Susceptibility testing is used to guide therapy and to generate surveillance data (Potz et al., 2004). Susceptibility is determined by growth inhibition and not the killing of bacterium (Walker, 2000). The results can be reported quantitatively or qualitatively. Qualitative results are reported as susceptible, intermediate, or resistant, while quantitative results provide a minimum inhibitory concentration (MIC) in µg/ml or mg/ml. The MIC is defined as the lowest concentration of drug required to inhibit growth of an organism using a standardized test (Jorgensen, 2004) and can be monitored to determine if a population is shifting towards increasing resistance (Walker, 2000).
Practitioners often require a clinically relevant category derived from applying interpretative breakpoints to the MIC information (Craig, 1993, MacGowan and Wise, 2001). Interpretive breakpoints allow for susceptible, intermediate, and resistant
categorization of isolates. The break point for susceptibility is the recommended dosage of an antimicrobial that inhibits the bacterium’s growth (Walker, 2000). Breakpoints for resistance represent concentrations that cannot be achieved by normal dosing, and
intermediate breakpoints are those which fall between susceptible and resistant (Walker, 2000).
Laboratory assessment of susceptibility and resistance is not necessarily equivalent to clinical susceptibility and resistance. Clinically (or in vivo) a strain is considered resistant if it survives therapy (Guardabassi and Courvalin, 2006). Clinical resistance can vary depending on the dosage, mode of drug administration, distribution of the drug, and the immune status of the patient (Guardabassi and Courvalin, 2006). Clinical breakpoints indicate the MIC that will reflect the probability of treatment success given a specified dosing schedule (Mouton, 2002). Clinical breakpoints are set not only based on the MICs, but also in vivo parameters such as pharmacokinetics and
pharmacodynamics of the drug as well as with correlation of the MICs with the clinical outcome (Guardabassi and Courvalin, 2006). Factors such as bacterial distribution in the host, sub-MIC effects, postantibiotic effects, protein binding, and variations in drug concentration in the blood can all affect in vivo susceptibility (Jorgensen, 2004) and determination of the clinical breakpoint. An excellent overview of approaches that can be used to calculate clinical breakpoints is provided by Mouton (2002).
Breakpoints can also be considered from a microbiological (in vitro) rather than a clinical point of view. Microbiological breakpoints are based on MICs for a bacterial species with resistance at the higher MICs when compared to the distribution of the normal susceptible population (Guardabassi and Courvalin, 2006). Microbiological resistance is determined by comparison of two or more strains under identical
conditions (Guardabassi and Courvalin, 2006). These breakpoints are useful for
surveillance and for identifying emerging resistance (Guardabassi and Courvalin, 2006).
Microbiological breakpoints are used to detect organisms that do no belong to the natural bacterial population. These organisms have acquired resistance and may represent an emerging resistant strain (Mouton, 2002). The microbiological breakpoint criteria do not consider drug pharmacokinetic properties in individual patients (Dudley and Ambrose, 2000, Mouton, 2002).
Breakpoints are generally derived from human isolates (Walker, 2000). The
pharmacokinetic data collected from human populations may differ significantly from that derived from animals; therefore, what may be an appropriate breakpoint for human isolates may not be the same for animal isolates. Since human breakpoints do not reliably predict clinical outcomes when applied to veterinary pathogens, the National Committee for Clinical Laboratory Standards (NCCLS) have developed a veterinary specific antimicrobial susceptibility criteria (NCCLS, 2000).
There are other challenges associated with the reporting of breakpoints and AMR. Resistance can only be assessed by comparing the strains of the same species or genus (Guardabassi and Courvalin, 2006). For example, ampicillin has an MIC breakpoint of 128 µg/ml for E. coli sp. but for Streptococcus agalacttiae the MIC is 0.12 µg/ml (Prince and Neu, 1983). Breakpoints may also vary between countries (MacGowan and Wise, 2001, Mouton, 2002, Jorgensen, 2004) depending on the agency setting the
breakpoints and the methodologies used. Therefore, when comparing susceptibility results between different organism and countries one must keep in mind what the susceptible, intermediate, and resistant breakpoints are for each respective organism or country. Despite these limitations, susceptibility breakpoints can provide a reference for clinical efficacy (Jorgensen, 2004) and for surveillance purposes.
2.3.1. Phenotype susceptibility testing methods
The primary methods used for susceptibility testing are agar disc diffusion, broth microdilution, agar dilution, broth macrodilution, and E-test. Since agar diffusion and broth microdilution are the two principal methodologies used in veterinary medicine (Brooks et al., 2003), this discussion will focus on these tests and some of their advantages and disadvantages.
Agar disc diffusion is based on diffusion of an antimicrobial agent from a
commercially prepared disc placed on an agar surface inoculated with a standardized growth medium that has been seeded with approximately 1.0 x 108 colony forming units of pure culture (Prescott, 2000). At the same time that the inoculum is growing, the antimicrobial agent is diffusing from the disc. If the organism is susceptible to the antimicrobial, a zone of growth inhibition is created around the disc. The larger the zone of inhibition, the more susceptible the organism is to the antimicrobial.
Agar disc diffusion techniques provide qualitative data, are flexible and low cost. However, the results of disc diffusion will vary unless the inoculum density, the agar
thickness and the incubation are carefully controlled (Potz et al., 2004). Veterinary specific antimicrobial disks are available for antimicrobials such as ceftiofur, enrofloxacin, and tilmicosin (Watts and Lindeman, 2006). Agar disc diffusion breakpoints are derived from the relationship between the zones of inhibition to the MIC (Craig, 2000).
Agar dilution is the gold standard, but it and broth macrodilution are often too
cumbersome for routine use and so are often replaced with broth microdilution (Walker, 2000). Broth microdilution involves using a microplate that contains antimicrobial agents of known concentration in progressive two fold dilutions that encompass similar concentrations to those obtained in serum and tissue at recommended doses (Walker, 2000). To perform broth microdilution, a bacterial suspension is made from an
overnight culture of a single randomly selected isolate, diluted to turbidity comparable to a 0.5 McFarland standard (Walker, 2000). This is further diluted so that the final concentration of bacteria per well is 5 x 104 colony forming units (Walker, 2000). The plates are then incubated for 16-20 hours (Walker, 2000). The minimum inhibitory concentration is recorded as the lowest concentration of antimicrobial that completely inhibits growth.
Broth microdilution and agar dilution both provide MICs by exposing the organism to a series of twofold log dilutions of the antimicrobial of interest (Jorgensen, 2004). These are the preferred methods of surveillance systems (Watts and Lindeman, 2006)
because they can demonstrate trends in MICs over time. Broth microdilution can be highly automated and, therefore, is capable of handling large volumes of samples.
The disadvantage is that broth microdilution utilizes MIC panels that are often inflexible as to the dilution and the antimicrobials available on a specified panel. Custom plates can be designed, but they are often cost prohibitive for many
laboratories. Another limitation is that because only a few (1-10) isolates/sample are selected for testing and MICs may fail to identify minority strains present in a complex polyclonal population unless a large number of isolates are investigated (Hedges et al., 1977, Humphrey et al., 2002). Also, under selective pressure of antimicrobial treatment, such minority species, if expressing a suitable phenotype, may be capable of dominating the microflora and potentially giving rise to sub-clinical or even clinical disease (Linton et al., 1978). As such random isolate selection may fail to fully describe the clinical importance AMR of any given bacterial population.