Abstract
Regulations dealing with microbicides in Europe and the United States are evolving and now require data on the risk of the development of resistance in organisms targeted by microbicidal products. There is no standard protocol to assess the risk of the development of resistance to microbicidal formulations. This study aimed to validate the use of changes in microbicide and antibiotic susceptibility as initial markers for predicting microbicide resistance and cross-resistance to antibiotics. Three industrial isolates (Pseudomonas aeruginosa, Burkholderia cepacia, and Klebsiella pneumoniae) and two Salmonella enterica serovar Typhimurium strains (SL1344 and 14028S) were exposed to a shampoo, a mouthwash, eye makeup remover, and the microbicides contained within these formulations (chlorhexidine digluconate [CHG] and benzalkonium chloride [BZC]) under realistic, in-use conditions. Baseline and postexposure data were compared. No significant increases in the MIC or the minimum bactericidal concentration (MBC) were observed for any strain after exposure to the three formulations. Increases as high as 100-fold in the MICs and MBCs of CHG and BZC for SL1344 and 14028S were observed but were unstable. Changes in antibiotic susceptibility were not clinically significant. The use of MICs and MBCs combined with antibiotic susceptibility profiling and stability testing generated reproducible data that allowed for an initial prediction of the development of resistance to microbicides. These approaches measure characteristics that are directly relevant to the concern over resistance and cross-resistance development following the use of microbicides. These are low-cost, high-throughput techniques, allowing manufacturers to provide to regulatory bodies, promptly and efficiently, data supporting an early assessment of the risk of resistance development.
INTRODUCTION
Microbicides have been extensively used in the control of bacteria for decades and are commonly incorporated into a variety of products, including disinfectants, cosmetics, preservatives, pesticides, and antiseptics. Despite this ever-increasing use, bacteria generally remain susceptible to microbicides when they are used correctly. However, the indiscriminate use of microbicides in a wide range of environments has raised concerns about the selection of microbicide- and antibiotic-resistant bacteria (1, 2). Despite the issuance of the Biocidal Product Regulation (BPR) (3) to regulate the authorization and use of biocidal products throughout the European Union, the total amount of microbicide use in the European Union remains unknown (2).
Of particular concern are formulations that contain microbicides at low concentrations, which may increase the risk of selection for resistance among target or nontarget microorganisms (2). Resistance or reduced susceptibility to microbicides and/or antibiotics as a result of exposure to low microbicide concentrations has been demonstrated extensively in the laboratory setting (4–8). Despite the lack of in vivo or in situ studies reporting a link between microbicide exposure and antibiotic resistance development, in vitro studies have clearly demonstrated the possibility of microbicide and antibiotic resistance development in bacteria. This has led committees such as the Scientific Committee on Emerging and Newly Identified Health Risks (SCENIHR) to produce reports and opinions on the knowledge gaps and research concerns associated with resistance. In its 2010 opinion paper, SCENIHR stated that both data on microbicide usage and an understanding of which microbicides are most at risk of promoting the development of bacterial resistance are lacking (2). SCENIHR recommended the standardization of methodologies used to monitor resistance levels and suggested the development of a standard protocol that could determine the risk of resistance development in a particular microorganism as a result of microbicide exposure.
In support of the requirement for such a protocol, the new BPR (EU 528/2012) requires biocidal product manufacturers to provide information on the likelihood of the development of resistance to their product in target organisms. In particular, it states:
(13) Active substances can, on the basis of their intrinsic hazardous properties, be designated as candidates for substitution with other active substances, whenever such substances considered as efficient toward the targeted harmful organisms become available in sufficient variety to avoid the development of resistances among harmful organisms …
(25) … The use of low-risk biocidal products should not lead to a high risk of developing resistance in target organisms.
(33) When biocidal products are being authorized, it is necessary to ensure that, when properly used for the purpose intended, they are sufficiently effective and have no unacceptable effect on the target organisms such as resistance … (3).
In addition, the U.S. Food and Drug Administration (FDA) has issued a proposed rule requiring manufacturers of antibacterial hand soaps and body washes to demonstrate that their products are safe for long-term daily use, are more effective than plain soap and water in preventing the spread of certain infections, and do not select for resistance (10). A standard protocol that could determine the risk of resistance development would allow microbicidal product manufacturers to provide this information in response to BPR and FDA regulations promptly and efficiently.
Our work focuses on the development of such a protocol and has involved the assessment of several laboratory techniques that can be used to measure microbicide resistance (e.g., determination of the MIC and minimum bactericidal concentration [MBC], antibiotic susceptibility testing, and phenotype stability testing) in terms of ease of use, high throughput, cost, and reproducibility. Our recommended protocol encompasses MIC, MBC, and antibiotic susceptibility determinations combined with bacterial phenotype stability testing as initial markers of bacterial microbicide resistance or antibiotic cross-resistance. This study aims to validate the use of these techniques in a combination protocol with the testing of three commercially available formulations and the active microbicides contained in them.
MATERIALS AND METHODS
Bacterial strains.
A range of Gram-negative bacteria was selected for the testing of three antimicrobial formulations and the microbicides contained within each. The bacteria included Salmonella enterica serovar Typhimurium strains SL1344 and 14028S (obtained from the University of Birmingham, Birmingham, United Kingdom) and three strains from the Unilever (United Kingdom) culture collection: Burkholderia cepacia (UL2P), Klebsiella pneumoniae (UL13), and Pseudomonas aeruginosa (UL-7P). The three Unilever strains were selected as challenge organisms due to their routine use, propagation, and handling in Unilever laboratories.
Culture and storage of bacteria.
Liquid cultures of all strains were grown in tryptone soya broth (TSB) (Oxoid, Basingstoke, United Kingdom) at 37°C (±1°C). Strains were stored on Protect beads (Fisher Scientific, Loughborough, United Kingdom) at −80°C (±1°C) and were restricted to a maximum of 2 subcultures from the original freezer stock prior to exposure to a given microbicide. Test inocula were prepared by harvesting an overnight TSB culture, centrifuging at 5,000 × g for 10 min, and resuspending in deionized water (diH2O).
Formulations, active ingredients, and neutralizer.
A mouthwash (containing 2 mg/ml chlorhexidine digluconate [CHG]), an eye makeup remover (containing 1 mg/ml CHG), and a shampoo (containing 5 mg/ml benzalkonium chloride [BZC]) were tested. These products were selected because they are commonly used home and personal care products. CHG and BZC (Sigma-Aldrich, Dorset, United Kingdom), which are the only microbicides contained within the three formulations, were also tested. The neutralizer used was composed of Tween 80 (30 g/liter) and asolectin (3 g/liter) (both from Sigma-Aldrich, Dorset, United Kingdom). The efficacy of the neutralizer to quench the antimicrobial activities of the mouthwash, shampoo, and eye makeup remover and the toxicity of the neutralizer toward all bacterial strains tested were determined as described previously (4).
Antimicrobial susceptibility testing. (i) Suspension testing.
Test strains were exposed to each formulation and each microbicide at a concentration resulting in a 1 to 3 log10 reduction in CFU/ml, leaving sufficient survivors for further antimicrobial susceptibility testing. Suspension tests were carried out according to the British standard (BS EN 1276:2009) protocol (11). Briefly, bacterial suspensions in diH2O produced from overnight cultures were standardized to 1 × 108 CFU/ml. Suspensions were used within 15 min of preparation. One milliliter of the standardized suspension was added to 9 ml of the desired formulation or active ingredient (diluted in diH2O) at 1.25 times the required concentration. The concentrations tested were as follows: 0.000125 mg/ml mouthwash or CHG, 0.00015 mg/ml shampoo or BZC, and 1 mg/ml eye makeup remover or CHG. After exposure for 1 min (the estimated length of time spent using each formulation by the consumer), 1 ml of this suspension was removed and was added to 9 ml of the neutralizer. After neutralization, suspensions were centrifuged at 5,000 × g for 10 min, and the supernatant was discarded. The remaining cells were then used in further antimicrobial susceptibility testing experiments. S. enterica strains SL1344 and 14028S were also exposed to low BZC and CHG concentrations ranging from 0.0001 to 0.004 mg/ml for 5 min.
(ii) Determination of the MIC.
The MIC of each formulation or microbicide was determined for all strains, before and after exposure to a given formulation or active ingredient by suspension testing, according to the BS EN ISO 20776-1 (12) protocol. Briefly, a 96-well microtiter plate (Sterilin Ltd., Newport, United Kingdom) containing doubling dilutions of a given formulation or active ingredient in TSB was set up. Concentration ranges were as follows: mouthwash or CHG, 2 to 0.001 mg/ml; shampoo or BZC, 1.25 to 0.001 mg/ml; eye makeup remover or CHG, 0.5 to 0.00048 mg/ml; CHG or BZC (for Salmonella strains only), 40 to 0.019 mg/ml. An overnight broth culture of each strain was standardized to 1 × 108 CFU/ml, and 50-μl volumes of this culture were added to the microtiter plate. The plate was incubated for 24 h at 37°C. The MIC was defined as the lowest concentration of a formulation or microbicide at which no bacterial growth was observed visually on the microtiter plate. (The approximate cost to test one microbicide and one bacterium in triplicate was <1 euro.)
(iii) Determination of the MBC.
The minimum bactericidal concentration (MBC) of each formulation or microbicide was also determined before and after the exposure of each strain to a given formulation or active ingredient by suspension testing. Twenty microliters of the suspension was removed from each well of the MIC microtiter plate where no bacterial growth was observed, and from wells containing the two lowest concentrations of the formulation or active ingredient at which growth was observed, and was added to 180 μl of neutralizer. Twenty-five microliters of this suspension was then spotted onto tryptone soya agar (TSA) and was incubated at 37°C for 24 h. The MBC was defined as the lowest concentration of the formulation or active ingredient at which no bacterial growth was observed on the agar plate. (The approximate cost to test one microbicide and one bacterium in triplicate was <1 euro.)
Antibiotic susceptibility testing.
The susceptibility of each strain to one or more of the following antibiotics was determined, before and after exposure to a given formulation or microbicide by suspension testing, according to the British Society for Antimicrobial Chemotherapy (BSAC) disk diffusion protocol (13): chloramphenicol (50 μg), ampicillin (10 μg), ciprofloxacin (1 μg), ceftriaxone (30 μg), piperacillin (30 μg), ceftazidime (30 μg), imipenem (10 μg), meropenem (15 μg), tobramycin (10 μg), and aztreonam (30 μg) (all from Oxoid, Basingstoke, United Kingdom). These antibiotics were selected due to their use as therapeutic agents in the treatment of infections with the organisms chosen for this study. There are no available BSAC susceptibility breakpoints for Burkholderia spp., so breakpoints for Pseudomonas spp. were used for B. cepacia strain UL2P. (The approximate cost to evaluate the susceptibility of 1 strain to 6 antibiotics was <2 euros.)
Phenotype stability testing.
The stability of any alterations in antimicrobial susceptibility observed after 5 min of exposure of S. enterica strains SL1344 and 14028S to a range of low CHG and BZC concentrations was investigated via the 24-h subculture of surviving organisms through TSB with or without a low concentration of CHG or BZC, as described previously (4).
Reproducibility of data.
In order to determine the reproducibility of the baseline and postexposure data obtained, the experiments described above were performed on 3 separate occasions (each using 3 biological replicates) over a 6 month period. Thus, data are the means of 9 results.
Statistical analysis.
Student's t test was used to compare MICs, MBCs, and the sizes of antibiotic zones of inhibition before and after microbicide exposure.
RESULTS
Three formulations and the microbicides they contained were tested on three separate occasions over a 6-month period in order to determine if exposure to a given microbicidal product or microbicide resulted in an alteration in microbicide or antibiotic susceptibility in test organisms. The data obtained on each occasion were compared in order to determine the reproducibility of the MIC, MBC, and antibiotic susceptibility test results and thus to validate the use of these tests as a high-throughput and low-cost initial approach for determining the risk of resistance development. The mean MIC and MBC for each test organism before and after exposure to the mouthwash, eye makeup remover, or shampoo, or to the corresponding microbicide (CHG, CHG, or BZC) at the same concentration as that contained in the product, are presented in Fig. 1. Exposure to one of the three formulations or to the corresponding microbicide resulted in both increases and decreases in MICs and MBCs for individual strains. For shampoo and eye makeup remover, accurate MBCs could not be determined, because all 5 strains grew in the highest testable concentration of the formulation. The greatest increases in the MBC were observed for S. enterica strain 14028S after exposure to 0.005 mg/ml CHG or mouthwash, or to 0.015 mg/ml BZC; all these increased MBCs were found to be significantly different from baseline MBCs. However, the postexposure MBC values observed (0.08, 0.05, and 0.05 mg/ml, respectively), are clearly still below or equal to the concentrations of CHG and BZC present in the relevant formulations in a worst-case scenario of product dilution by the consumer. “Worst-case” dilution factors of 1 in 40 (mouthwash) and 1 in 100 (shampoo) were estimated based on product use, e.g., rinsing with water. This would result in 0.05 mg/ml CHG in mouthwash and 0.05 mg/ml BZC in shampoo. An MBC of 0.50 mg/ml for BZC is also of less concern, since the primary function of BZC in the shampoo is not as an antimicrobial but as a surfactant. Very few of the remaining changes observed in the MIC or MBC were found to be statistically significant (P ≤ 0.05), nor did they approach the microbicide concentrations found in the formulations tested after “worst-case” product dilution by the consumer.
FIG 1.
MIC and MBC values for 5 test organisms before and after exposure to 3 formulations and their corresponding pure active ingredients. Data are means of 9 results. Blue bars, baseline MICs; red bars, postexposure MICs; green bars, baseline MBCs; purple bars, postexposure MBCs. Error bars correspond to SD. MICs and MBCs were determined by 2-fold dilution (see the text for detailed information). Strains were exposed to 0.005 mg/ml CHG (A), mouthwash (containing 0.005 mg/ml CHG) (B), 1 mg/ml CHG (C), eye makeup remover (EMR) (undistilled; containing 1 mg/ml CHG) (D), 0.015 mg/ml BZC (E), or shampoo (containing 0.015 mg/ml BZC) (F).
An important factor in the validation of the use of MIC and MBC determinations in an initial assessment of the risk of resistance development was the reproducibility of the data obtained. It is clear from Fig. 1 that both the baseline and postexposure mean MIC and MBC values were highly reproducible across the 3 separate experiments, as indicated by the small standard deviations (SD) observed for each strain and formulation or pure active ingredient. Our protocol is based on performing MIC/MBC testing in 2-fold dilutions. Standard deviations were calculated based on the MIC or MBC values, which means that an increase or decrease in the MIC or MBC by 1-fold dilution will result in a large standard deviation. Error bars (representing SD) on the graphs displayed in Fig. 1 may indicate only an increase or decrease of one doubling dilution.
For all 5 strains, there was no clinical change in susceptibility to any of the antibiotics tested after 1 min of exposure to any of the 3 formulations or their corresponding microbicides (according to BSAC susceptibility breakpoints for Enterobacteriaceae or Pseudomonas spp. [13]) (data not shown). For some strains and antibiotics, statistically significant changes in the size of the zone of inhibition were observed. However, these differences were often due to an increase in the mean size of the zone of inhibition and therefore to an increase in antibiotic susceptibility (e.g., the susceptibility of K. pneumoniae to ciprofloxacin, chloramphenicol, and ceftazidime after exposure to mouthwash [0.050 mg/ml CHG] or the susceptibility of P. aeruginosa to ceftazidime after exposure to shampoo [0.015 mg/ml BZC]). A statistically significant reduction in the mean size of the zone of inhibition of aztreonam for P. aeruginosa was observed after exposure to 0.005 mg/ml CHG, 0.015 mg/ml BZC, or 1 mg/ml CHG. However, P. aeruginosa was already resistant to this antibiotic prior to microbicide exposure, and therefore, no clinical susceptibility change was observed. It was not possible to determine clearly if clinical changes in susceptibility were observed in B. cepacia, since there were no available breakpoints provided in the BSAC protocol, and clinical susceptibility was therefore based on Pseudomonas sp. breakpoints.
Carrying out this experiment on 3 separate occasions over a 6-month period also allowed for an assessment of the reproducibility of the results obtained. The BSAC method produces consistent and reproducible baseline and postexposure data (data not shown).
S. enterica strains SL1344 and 14028S were also exposed to a range of low concentrations of CHG and BZC for 5 min before the antimicrobial susceptibility of surviving organisms was determined. Tables 1 and 2 show the baseline and postexposure values for SL1344 and 14028S, respectively, after 5 min of exposure to a range of low CHG and BZC concentrations.
TABLE 1.
Mean baseline and postexposure MICs and MBCs for strain SL1344 after 5 min of exposure to a range of low CHG and BZC concentrations
| Condition | Mean MIC or MBC (mg/ml) ± SDa |
|||
|---|---|---|---|---|
| CHG MIC | CHG MBC | BZC MIC | BZC MBC | |
| Baseline | 0.03 ± 0.03 | 0.10 ± 0.06 | 0.03 ± 0.00 | 0.03 ± 0.03 |
| CHG concn (mg/ml) | ||||
| 0.004 | 0.80 ± 0.00 | 2.00 ± 0.90 | 2.00 ± 0.00 | 2.00 ± 0.00 |
| 0.001 | 0.80 ± 0.00 | 2.00 ± 0.00 | 0.30 ± 0.20 | 0.50 ± 0.20 |
| 0.0005 | 0.40 ± 0.00 | 0.40 ± 0.00 | 0.10 ± 0.00 | 2.00 ± 2.00 |
| 0.0001 | 0.80 ± 0.00 | 1.00 ± 0.40 | 0.70 ± 1.00 | 1.30 ± 2.00 |
| BZC concn (mg/ml) | ||||
| 0.004 | 0.50 ± 2.00 | 3.00 ± 0.00 | 3.00 ± 1.00 | 8.00 ± 0.00 |
| 0.001 | 0.40 ± 0.00 | 2.00 ± 0.00 | 0.80 ± 0.00 | 2.00 ± 0.00 |
| 0.0001 | 0.80 ± 0.00 | 2.00 ± 1.00 | 0.70 ± 1.00 | 3.00 ± 2.00 |
Data are means of 9 results.
TABLE 2.
Mean baseline and postexposure MICs and MBCs for strain 14028S after 5 min of exposure to a range of low CHG and BZC concentrations
| Condition | Mean MIC or MBC (mg/ml) ± SDa |
|||
|---|---|---|---|---|
| CHG MIC | CHG MBC | BZC MIC | BZC MBC | |
| Baseline | 0.030 ± 0.03 | 0.06 ± 0.03 | 0.04 ± 0.03 | 0.08 ± 0.02 |
| CHG concn (mg/ml) | ||||
| 0.005 | 0.10 ± 0.00 | 1.00 ± 0.90 | 0.80 ± 0.00 | 1.00 ± 0.00 |
| 0.001 | 1.00 ± 0.00 | 20.00 ± 0.00 | 0.10 ± 0.00 | 2.00 ± 0.60 |
| BZC concn (mg/ml) | ||||
| 0.015 | 0.40 ± 0.00 | 50.00 ± 0.00 | 0.80 ± 0.00 | 1.00 ± 0.00 |
| 0.004 | 0.80 ± 0.00 | 3.00 ± 0.00 | 2.00 ± 0.00 | 20.00 ± 0.90 |
Data are means of 9 results.
In the case of both strains, all postexposure MIC and MBC values of CHG and BZC were significantly different from baseline MIC and MBC values (P ≤ 0.05). For strain SL1344, the greatest increases in the MIC and MBC were observed after 5 min of exposure to 0.004 mg/ml CHG or 0.004 mg/ml BZC (Table 1). For strain 14028S, exposure to 0.001 mg/ml CHG or 0.004 mg/ml BZC resulted in the greatest increases in the MIC and MBC in surviving organisms (Table 2). The data appear highly reproducible across all 9 repeats in the case of both strains, as indicated by the low standard deviation values, supporting our recommendation of the use of MIC and MBC determinations as initial indicators of resistance development in bacteria. (As discussed for Fig. 1, occasions where standard deviations appear larger are due to the use of doubling dilutions of a given microbicide or formulation during MIC/MBC testing.) Susceptibility to a range of antibiotics was also determined for strains SL1344 and 14028S before and after exposure to low CHG and BZC concentrations. No alterations in antibiotic susceptibility were observed (data not shown).
The stability of the increases in the MBC observed after 5-min exposures of SL1344 and 14028S to a range of low CHG and BZC concentrations was investigated via the 24-h subculture of surviving organisms through TSB with or without a low concentration of CHG or BZC. Tables 3 and 4 show the mean MBC values after 1, 5, and 10 subcultures of surviving organisms through TSB with or without CHG or BZC for SL1344 and 14028S, respectively. The high MBC values observed after the initial 5-min exposure to CHG or BZC were lost after 1 subculture in the absence of CHG or BZC. In the presence of a low CHG or BZC concentration, MBC values also returned to baseline levels after 10 subcultures. This was thought to be due to cumulative damage to the cell or to the fact that maintaining a high MBC was detrimental to cell survival. The instability of the increased MBC values suggested a low risk of development of stable resistance to CHG or BZC by either S. enterica strain at the concentrations tested. The values obtained from the phenotype stability tests were reproducible between repeats (as indicated by the low standard deviation values in Tables 3 and 4), and the data therefore support our recommendation of the use of this technique as part of a protocol to predict the development of microbicide resistance.
TABLE 3.
Mean baseline and postexposure MBCs for strain SL1344 after 1, 5, and 10 subcultures in TSB with or without 0.004 mg/ml CHG or BZC
| Condition | Mean MBC (mg/ml) ± SDa |
|
|---|---|---|
| CHG | BZC | |
| Baseline | 0.10 ± 0.90 | 0.03 ± 0.00 |
| Exposure to CHG (0.004 mg/ml) for 5 min | 5.00 ± 0.00* | 1.50 ± 0.00* |
| Subcultures without CHG | ||
| 1 SC | 0.08 ± 0.00 | 0.04 ± 0.00 |
| 5 SC | 0.09 ± 0.00 | 0.06 ± 0.00 |
| 10 SC | 0.06 ± 0.00 | 0.06 ± 0.00 |
| Subcultures with CHG | ||
| 1 SC | 0.15 ± 0.40 | 0.19 ± 0.00* |
| 5 SC | 0.10 ± 0.40 | 0.50 ± 0.20* |
| 10 SC | 0.10 ± 0.00 | 0.06 ± 0.00 |
| Exposure to BZC (0.004 mg/ml) for 5 min | 5.00 ± 0.00* | 3.00* ± 0.00 |
| Subcultures without BZC | ||
| 1 SCb | 0.20 ± 0.30 | 0.06 ± 0.00 |
| 5 SC | 0.10 ± 0.00 | 0.06 ± 0.00 |
| 10 SC | 0.10 ± 0.00 | 0.06 ± 0.00 |
| Subcultures with BZC | ||
| 1 SC | 0.80 ± 0.40* | 0.78 ± 0.00* |
| 5 SC | 0.80 ± 0.40* | 0.60 ± 0.20* |
| 10 SC | 0.10 ± 0.00 | 0.03 ± 0.00 |
Asterisks indicate values significantly different from the baseline (P ≤ 0.05).
SC, subculture.
TABLE 4.
Mean baseline and postexposure MBCs for strain 14028S after 1, 5, and 10 subcultures in TSB with or without 0.001 mg/ml CHG or 0.004 mg/ml BZC
| Condition | Mean MBC (mg/ml) ± SDa |
|
|---|---|---|
| CHG | BZC | |
| Baseline | 0.06 ± 0.03 | 0.08 ± 0.02 |
| Exposure to CHG (0.001 mg/ml) for 5 min | 5.00 ± 0.00* | 3.00 ± 0.00* |
| Subcultures without CHG | ||
| 1 SC | 0.01 ± 0.00 | 0.06 ± 0.00 |
| 5 SC | 0.06 ± 0.00 | 0.07 ± 0.00 |
| 10 SC | 0.09 ± 0.00 | 0.06 ± 0.00 |
| Subcultures with CHG | ||
| 1 SC | 0.80 ± 0.40* | 0.19 ± 0.00* |
| 5 SC | 0.80 ± 0.40* | 0.20 ± 0.00* |
| 10 SC | 0.06 ± 0.00 | 0.06 ± 0.00 |
| Exposure to BZC (0.004 mg/ml) for 5 min | 5.00 ± 0.00* | 3.00 ± 0.00* |
| Subcultures without BZC | ||
| 1 SCb | 0.06 ± 0.00 | 0.07 ± 0.00 |
| 5 SC | 0.05 ± 0.00 | 0.04 ± 0.00 |
| 10 SC | 0.06 ± 0.00 | 0.06 ± 0.00 |
| Subcultures with BZC | ||
| 1 SC | 0.40 ± 0.20* | 0.19 ± 0.00* |
| 5 SC | 0.70 ± 0.70* | 0.20 ± 0.00* |
| 10 SC | 0.06 ± 0.00 | 0.06 ± 0.00 |
Asterisks indicate values significantly different from the baseline (P ≤ 0.05).
SC, subculture.
DISCUSSION
The principal aim of this work is to design a protocol that can predict bacterial microbicide resistance and antibiotic cross-resistance and give an indication of the risk of resistance development. The purpose of this study was to validate the use of MIC, MBC and antibiotic susceptibility determinations before and after microbicide exposure, and the use of phenotype stability testing, for the initial prediction of bacterial resistance to microbicides.
The use of existing standard protocols for MIC, MBC, and antibiotic susceptibility measurements (i.e., BS EN 1276:2009, BS EN ISO 20776-1:2006, and the BSAC disk diffusion method) helps to avoid data variability, which has been observed previously with MIC values obtained using different methodologies. Schurmaans et al. (14) found that MIC values could vary by as much as a factor of 8 if small alterations were made to the method used. Phenotypic variability was avoided by using overnight broth cultures for susceptibility testing, rather than selecting single colonies from an agar plate, which has been demonstrated to result in phenotypic variability for Burkholderia cepacia (15), illustrating the importance of consistent inoculum preparation in performing susceptibility tests. In the work carried out here, the inoculum was resuspended in diH2O instead of tryptone sodium chloride (TSC) buffer, because TSC has been observed to interfere with log reduction results due to carryover from the inoculum (unpublished data). However, the inoculum was used within 15 min of preparation in diH2O in order to avoid subjecting bacterial cells to osmotic stress.
The MIC, MBC, and antibiotic susceptibility values for mouthwash, shampoo, eye makeup remover, CHG, and BZC were found to be reproducible between separate experiments at the concentrations tested for all 5 test strains, confirming the appropriateness of using these standard protocols. We concluded that there is a very low risk of development of resistance to the formulations and corresponding pure active ingredients tested, even in the case of the elevated MICs and MBCs observed for strains SL1344 and 14028S, since these values were not stable in the absence or presence of CHG or BZC.
The use of the MIC and MBC in resistance prediction and the comparison between baseline and postexposure susceptibility data are supported by our previous work investigating the effect of cationic microbicide exposure on Burkholderia lata strain 383 (4). Our protocol allows the testing of any isolate of interest, since data for an individual isolate are always compared with baseline data for the same isolate rather than with MIC/MBC data for the bacterial species.
One of the criticisms of in vitro techniques used in the measurement of microbicide resistance is that experimental parameters such as the microbicide concentration, exposure time, dilution on application, and bioavailability do not reflect in-use conditions (1, 16). In our work, we attempted to accurately reflect product use in terms of exposure time and product concentration (i.e., any dilution of the product as a result of its use). For the purpose of protocol development, the test concentrations used were considerably lower than those found in the original formulations (i.e., concentrations low enough to allow us to obtain surviving organisms), but test concentrations should be kept realistic when one is using the techniques recommended here to predict and assess the risk of resistance development. Both the formulations and the corresponding active microbicides were tested during protocol development in order to validate the different techniques used, but it must be emphasized that using such a protocol to predict resistance to pure active ingredients alone may be of less relevance than testing the formulation as a whole, since multiple components of a formulation often contribute to the overall microbicidal effect or could prove antagonistic.
Although they are more representative of microbicide use, long-term (≥6 months) studies investigating the effects of exposure to commonly used household microbicides on antimicrobial susceptibility have failed to demonstrate resistance development in isolated bacteria (17–20). These studies are also costly and do not allow for a prompt response to regulatory bodies. This suggests that in light of new regulatory expectations, a compromise may be required, allowing the rapid generation of data and preliminary assessment of risk by using in vitro techniques based on existing standard methods while controlling parameters such as the microbicide formulation, contact time, and concentration in order to bring realism to the evaluation. The protocol proposed in this study aims to achieve this.
A further recommendation of Maillard et al. (1) and SCENIHR (2) in the event of the observation of a reproducible change in microbicide susceptibility is the execution of further tests to understand the nature of the change. This could include molecular techniques to investigate changes to the transcriptome and proteome as a result of microbicide exposure. Genotypic alterations as a result of microbicide exposure and their potential as resistance markers have been investigated by numerous groups (21–23), and molecular techniques such as PCR and microarray technology have been successfully used to define microbicide resistance mechanisms. Although useful, molecular techniques can be complex, costly, and time-consuming, and we therefore do not recommend them as a core part of this predictive protocol. Taking this into account, Fig. 2 shows the proposed protocol steps in the form of a decision tree, as well as potential steps in the event of observed, reproducible resistance. A stable increase in the MIC or MBC or a change in antibiotic susceptibility could result in a risk of resistance development. It must be emphasized that the exact level of risk can be determined only through further assessment. For example, a stable increase in the MBC may not constitute a high level of risk if this new MBC does not approach the concentration of a particular microbicide intended for use (Fig. 2). Some microbicides (e.g., chlorhexidine, triclosan, and benzalkonium chloride) have a long history of use and a large amount of literature studying their efficacy and any observed bacterial resistance. For these microbicides, sufficient evidence may be available in the literature to support a weight-of-evidence assessment of the risk of resistance development before one considers generating new data on resistance (24, 25).
FIG 2.
Proposed protocol for use in the prediction of bacterial microbicide resistance. Examples of further work that could be carried out to investigate the mechanisms behind changes in antimicrobial susceptibility are presented in gray letters at the bottom of the decision tree. 1 “Realistic conditions” are those under which the product will be used. Factors such as concentration, contact time, and product formulation should be considered in order to represent product use as accurately as possible. 2 If reproducible and phenotypically stable changes in antimicrobial susceptibility are observed after exposure to a particular product under realistic, in-use conditions, the risk can be investigated further. This may involve the elucidation of possible mechanisms behind susceptibility changes, leading to better understanding of the level of risk. This investigation could be extended beyond the examples shown here and could include the exploration of additional resistance markers and the use of additional techniques.
Our findings and our proposed approach for risk assessment can be applicable to the wider use of microbicides in various settings. This approach is preventative and is aimed at being predictive, thereby ensuring that microbicide-containing formulations are safe by design with regard to resistance and cross-resistance risks, either by enabling the omission of an ingredient identified by the protocol as undesirable or by using the improved understanding of resistance and cross-resistance mechanisms to design a formulation with an ingredient preventing the expression of a microbicide-relevant resistance mechanism (e.g., efflux pump inhibitors). Such a strategy has already been investigated and has been documented to decrease bacterial resistance to antibiotics (26).
With the U.S. FDA and EU BPR regulations requiring information on the propensities of microbicidal products to select for resistant bacteria, it is imperative that relevant, cost-effective, high-throughput techniques be available to enable product manufacturers to provide this information. Since global harmonization of the protocols used to measure changes in microbicide susceptibility is now considered a key requirement in moving microbicidal research forward (1, 2), we recommend, and here demonstrate, the efficacy of a protocol that allows the prediction of resistance development using simple, low-cost, and high-throughput techniques.
ACKNOWLEDGMENT
This project, conducted by Cardiff University, was sponsored by the Unilever Safety & Environmental Assurance Centre, which provided a Ph.D. studentship to L. Knapp.
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