Antimicrobial Resistance In Bacteria Biology Essay

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Several methods, like disc diffusion, E-test, agar dilution, broth microdilution and broth macrodilution are suitable for in vitro antimicrobial susceptibility testing (AST). Whichever method is used, the tests have to be performed in accordance with an internationally accepted procedure, such as those published by the Clinical and Laboratory Standards Institute (CLSI) [1], the British Society for Antimicrobial Chemotherapy (BSAC) [2], the Deutsches Institut fu¨r Normung e.V. (DIN) [3], and the Comite´ de l'Antibiogramme de la Socie´ te´ Franc¸aise de Microbiologie (CA-SFM) [4] among others. The documents issued by these bodies are regularly updated and, since the methodologies and interpretative criteria change over time, it is important to follow the latest edition. Among these bodies, the CLSI is unique in that it produces separate documents for use in human and veterinary microbiology. The CLSI also differs from the other bodies in that its documents are not freely available, but must be purchased.

The status of the various types of documents is clarified below. The CLSI for example differentiates between ''standards'' and ''guidelines''. A ''standard'' is a document that clearly identifies specific and essential requirements for materials, methods, and practices to be used in an unmodified form. A standard may, in addition, contain discretionary elements, which are clearly identified. In contrast, a ''guideline'' is a document describing criteria for a general operating practice, procedure, or material for voluntary use. A guideline can be used as written or modified by the user to fit specific needs.

The current CLSI document for testing antimicrobial susceptibilities of bacteria isolated from animals, M31-A3 [1], is an approved standard and cannot be used in a modified form. Clear and precise instructions on how to perform Antibiotic Susceptibility Testing (AST) in vitro are given. They include, for example, the medium to be used (including any supplements required to support the growth of specific bacteria), the inoculum density, the incubation time, the temperature and test conditions. These instructions are not optional, but are strict rules that must be adhered to for good laboratory practice. Thus, statements such as ''Susceptibility testing mainly followed the recommendations given in the CLSI document M31-A3'' are not acceptable. Any deviation from the approved test conditions, such as the use of a different medium or extended incubation times for slow-growing bacteria, has to be specified and justified by the authors.

Most AST documents cover testing of numerous different bacterial species. However, for several bacterial pathogens relevant to the veterinary field, such as Haemophilus parasuis or Riemerella anatipestifer, no approved methodology exists.

If authors adopt a method approved for a phylogenetically closely related organism, it must be stated clearly that the method used has not been approved for the species tested, but for another member of the same genus (e.g., if the method for testing Haemophilus influenzae is used to test H. parasuis).Whenever susceptibility testing is undertaken on bacteria for which there is no approved standard available, the methodology chosen has to be validated first, as detailed in CLSI document M37-A3 [5].


It is essential to test approved AST reference strains in parallel with the test strains for quality control (QC) purposes. Lists of approved reference strains are included in the documents mentioned. They also contain acceptable Minimum Inhibitory Concentration (MIC) and zone diameter ranges for these reference strains and clearly state the methodology (e.g. broth microdilution) and the medium (e.g. Mueller-Hinton agar) that the values relate to. The reference strains must be relevant to the bacterial species tested, e.g. Escherichia coli ATCC125922 may be used when testing Enterobacteriaceae. Furthermore, authors must ensure (a) that reference strains are suitable for quality control of the antimicrobial agents tested, (b) that the range of concentrations (in broth microdilution) tested spans the entire approved QC ranges, and (c) that discs (in disc diffusion tests) contain the quantity of antimicrobial for which the QC ranges are approved.


AST studies seek to categorize bacterial isolates as susceptible, intermediate or resistant to each antimicrobial tested, on the basis of the MICs or the zone diameters obtained. Such classification requires approved interpretive criteria. Currently, two different types of interpretive criteria are available, clinical breakpoints and epidemiological cut-off values [6]. The precise emphasis of a particular study will dictate which criteria must be applied. If data are intended to guide a therapeutic approach (i.e., the aim of the study is to determine which antimicrobial agents are most likely to lead to therapeutic success), clinical breakpoints must be applied. Epidemiological cut-off values should be used to describe MIC distributions of bacteria without clinical context. Clinical breakpoints and epidemiological cut-off values may be very similar or even identical for some bacteria/drug combinations; however, authors need to understand that epidemiological cut-off values are determined by a different approach than clinical breakpoints and do not necessarily take into account the results of clinical efficacy studies, dosing and route of administration of the antimicrobial agents, nor the drug's pharmacokinetic and pharmacodynamic parameters in the respective animal species. The term ''breakpoint'' should be used exclusively for clinical breakpoints and ''susceptible'', ''intermediate'' and ''resistant'' categories should also be reserved for classifications made in relation to the therapeutic application of antimicrobial agents. When reporting data using epidemiological cut-off values, the term 'resistant' is inappropriate, rather bacteria should be reported as 'wild type' if the MIC or zone diameter falls within the wild type range, or 'non-wild type' if the MIC is higher or the zone diameter smaller than the wild type range.

The CLSI document M31-A3 [1] lists exclusively clinical breakpoints and includes the largest collection of approved clinical breakpoints for bacteria of animal origin currently available, a considerable number of which represent veterinary-specific breakpoints. Many of the latter have been approved for specific disease conditions often caused by particular bacterial species in defined animal host species. For example, approved clinical breakpoints for enrofloxacin in cattle apply exclusively for bovine respiratory diseases (BRD) due to Pasteurella multocida, Mannheimia haemolytica and Histophilus somni. The use of these breakpoints for other bovine bacteria and different disease conditions, e.g., Staphylococcus aureus from bovine mastitis, is unacceptable. Thus, the scope of application of the veterinary-specific breakpoints is clearly defined and cannot be altered.

All standards for performance of AST contain interpretive criteria which refer specifically to that particular methodology. Thus a certain methodology and its associated interpretive criteria are an entity, and as such belong together. It is not good practice to 'mix and match' testing methodologies and interpretive criteria issued by different organizations. Authors who perform E-tests must refer to the interpretive criteria given by the manufacturer of the E-test strips. Since these interpretive criteria are not veterinary-specific, but are adopted from human medicine, their true value for veterinary pathogens is unknown. The same holds for CLSI-approved breakpoints adopted from human medicine and listed in CLSI document M31-A3 [1].

Authors who describe AST of animal isolates, often use incorrect or out-dated interpretive criteria derived from their own or others' previous publications. This is also an inappropriate practice and often results in cumulative errors. Authors must ensure that correct (at the time of submission) interpretive criteria are used. In addition, there is an onus on reviewers to verify whether the correct interpretive criteria were used.

When comparing rates (percentages) of resistance between published studies, authors must make sure that the same methodologies and the same interpretive criteria have been used. Interpretive criteria often change over time and lowering the breakpoint(s) for a specific antimicrobial agent will result in a higher percentage of isolates being classified as resistant even if the MIC/zone size distribution of the population has not changed. As a consequence, an artefactual increase in the percentage of resistant strains may be noted. Publication of the full MIC distributions for each species/drug combination reduces the potential for this error since the data can be reanalyzed by others if interpretive criteria change. Such tables or histograms are often large and due to limitations on journal space, may need to be provided as supplement material.

Before performing disc diffusion, authors need to make sure that the discs contain the correct quantity of antibiotic for which interpretive criteria are available. Unfortunately, for many antimicrobial agents a range of discs with varying amounts of the antimicrobial agent are commercially available. However, zone diameter interpretive criteria are commonly available only for a single specific disc strength. For example, discs charged with 10mg, 15mg or 30mg erythromycin are available, but CLSI interpretive criteria and QC ranges for reference strains [1] refer only to zone diameters around a 15 mg disc. Since it is not possible to adjust the values measured with a 10mg or a 30mg disc to the approved values for a 15mg disc, zone sizes obtained with the 10mg or a30mg disc can neither be interpreted nor validated.

A standard dilution series for AST consists of doubling antibiotic concentrations and includes the reference concentration 1 mg/L (e.g., 0.125 mg/L, 0.25 mg/L, 0.5 mg/L, 1 mg/L, 2 mg/L, 4 mg/L, 8 mg/L, etc.). E-test strips indicate half-log values and so MICs determined by E-test should be 'rounded up' to the next highest value on the standard series. For example, if an E-test indicates that growth is inhibited at 0.38 mg/L (which is not a concentration in the standard series), the MIC should be rounded up and reported as 0.5 mg/L.


As quoted earlier CLSI clearly differentiates between "standards" and "guidelines." CLSI document M31, for testing antimicrobial susceptibilities of bacteria isolated from animals is an approved standard that cannot be used in a modified form. Clear and precise instructions on how to perform susceptibility tests are given which are not optional, but have to be adhered strictly for good laboratory practice.

Unfortunately, the scientific literature abounds in papers that claim to use CLSI methods, but display methodological details incompatible with CLSI recommendations. Common errors in the application of CLSI methods include the use of an incorrect medium, different antimicrobial potency for disk diffusion testing (e.g., using a 15 µg or 30 µg gentamicin disk rather than the required 10 µg disk), or results for drug combinations for which there are no CLSI clinical breakpoints (e.g., amoxicillin and Enterobacteriaceae). Statements such as "Susceptibility testing mainly followed the recommendations given in CLSI document M31" are not acceptable. All standards for performance of AST contain interpretive criteria that refer specifically to that particular methodology. Thus, a specific method and its associated clinical breakpoints are inseparable. It is not scientifically valid to "mix and match" testing methods and clinical breakpoints issued by different organizations.

Another common error is the use of out-of-date clinical breakpoints, especially if findings from multiple years are compared. As indicated elsewhere in this document, authors should use the most recent clinical breakpoints available at the time that statistical analyses are performed-not the criteria current at the time that susceptibility tests were performed. For example, if analyzing trends in percent resistance from 2000 through 2010, the 2010 breakpoints should be applied to MIC and disk diffusion measurements from all years to determine the correct interpretation, as best understood in 2010.

Reanalyzing historical data using current breakpoints is feasible, if the original quantitative results (MICs and disk diffusion zone diameters) have been stored and retained for analysis. It may not be possible to compare current findings with historical data if, for example, only test interpretations have been stored. Such reports should recommend caution to readers when interpreting historical trends for those species-antimicrobial combinations for which clinical breakpoints have changed. Similarly, when comparing resistance findings determined by breakpoints of different references bodies, e.g., CLSI and EUCAST, authors should note the limitations of such comparisons.

A number of investigators mistakenly believe that they have performed and interpreted susceptibility test results according to CLSI documents, yet did not follow CLSI protocols for QA. Reliable test results require an ongoing strategy for continuous quality assessment and improvement, and validating the adequacy of test reagents and the knowledge and skills of laboratory staff in performing, interpreting, and reporting results.

Table 1 gives additional examples of common errors and deviations from the CLSI recommendations that frequently have been observed in laboratories and in published or submitted manuscripts.


MIC50 and MIC90 values as well as the range of values obtained are important parameters for reporting results of susceptibility testing when multiple isolates of a given species are tested. The MIC50 represents the MIC value at which at least 50% of the isolates in a test population are inhibited; it is equivalent to the median MIC value. Given n test strains and the values y1, y2, . . ., yn representing a graded series of MICs starting with the lowest value, the MIC50 is the value at position n _ 0.5 as long as n is an even number of test strains. If n is an odd number of test strains, the value at position (n + 1) _ 0.5 represents the MIC50 value. The MIC90 represents the MIC value at which at least 90% of the strains within a test population are inhibited; the 90th percentile. The MIC90 is calculated accordingly, using n _ 0.9. If the resulting number is an integer, this number represents the MIC90; if the resulting number is not an integer, the next integer following the respective value represents the MIC90. MIC50 and MIC90 values should always be presented as concentrations on the standard AST dilution series. If using a statistical package to calculate the values, never use intermediate values. It should be noted that MIC50 and MIC90 values are not necessarily suitable parameters to describe bimodal or trimodal MIC distributions, although a discrepancy of several dilution steps between the MIC50 and MIC90 values, e.g., MIC50 at 0.25 mg/L and the MIC90 at 16 mg/L, might point towards the presence of at least two subpopulations which differ distinctly in their MICs to a given antimicrobial agent. As an example, in a test population of 70 strains, the MIC50 is the value at position 35 and the MIC90 the one at position 63 in a graded series of MICs starting with the lowest MIC value at position 1. In a test population of 71 strains, the MIC50 is the value at position 36 and the MIC90 the one at position 64 in the aforementioned graded series of the MICs.

Although MIC50 and MIC90 values can also be calculated for small test populations of, e.g., 10-30 strains, under such conditions few strains with high MICs will have a disproportionately high influence on the MIC50 and MIC90 values. Thus, researchers are encouraged not to overemphasize MIC50 and MIC90 data obtained from small test populations. Since the significance of MIC50 and MIC90 increases with the numbers of strains tested, sufficiently large test populations should be used for most meaningful statements on MIC50 and MIC90 values.


The term 'multi-resistance' exclusively refers to acquired resistance properties. Bacteria may occasionally exhibit intrinsic (primary) resistance to certain antimicrobial agents. Intrinsic resistance may be based on either the lack or the inaccessibility of the antimicrobial target site among the bacteria in question. In other cases, intrinsically resistant bacteria produce inactivating enzymes, such as species-specific β-lactamases, contain multidrug transporters, and/or exhibit permeability barriers [7, 8]. Such intrinsic resistances must be excluded when describing multi-resistance patterns.

There is no universally accepted definition of 'multi-resistance'. As a consequence, this term is used inconsistently in the literature. The following suggestions are intended to provide guidance for the most accurate presentation of multi-resistance patterns:

1. If only phenotypic susceptibility testing is performed, resistance to three or more classes of antimicrobial agents can be referred to as multi-resistance. For example, resistance to enrofloxacin, marbofloxacin, difloxacin and orbifloxacin represents resistance to one antimicrobial class, since all agents are fluoroquinolones and resistance is most likely mediated by the same mechanism(s). In the case of fluoroquinolones (and some other antimicrobial classes), resistance to a single representative of this class of antibiotic agent can reasonably be extrapolated to resistance (or reduced susceptibility) to other members of that class. However, single class representatives cannot always be validly defined, e.g. for β-lactams and aminoglycosides. In these cases, resistance is not a class effect and multiple, diverse resistance mechanisms exist, each of which confers resistance to sub-groups of the respective antimicrobial class. Resistance to sub-groups should be counted separately, e.g., resistance to streptomycin and spectinomycin is distinct from resistance to gentamicin, kanamycin and/or tobramycin.

2. If phenotypic susceptibility testing is supplemented with molecular analysis for the resistance genes present, multi-resistance should be assessed at the molecular level. Bacterial isolates exhibiting the presence of three or more resistance genes or mutations, all of which are associated with a different resistance phenotype (i.e., affecting different antimicrobial classes or sub-groups), may be referred to as multi-resistant. Exceptions to this rule would include those cases where a single resistance gene or a gene complex is associated with resistance to structurally and/or functionally different antimicrobial agents, e.g., the gene cfr for resistance to phenicols, lincosamides, oxazolidinones, pleuromutilins, and streptogramin A antibiotics [9] or the erm genes for combined resistance to macrolides, lincosamides and streptogramin B antibiotics [10].


The breakpoint Minimum Inhibitory Concentration (MIC) for an antimicrobial agent and a bacterial pathogen has traditionally been the threshold above which the pathogen is unlikely to respond to treatment with the specified antimicrobial agent. However, breakpoints are becoming contentious because of differing and incompatible demands being placed on what has hitherto been a single parameter. In particular, the needs of the clinician and the epidemiologist are different.

What the veterinary clinician needs: A clinician choosing an antimicrobial agent to treat an animal suffering from a specific infection needs to know that the compound chosen should be effective against the pathogen involved (although a clinical result may be affected by several other factors such as formulation and dosage). To this end, the MIC is ideally obtained for the pathogen in vitro, and this is compared with the pre-determined clinical breakpoint to determine whether the organism is likely to respond in vivo. The clinical breakpoint should have taken account of the behaviour of the drug following administration, and assumes that if an isolate shows an MIC below the allocated clinical breakpoint for the pathogen, then a clinical response should be obtained if the drug is dosed as recommended, and there are no other factors to affect the outcome. Conversely, an MIC for the target pathogen found to be above the clinical breakpoint indicates resistance and that an alternative treatment should be considered. Knowledge of the appropriate breakpoint (whether expressed as an MIC, or indirectly through an inhibition zone diameter) is even more important as veterinarians are increasingly expected to defend their choice of antimicrobial agent against accusations of imprudent or indiscriminate use. In reality, however, specific veterinary breakpoints, especially for older compounds, may not be clearly established [11].

What the epidemiologist needs: The MIC distribution pattern often enables identification of two or more populations of microrganisms that can be differentiated by the presence or absence of resistance factors. This is illustrated in Fig 1. The wild-type (WT) "susceptible" subpopulation is assumed to show the antibiogram profile before any resistance has developed or has been acquired, and its distribution can be differentiated clearly from the "resistant" subpopulation.

Where full resistance is achieved by a single step (perhaps through acquisition of a plasmid or a single point mutation), then an isolate may be expected to fall clearly into one of the two major subpopulations- either fully susceptible, or having acquired the plasmid, fully resistant. However, where resistance is achieved in a series of steps, for example combination of efflux mechanisms and point mutations, then an isolate may fall somewhere in between depending on the number of steps passed. A dividing or cut-off MIC value can thus be established to indicate the MIC above which the pathogen has some discernable reduction in susceptibility. This value should be based on an adequate number of isolates to give confidence that the WT population has been identified, and will normally be placed close to the WT population. In veterinary medicine there is in fact a shortage of large databases on which to base a good estimate of the wild-type population. The epidemiological cut-off value will often (although not always) be lower than the breakpoint used for clinical prediction. In that case, taking the hypothetical illustration in Fig. 1, an isolate with an MIC of, say 4 µg/mL (shown as "intermediate population) may yet be expected to respond clinically. Thus a breakpoint set by clinical criteria may fail to identify emerging resistance although it may be perfectly adequate to predict clinical efficacy. Conversely a breakpoint set by epidemiological criteria may imply that a potential treatment would fail, yet in fact it could respond since it may yet fall below the clinical breakpoint for the particular agent and organism.

The need for clear terminology: The objective of a single universal breakpoint to achieve both (a) detection of the early stages of resistance development among a bacterial population and (b) predicting outcome of therapy will continue to fail in many circumstances, and will be a source of confusion among veterinary clinicians, clinical microbiologists, and regulators. MIC breakpoints for clinical purposes are defined against a background of data, including therapeutic indications, clinical response data, dosing schedules, pharmacokinetics and pharmacodynamics. Although the process of determining such breakpoints never was, and probably never will be, exact or strictly scientific [12], clarity of definition is essential.


As indicated above, conducting AST and subsequent data interpretation is a complex matter. A number of competent authorities provide instructions for performing AST and data interpretation. Each should be followed precisely. Importantly, protocols for AST and data interpretation from different authorities cannot be interchanged. AST data intended for the recommendation of therapy should be interpreted and reported using clinical breakpoints, whereas AST data intended for surveillance purposes may be reported using epidemiological cut-off values. Moreover, the comparison of data generated in different studies requires not only a common methodology, but also the preferential presentation of the data as MIC distribution which allows for fast and easy re-evaluation of the original data even if the interpretive criteria change over time. This editorial is not only published in this journal, but also in others to emphasize its importance.

The term "breakpoint" should be retained solely for clinical breakpoints and be distinguished from the "epidemiological cut-off point", where the latter shows that a change away from the wild-type population may have occurred in a subpopulation. This terminology is used by European Committee on Antimicrobial Sensitivity Testing [12].

Universal adoption and understanding of such separate terminology would enable clinicians to choose appropriate treatment based on information relevant to the individual patient, yet would recognise that epidemiologists need to be aware of small changes in bacterial susceptibility which may indicate emerging resistance, and allow for appropriate control measures to be considered.