – – – – 
Trimethoprim – – – – – – – – – 
Tetracycline – – – – – – – – – – 
Chloramphenicol – – – – – – – – – – – – – – – – 
Amoxicillin – – – – – – – – – – – – – 
 T-0.5-Post-4 (B. cereus)
 
        
Kanamycin         
Trimethoprim – – – – – – – –         
Tetracycline         
Chloramphenicol         
Amoxicillin – – – – – – – –         

S, synergy; A, antagonism; A/S, combination; –, no observed effect.

Antagonism observed between TCS, kanamycin and amoxicillin may be attributed to the fact that bactericidal antimicrobials generally require the occurrence of cell growth, which is prevented by bacteriostatic agents, in this case TCS. At higher concentrations, the growth of certain cells may be inhibited to a point where the bactericidal agents are no longer effective (antagonism); but at low concentrations, growth is only slightly inhibited, contributing to the bactericidal action (synergy) (Ocampo et al. 2014; Bollenbach 2015). This occurrence may also be due to efflux mechanisms, which may be triggered at varying concentrations of the antimicrobials. Antagonism was also observed between chloramphenicol and TCS; this may be due to the presence of efflux mechanisms, or changes in gene expression owing to simultaneous exposure to both antimicrobials (Schweizer 2003; Li & Nikaido 2009).

Other than kanamycin, synergy was also observed between TCS alongside tetracycline, trimethoprim, chloramphenicol and amoxicillin. Amoxicillin and TCS both inhibit cell wall synthesis, thus synergy may occur due to the fact that both antimicrobials share a similar target (Bollenbach 2015). Tetracycline and chloramphenicol are both protein synthesis inhibitors, while trimethoprim blocks folic acid synthesis. All three of these antibiotics, as well as TCS, are described as bacteriostatic antimicrobials and thus synergy may be attributed to a joint effect on the inhibition of bacterial cell growth. There is also the possibility that resistance to bacteriostatic agents may be attributed to similar mechanisms, and the combination of two such antimicrobials may overwhelm the cell's defences (Tabak et al. 2009; Bollenbach 2015).

Antagonism observed between PCMX, tetracycline, trimethoprim and chloramphenicol can be attributed to the fact that both trimethoprim and chloramphenicol are primarily bacteriostatic agents while PCMX is a bactericidal agent. As previously stated, at higher antimicrobial concentrations the growth of certain cells may be inhibited to a point where the bactericidal agents are no longer effective (Ocampo et al. 2014). Antagonistic effects may also be present due to the presence of efflux mechanisms, or changes in gene expression owing to simultaneous exposure to both antimicrobials (Li & Nikaido 2009; Haaber et al. 2015). Synergy was observed between PCMX, kanamycin, chloramphenicol, tetracycline and amoxicillin. Kanamycin and amoxicillin are both bactericidal agents, the same as PCMX, thus synergy may be attributed to joint bactericidal activity (Tabak et al. 2009). According to Bollenbach (2015), resistance to antimicrobials may be due to similar mechanisms and thus the synergy observed between PCMX, chloramphenicol and tetracycline may be due to the fact that in these cases a similar resistance mechanism is shared which becomes overwhelmed when exposed to both antimicrobials simultaneously. PCMX is known to cause cell membrane damage, thus increasing permeability for protein synthesis inhibitors such as kanamycin, chloramphenicol and tetracycline, which may also lead to the observed synergistic effects (Tabak et al. 2009).

Results obtained while determining MICs indicated that certain concentrations of antimicrobials induced an increased level of resistance, and these observations may also contribute to the antagonism seen between TCS/PCMX, and various antibiotics. Efflux mechanisms are known to confer resistance to various antimicrobials, for example, the RND, SMR (small multidrug resistance) and MFS (major facilitator superfamily) efflux pump mechanisms are all known to confer resistance to biocides, and to several of the antibiotics used during the course of this study (Yılmaz & Özcengiz 2017). According to Yılmaz & Özcengiz (2017), the above-mentioned efflux systems confer resistance to tetracyclines, trimethoprim, chloramphenicol, β-lactams and aminoglycosides. Several studies have also demonstrated the role of RND and MFS efflux mechanisms in resistance to biocides such as TCS (Chuanchuen et al. 2001). Thus the current results obtained during the determination of antibiotic resistance profiles, MICs and synergistic/antagonistic interactions all indicate the possibility that efflux mechanisms may be the primary means of resistance to both antibiotics, and the antimicrobials in question (Schweizer 2003).

Pathogenic potential

Microorganisms are known to synthesize and secrete exotoxins, some of which are enzymes, into their environment, which play a role in pathogenicity. Some of these enzymes play a role in pathogenicity, and this contributes to the pathogenic potential of a bacterial isolate (Pavlov et al. 2004). Antibiotic resistance in itself is not considered to be a virulence factor but it may still perform an important role during the development of infection, contributing to the overall virulence of a pathogen (Beceiro et al. 2013).

Pseudomonas, Aeromonas, Bacillus and Klebsiella spp. are well described as opportunistic pathogens capable of causing various diseases, and each isolate has its own set of virulence characteristics (Table 2). Among all isolates DNase activity was the most prevalent (78%), followed by gelatinase (70%), chondroitinase (65%), lecithinase (65%), proteinase (61%) and lipase (30%). None of the isolates tested positive for the presence of hyaluronidase. Resistance to amoxicillin was observed among most isolates (78%), followed by trimethoprim (43%), oxytetracycline (39%) and vancomycin (9%). Only one isolate, P. aeruginosa, exhibited resistance to chloramphenicol and kanamycin. These factors along with haemolytic activity contributed to the assigned pathogen score. The P. aeruginosa isolate scored the highest, followed by A. veronii and A. caviae. The next highest scores were among Bacillus spp., while the lowest scores were attributed to P. monteilii, K. oxytoca, and P. alcaligenes. As previously stated, the majority of South Africa's population still rely on surface water as their primary source of water, and many still utilize untreated water. Unsafe water leads to an increased risk of infection due to waterborne pathogens, and this along with the HIV epidemic poses a serious health risk particularly from opportunistic pathogens (Momba et al. 2006). These facts along with the results obtained show the potential for virulence among the isolates, indicating that these organisms may pose a serious health risk considering their presence in water used for downstream recreational and irrigation purposes (Horn et al. 2016).

Conclusions

In conclusion, TCS and PCMX tolerant potentially pathogenic HPC bacteria were isolated from the WWTP North-West Potchefstroom. Several isolates well known to be opportunistic pathogens were found at various sampling points, the most prevalent of these being the Aeromonas spp. Isolates exhibited resistance and/or tolerance to various antimicrobials, and tested positive for the presence of several extracellular enzymes associated with virulence. Both PCMX and TCS were found in the WWTP but based on current results are not released into the environment. The presence of these biocides in the WWTP may drive the process of selection for multidrug-resistant pathogens which may be entering the environment, posing a serious health concern due to downstream usage of the receiving waters for both recreational and irrigation purposes.

ACKNOWLEDGEMENTS

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The research was supported by the Unit for Environmental Science and Management: Microbiology, North-West University, Potchefstroom Campus, South Africa.

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