Antibiotics in Laboratory Medicine, 6 Ed.

Chapter 9. Molecular Methods for Detection of Antibacterial Resistance Genes: Rationale and Applications

Kristin Hegstad, Ørjan Samuelsen, Joachim Hegstad, and Arnfinn Sundsfjord

THE CHALLENGE

The emergence and spread of antibiotic resistance in clinically important bacteria represent a multifaceted challenge in clinical microbiology. Rapid identification of pathogens and prediction of their antimicrobial susceptibility has important therapeutic and prognostic implications for individual patients (1). Detection of patients colonized by clinically important resistant bacteria is instrumental for efficient infection control measures (2–4). Moreover, elucidation of antimicrobial resistance mechanisms at a molecular level is fundamental in diagnostic interpretation of resistance phenotypes, understanding of the origins of resistance mechanisms, identification of transmission routes and vehicles for dissemination, and development of new antimicrobials (5,6).

Thus, we need specific and rapid diagnostic methods to guide antimicrobial therapy and infection control interventions as well as accurate and efficient techniques for detection of genetic and biochemical mechanisms involved in the development and spread of antibiotic resistance. In this review, we describe the rationale for molecular detection of antimicrobial resistance genes, advantages, and limitations; address relevant technical aspects; and discuss the application of these methods for specific clinical or epidemiologic purposes.

Enormous progress has been made in our understanding of the genetics and biochemistry of antimicrobial resistance (5,7). This knowledge has important conceptual implications in a discussion of the use of molecular methods in detection of antimicrobial resistance. Most antimicrobials are nature’s own products or derivatives developed by microorganisms in their competition for life and space. Thus, bacteria have evolved protective mechanisms that predate the antimicrobial era to avoid their own or others’ inhibitory actions. Characterization of the antimicrobial resistome has revealed the presence of protoresistance genes with a phylogenetic relationship and potential to evolve into a resistance gene (5).

The genetic information encoding protective measures may be passed on to daughter cells (vertical transmission) or to other bacteria through transformation, transduction, or conjugation (horizontal gene transfer). The genetic basis for antimicrobial resistance includes (a) the acquisition, stabilization, and expression of new DNA by horizontal gene transfer or (b) mutations in cellular genes or acquired genes that alter antimicrobial target sites or affect gene expression. Recently, the concept of adaptive resistance has been introduced. Adaptive resistance involves transient alterations in gene and/or protein expression, including porins and efflux pumps, due to environmental stress that reverts after removal of the trigger (8). The genetic alterations or adaptations mediate a diversity of biochemical mechanisms of antimicrobial resistance: (a) enzymatic modification of antimicrobial agents; (b) target substitutions, amplification, or modifications bypassing the binding or reducing the affinity for the antimicrobial agent; (c) barriers or efflux pumps reducing the access to the target.

Mutational resistance within a bacterial population and horizontal gene transfer events may not be frequent and the acquisition of modified or new genetic information mediates a biologic cost to the host that hamper expansion of the recipient. However, antimicrobial selection creates opportunities and ecologic niches for biologic amplification of antimicrobial resistance determinants and their hosts (9). Moreover, bacteria have developed compensatory mechanisms of fitness costs and host elements for capturing, stabilization, and mobilization of new genetic information, systems that favor long-term persistence of antimicrobial resistance genes without the exposure to selection (10,11).

Genetic and biochemical research in antimicrobial resistance have also provided insight into the molecular basis for cross- and coresistance (7). The concept of cross-resistance is based on mutations in overlapping antimicrobial targets, enzymatic modification, and drug efflux mechanisms affecting the susceptibility of antimicrobials across classes. The increased occurrence of genetically linked and coexpressed resistance determinants in R plasmids, integrons, and transposons illustrates the concept of coresistance and the selection of multiple resistance mechanism by the use of a single antimicrobial.

In clinical terms, the characterization of biochemical mechanisms for antimicrobial resistance and their genetic support has been important in the improvement of antimicrobial susceptibility testing and therapeutic interpretation of resistance phenotypes (12). Interpretive reading of antibiogram data involves the deduction of resistance mechanisms from susceptibility test results and interpretation of clinical susceptibility based on resistance mechanisms (13).

Phenotypic antimicrobial susceptibility testing requires growth of bacteria in pure culture and may routinely take at least 24 to 48 hours to obtain a valid result. Antimicrobial susceptibility testing of slow-growing organisms such as Mycobacterium tuberculosis may take even weeks or months (14). Thus, the development of rapid molecular assays may provide an attractive diagnostic approach as a guide to treatment options (15,16).

The advantages of genetic detection of antimicrobial resistance include the following: (a) A YES or NO answer if the presence of a defined resistance determinant is provided. (b) Not dependent on clinical categorization of susceptibility breakpoints, which may vary between countries and authoritative institutions. (c) Ability to detect resistance mechanisms involved in low-level resistance that could be difficult to detect by phenotypic methods. (d) Genetic assays can be performed directly with clinical specimens and bypass phenotypic expression reducing the time for detection. This is particularly important for difficult-to-culture organisms. (e) Easy and early interpretation allows early therapeutic predictions. (f) Genetic assays may reduce the biohazard risk associated with handling of culture-based techniques.

However, there are also drawbacks and pitfalls in the molecular approach: (a) Genetic predictions are based on screening for resistance determinants, whereas the preferred antimicrobial therapy is based on the detection of susceptibility. (b) You can, in principle, only detect what you already know and genetic methods do not take into account new resistance mechanisms. Thus, validated genetic methods generally have a high specificity but a lower sensitivity due to unknown resistance mechanisms not covered by current molecular assays. (c) There are silent genes, pseudogenes, or protoresistance genes that may cause false-positive results. (d) Mutations in primer binding sites may preclude PCR amplification generating false-negative results. (e) Low clinical sensitivity when performed directly on clinical samples due to inhibition of nucleic acid amplification or a limited number of targets. (f) Finally, regulatory environmental adaptations that only affect gene expression (adaptive resistance) are not detected unless a quantitative assessment of the specific mRNA is performed (8).

Hence, the genetic approach based on today’s concepts cannot displace phenotypic methods in routine antimicrobial susceptibility testing of rapid-growing clinical relevant bacteria. Novel resistance mechanisms will arise continuously by mutations and regulatory adaptations, mobilization of unknown preexisting resistance genes from environmental reservoirs, and evolving protoresistance genes to resistance genes. However, genotypic methods should be endorsed for clinically important slow-growing organisms with increasing resistance problems based on chromosomal mutations such as M. tuberculosis. Moreover, the success of genetic assays in detection of antimicrobial resistance is also dependent on technical improvements; speed, accuracy, and user-friendliness may provide cost-saving formats of molecular assays. Apparently, the recent advances in whole genome sequencing (WGS) and bioinformatics workflows are of interest and, in particular, with regard to in silico antimicrobial susceptibility testing in surveillance and infection control (17–22).

New molecular diagnostics tools and new combinations of existing technology are continuously developed. Thus, the technology presented herein represents a snapshot as of early 2013 focusing mainly on nucleic acid amplification techniques (NAATs) and microarrays as well as giving a glimpse into the rapidly evolving technologies matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) and next generation sequencing for use in the molecular diagnostics of antimicrobial resistance.

Nucleic Acid Amplification Techniques

Many different NAATs have been developed. Some test principles and their relevant characteristics in the detection of antimicrobial resistance mechanisms are listed in Table 9.1. NAATs amplify restricted parts of DNA/RNA for the sample in question in a logarithmic manner, ending up with billions of copies per reaction tube. All these copies of DNA/RNA makes amplification techniques well suited for sensitive assays.

 

Table 9.1 descriptions include commonly used NAATs such as traditional polymerase chain reaction (PCR), multiplex PCR, real-time PCR, nucleic acid sequence-based amplification (NASBA), loop-mediated isothermal amplification (LAMP), and helicase-dependent amplification (HDA). Several detection systems used by real-time PCR are not mentioned, that is, Scorpions primers (Biosearch Technologies, Petaluma, CA), MGB Eclipse probes (EliTechGroup, Paris, France and Life Technologies, Grand Island, NY), Light-up probes (LightUp Technologies AB, Huddinge, Sweden), HyBeacon probes (Hain Lifescience GmbH, Nehren, Germany), Yin-yang probes (QuanDx, Menlo Park, CA), or Amplifluor (EMD Millipore, Billerica, MA). Examples of a real-time PCR melt curve and an amplification plot from real-time PCR probe detection are displayed in Figures 9.1 and 9.2, respectively.

Microarrays

The traditional Southern or Northern blot hybridization principles were used to develop microarrays for fast parallel, high-throughput detection and quantitation of nucleic acids (23). In nucleic acid arrays, hundreds or thousands of sequence-specific probes such as oligonucleotides or PCR products are deposited in fixed regions on a solid support or chip. Labelled targets applied to the solid support then hybridize to sequence-specific regions. The purposes for application of microarrays include large-scale genotyping (including single nucleotide polymorphism [SNP] analyses), gene expression profiling, and comparative genomic hybridizations (including copy number variation analysis). For a thorough introduction to microarray technology, including its applications, fabrication, target preparation, hybridization, detection, and data analysis, see Dufva (24). Both in-house and commercial microbial diagnostic microarrays have been developed to detect microbes as well as genes involved in antimicrobial resistance and virulence (25). The easy-to-use commercial microarray technology multiplexing power is attractive for antimicrobial resistance screening in central high-throughput facilities or hospital labs. A limitation of microarrays is that the signal does not provide any other information than the presence of the target. The size or complete sequence of the captured target molecule is not revealed.

The Application of Matrix-Assisted Laser Desorption-Ionization Time-of-Flight Mass Spectrometry Opens New Perspectives in the Detection of Antimicrobial Resistance

Bacterial identification based on mass spectral fingerprints obtained by MALDI-TOF MS is now routinely used in many clinical laboratories. The use of this technology in identification of antimicrobial resistance is rapidly increasing. For a detailed presentation of the use of MALDI-TOF MS in detection of antimicrobial resistance mechanisms, see Hrabak et al. (26). Briefly, antimicrobial resistance can either be revealed by changes in whole cell protein mass spectra when comparing susceptible and resistant isolates; by changes in mass spectra representing antimicrobials and their enzymatic degradation products or wild type and modified proteins/RNA; or by peptide, RNA, and DNA mini-sequencing (26–29).

The potential use of MALDI-TOF MS in detection of vancomycin-resistant enterococci (VRE) (30) and methicillin-resistant Staphylococcus aureus (MRSA) have been described but needs further refinements and validation (31). MALDI-TOF assays have also been developed to identify the enzymatic degradation of β-lactams by β-lactamases (32,33) or to reveal methylation of 23S rRNA by the cfr(chloramphenicol–florfenicol resistance) gene (34). Furthermore, MALDI-TOF MS–based mini-sequencing can reveal nucleotide polymorphisms responsible for antimicrobial resistance, that is, TEM-type extended-spectrum β-lactamase polymorphisms (35) and drug-resistant M. tuberculosis (36). Proteomic analyses using MALDI-TOF MS to identify proteins associated with resistance by peptide mass fingerprinting following sodium dodecyl sulfate polyacrylamide gel electrophoresis or 2D electrophoresis has been used to identify outer membrane or periplasmic proteins with different expression levels in resistant compared to susceptible isolates (37–41). Application of MALDI-TOF MS in proteomic analyses can complement molecular genetic techniques in reference or research laboratories. However, some of their applications will be challenged by the use of WGS in the near future (26).

Nucleotide Sequencing Techniques and Their Application in Detection of Antimicrobial Resistance

Traditional Sanger dideoxy terminator sequencing, the gold standard for 30 years, has mainly been used to identify SNPs resulting in antimicrobial resistance rather than determining the presence of acquired resistance genes. Once the acquired genetic trait has been explored, the presence or absence of this is sufficient to reveal resistance mechanisms. The expanding need for whole genome sequence information has fuelled a technical revolution. Today’s sequencers provided large volumes of genetic information in high resolution at dramatically decreased cost. Recent reviews have in detail described available first- to fourth-generation sequencing methods and their relevant characteristics and applications (42,43).

The turnaround time, cost, and user-friendliness of WGS have improved tremendously. Thus, whole bacterial genome sequencing is predicted to be a future routine method for species identification, the examination of antimicrobial resistance and virulence determinants as well as monitoring the evolution and clonal spread of bacterial pathogens (18).

Rapid WGS has already been used to investigate outbreaks of MRSA (44) and carbapenem-resistant Klebsiella pneumoniae (45) and to unravel the molecular mechanisms in development of antimicrobial resistance during antimicrobial treatment of infections with multidrug-resistant Acinetobacter baumannii (46) and K. pneumoniae (45). Zankari et al. (47) have developed a continuously updated Web-based program (ResFinder at http://www.genomicepidemiology.org) presenting an easy way to identify acquired antimicrobial resistance genes in whole genome data. However, it is important when using this database to adjust the software ID threshold to less than 100% to find resistance genes that have mutations not recorded in the database. Furthermore, the results are categorized into different antimicrobial groups, but it is still important to understand the resulting genetic information in the context of the antimicrobial susceptibility profile.

The use of sequencing in clinical microbiology also call for a quality standard for sequence-based assays defining DNA sequence quality as well as quality of reference sequences from external databases. Extended comments on automated sequence quality assessments and the quality control of currently available databases have been pertinently outlined by Underwood and Green (48).

It is critical that the molecular assays are sufficiently validated and quality assured for diagnostic purposes. This is not obvious even for methods published in peer review journals (authors own experiences). The validation of an assay has some key parameters to test such as sensitivity, specificity, accuracy, precision, limit of detection, detection range, repeatability and reproducibility, and external quality assessment (EQA)/proficiency testing, for example, Quality Control for Molecular Diagnostics (http://www.qcmd.org) (49,50).

Nucleic Acid Extraction

High-quality RNA/DNA provided by nucleic acid extraction is a prerequisite for the performance of NAAT. Both in-house and commercial as well as manual, semi-automated, and fully automated extraction systems are used for nucleic acid extraction. Silica solid-phase extraction by centrifugation or vacuum, coated and uncoated magnetic beads extraction, and magnetic silica beads extraction are commonly used in automated systems. The four main steps in nucleic acid extraction are cell disruption, lysis, wash and removal of cell debris and inhibitor buffer, and, finally, recovery of pure nucleic acid without inhibitors.

Inhibitors and enhancers can influence the sensitivity of a NAAT-based method at all stages. Inhibitors can originate from the clinical sample or extraction buffers, typically the lysis buffer or ethanol. The inhibitors can be the result of suboptimal extraction protocols not suitable for the test material or difficult-to-treat clinical samples such as sputum or whole blood.

The credibility of the sample result of a NAAT depends on the validation process of the assay and on types and number of controls that runs every time the assay is performed. The controls are meant to assure you that the process has been optimally performed. During nucleic acid extraction, positive and negative process controls (PPC and NPC) are needed. The PPC is a known positive reference strain that is diluted to 1 log above the limit of detection. Transport medium or ddH₂O is typically used as NPC. The purpose of the PPC is to confirm that the extraction process is performed optimally. If the PPC is negative after the NAAT, you need to rerun all samples from extraction. The purpose of the NPC is to check for cross-contamination during extraction.

An internal control (IC), also called internal amplification control (IAC) or internal positive control (IPC), is an inhibition control. The IC can be an oligo, plasmid or purified PCR product that will be amplified during the NAAT. Inhibition control is preferably introduced before the extraction step, for example, spiked in the magnetic beads solution, but can also be introduced from the amplification step, for example, spiked in the NAAT master mix. All negative samples should detect the IC; otherwise, the sample result should be discharged. The sample or nucleic acid elute should then be diluted 1:1 and rerun. When performing NAAT, it is recommended to include a positive and a negative amplification control.

Characteristics of Methicillin-Resistant Staphylococcus aureus

S. aureus is a major human pathogen within health care institutions and in the community. Thus, the overall resistance profile in clinical strains of S. aureus has an important impact on guidelines for empirical treatment of bacterial infections in general and bloodstream infection in particular. Wild-type S. aureus is naturally susceptible to β-lactam antimicrobials with the exception of monobactams. The high prevalence of penicillinase production in S. aureushas rendered the penicillinase-stable penicillins (oxacillin, cloxacillin, nafcillin, methicillin) the most active β-lactams.

Resistance toward penicillinase-stable penicillins in S. aureus is named methicillin resistance although this antimicrobial is not in clinical use. Methicillin resistance in S. aureus (MRSA) is caused by the acquisition of a mecAgene encoding a β-lactam low-affinity penicillin-binding protein (PBP), termed PBP2a or PBP2’. PBP2a substitute the essential functions of the high-affinity PBPs in the presence of β-lactam antimicrobials, rendering the bacteria resistant to this important class of antimicrobials (51). The regulation of mecA expression is complex. Expression of mecA in a minor fraction of the bacterial population (heterogeneous expression) challenge phenotypic detection and requires molecular confirmation (52).

The new cephalosporins (ceftobiprole and ceftaroline) have a strong affinity for PBP2a and are active against MRSA (53). However, penicillinase-stable penicillins remain the reference β-lactams in the treatment of S. aureusinfections in the absence of methicillin resistance. Infections with MRSA are associated with higher morbidity and mortality and increased hospital costs (54). Thus, rapid and accurate detection of MRSA from pure culture or directly in clinical samples are important for tailoring individual antimicrobial treatment as well as the implementation of appropriate infection control measurements to prevent the spread in health care institutions. Molecular techniques are used to confirm phenotypically suspected MRSA and to reduce the detection time in clinical samples.

Molecular Methods for Detection of Methicillin-Resistant Staphylococcus aureus

The development of molecular methods for detection of MRSA has been based on our current understanding of the genetic support of the mecA gene and its wide distribution in S. aureus and several coagulase-negative staphylococci (CoNS). The conserved 2.1 kb mecA gene is carried by a mobile genetic element in staphylococci, designated the staphylococcal cassette chromosome mec (SCCmec) (55). The SSCmec varies in size and content. A number of SCCmec types have been characterized (http://www.sccmec.org/Pages/SCC_HomeEN.html) and more diversity is to be expected. SSCmec encode recombinases (cassette chromosome recombinases [ccr]) that mediate excision and site-specific integration at the chromosomal attB site near the 3′ end of orfX.

An array of different molecular strategies has been developed for the detection of MRSA, and selected publications are presented in Table 9.2. Some methods have targeted mecA itself and linked S. aureus–specific chromosomal genes (nuc, femA) in multiplex formats to differentiate between MRSA and other methicillin-resistant staphylococci (56–58). New insights into the detailed organization of SCCmecprovided new concepts for MRSA-specific PCRs bridging the SSCmec-chromosomal orfX junction site (59). Developments of these strategies into real-time PCR assays have significantly improved their application in clinical microbiology. These methods are, together with the immunologic detection of PBP2’, used as standard tests for MRSA detection and confirmation.

Challenges and Possibilities for Molecular Diagnostics of Methicillin-Resistant Staphylococcus aureus

The recent detection of a novel mecA homologue in human and bovine S. aureus populations has challenged our current molecular methods for detection of MRSA (60). The new mecA homologue is now classified as mecC in line with phylogenetic principles. mecC shows only 70% nucleotide sequence homology to mecA. Consequently, mecC and its corresponding PBP is not detected by conventional mecA-based PCRs or commercial immunologic PBP2’ assays, respectively (61). Recent progress in molecular detection of MRSA has taken our extended knowledge on mec-alleles into consideration, both in the design of new PCR formats (62,63) and in a rapid microarray-based detection (64).

The increasing repertoire of clinically relevant mec-homologues will also challenge the prospects for a rapid proteomic-based approach in the detection of MRSA. Both MALDI-TOF MS methods as well as surface-enhanced laser desorption-ionization time-of-flight (SELDI-TOF) MS has been described for the discrimination between methicillin-susceptible S. aureus (MSSA) and MRSA (31,65). A recent review on the application of MALDI-TOF MS in the detection of antimicrobial resistance concluded that the previously mentioned test needed further validation, although reproducible MRSA-specific profiles were obtained (26).

In conclusion, genetic detection of MRSA from pure cultures and complex clinical samples can be approached by a diversity of amplification-based techniques including in-house and commercial methods (66). Proteomic-based assays, except immunologic PBP2’-detection, need further refinements to be used in routine diagnostics. Methods based on the detection of SCCmec integration sites should take into account the increasing modular and sequence diversity in SCCmec types that may provide both false-positive and false-negative results. Moreover, antimicrobial selection will continue to facilitate transfer and stabilization of new mec homologues from commensals to S. aureusand challenge our molecular diagnostic repertoire targeting only known mec types (61).

VRE and vancomycin-resistant Enterococcus faecium (VREfm) in particular are common nosocomial pathogens worldwide (67). The rates of vancomycin resistance monitored in medical centers in Europe, North and Latin America, and the Asia-Pacific region in 2004 to 2006 were less than 5% for Enterococcus faecalis and varied from 12% in Europe to 66% in North America for E. faecium (68). The implementation of measures to control health care–associated VREfm are by many considered unmanageable with those resistance rates. However, the burden of VRE infections should not be belittled (70). VRE bloodstream infections are associated with increased mortality. Increased density of van-determinants and associated resistances will raise the risk of transfer to other gram-positive pathogens.

The van Alphabet

The vancomycin resistance cluster (van) alphabet in enterococci currently consist of nine gene clusters, namely the acquired vanA, vanB, vanD, vanE, vanG, vanL (69), vanM (71), and vanN (72), and the intrinsic vanC genotype in Enterococcus gallinarum and Enterococcus casseliflavus. Resistance is due to synthesis of altered peptidoglycan precursors with peptide side chains that terminate in D-lactate (vanA, vanB, vanD and vanM) or D-serine (vanC, vanE, vanG, vanL, and vanN) for which vancomycin has lower affinity than the normal D-alanine side chain terminus (73–76). Their characteristics and species distribution are summarized in Table 9.3. Both vanA, vanB, vanG, vanM, and vanN have been shown to be transferable between enterococci as part of large conjugative chromosomal elements or plasmids (69,71,72). However, the vast majority of VRE is associated with vanA and vanB determinants hosted by E. faecium or E. faecalis. Importantly, several independent cases of vanA transfer to S. aureusand MRSA have been reported (77). S. aureus may coexist with VRE in the gastrointestinal tract or superficial wounds, providing a likely reservoir for development of vancomycin-resistant S. aureus (VRSA) (78).

The vanA genotype is currently the most prevalent VRE genotype worldwide, but rates of infections with vanB-type VRE (mainly VREfm) infections are increasing in several European countries and are predominant in Australia (79–85). In contrast to vanA, the vanB ligase gene has been divided into three subtypes, vanB1–3, based on phylogenetic diversity (86–88). The most prevalent vanB2 subtype (89–100) has been identified in adapted bacterial genera of the normal intestinal flora such as Atopobium, Clostridium, Ruminococcus, Eggerthella, and Streptococcus (101–104). The vanB2 subtype has also been observed in two clinical samples of Atopobium and Clostridium (104). Interestingly, the vanB2 subtype has a high prevalence in community and hospital human fecal specimens in the absence of cultivable VRE (105–107). The high rates of nonenterococcal vanB in fecal samples result in a low predictive positive value for VRE using PCR detection of vanB directly from fecal samples (107–111), whereas vanAdetection is more specific (111–113).

Possible Methods for Molecular Detection of van Genes

MALDI-TOF MS technology has been used to identify and investigate the epidemiology of an outbreak with vanB-positive VREfm (30), and an array of Raman-enhancing nanoparticles coated with vancomycin has been employed to capture VRE from human blood (114). Thus, the future holds promise for use of novel techniques to detect VRE. However, today, most described techniques for molecular detection of glycopeptide resistance involves amplification of the van genes.

A number of amplification techniques to detect the glycopeptide resistance genes have been developed. Methods that detect at least the two most common van genotypes (vanA and vanB) and evaluated on well-characterized strain collections or clinical specimens in comparison with in vitro susceptibility tests are listed in Table 9.4.

Amplification techniques are easy and useful tools for reference laboratories and routine labs that wish to confirm the phenotypic detection or investigate the molecular epidemiology of VRE. However, there are some aspects that are important to consider when applying these techniques. The vanB, vanD, and vanG determinants have subtypes. Thus, primers and probes described in the literature to hybridize to these van genotypes have been checked in silico against all subtypes to reveal ambiguities and notes of which subtypes they are likely to cover have been made in Table 9.4. Importantly, although the vanB2subtype is the most widespread subtype of vanB, not all PCR-based methods detect this subtype.

Because the van genes can be found in other bacterial genera than enterococci, it is important to consider when performing screening on biologic samples that many molecular methods detect the van genes and not VRE per se. Methods that detect only the van genes are thus expected to have a higher rate of false-positive results. Some of the methods listed in Table 9.4 include species-specific (E. faecalis and E. faecium ddl, E. faecium recG) or genus-specific (tuf) genes for identification of enterococci or staphylococci (S. aureus nuc, Staphylococcus epidermidis species-specific gene) to overcome this problem.

An oligonucleotide DNA microarray with 105 probes that target 42 genes of the glycopeptide resistance gene clusters vanA, vanB, vanC, vanD, vanE, and vanG including the subtypes of vanB, vanD, and vanG as well as detection of ermB and the E. faecalis specific gene lsa correctly identified the different genotypes of reference and other VRE strains with various phenotypes (115). This microarray give additional and complementary information compared to phenotype alone and is suitable for reference laboratories that wish to reveal the genetic content of the van clusters explaining defective gene clusters and identifying additional resistance elements masked by a similar resistance phenotype. This array is not commercially available. Moreover, all presently known van clusters are not included in this array. Thus, WGS will be a better research approach to identify all present resistance elements contributing to a phenotype because this will also give the opportunity to explore the unknown.

Characteristics of Resistance to Macrolide, Lincosamide, and Streptogramin Antibiotics

A multiplicity of clinical relevant mechanisms of macrolide, lincosamide, and streptogramin (MLS antimicrobials) resistance is found (116–119). A recently updated database on MLS resistance genes is available at http://faculty.washington.edu/marilynr/. The nomenclature review of MLS resistance genes in 1999 defined that a new MLS gene must have a 79% or less amino acid identity with all previously characterized MLS determinants before receiving a unique name (116). The conservative criteria are controversial for some of the genes, as determinants with higher identity score may have different host range and genetic support (118,120). Herein, we focus on the most prevalent and clinical relevant determinants of resistance and their molecular detection. Phenotypic antimicrobial susceptibility testing distinguishes between the main groups of MLS resistance mechanism and guides antimicrobial therapy. Thus, the main purpose for genotypic identification is related to molecular epidemiology issues, understanding the dissemination and origins of MLS-related resistance determinants and their dynamics.

MLS antimicrobials have different chemical structures, but they share similar mechanisms of action. They are all inhibitors of bacterial translation. The structural analysis of bacterial ribosomal subunits in complex with antimicrobial inhibitors at an anatomic level has revealed their overlapping target sites (the peptidyl transfer center and the peptide exit tunnel) in the 50S subunit complex (121). Thus, they share many of the same resistance mechanisms (122).

The most commonly used macrolide antimicrobials include the natural product drug erythromycin and the semisynthetic derivatives clarithromycin and azithromycin. Macrolides are classified according to the number of atoms in the macrolactone ring: 14-membered (erythromycin and clarithromycin), 15-membered (azithromycin), and 16-membered (spiramycin). Ketolides (telithromycin) are semisynthetic derivatives of macrolides. Lincosamides (clindamycin and lincomycin) lacks the lactone ring. Streptogramin antimicrobials consist of a mixture of type A peptide–polyketide hybrids and type B cyclic depsipeptides that act synergistically by binding to the peptidyl transfer center and the peptide exit tunnel, respectively (5).

The spectrum of antibacterial activity of MLS antimicrobials is mainly restricted to gram-positive cocci (staphylococci and streptococci) and bacilli and gram-negative cocci. Gram-negative bacteria are, in general, inherently resistant to macrolides due to efflux mechanisms and drug inactivation. Exceptions include important human pathogens such as Bordetella pertussis, Campylobacter spp, Chlamydiales, Helicobacter pylori, and Legionella spp.

Mechanisms of Macrolide, Lincosamide, and Streptogramin Resistance and Their Genetic Determinants

There are three major mechanisms of MLS resistance: (a) target site modification by methylation or mutation that prevents the binding of the antimicrobial to its 50S ribosomal complex, (b) active efflux, and (c) enzyme-catalyzed drug inactivation. These mechanisms have been found in the bacteria producing these antimicrobials (5). The impact of the three mechanisms is unequal in terms of distribution and therapeutic implications in pathogenic bacteria. In large, modification of the ribosomal target complex confers broad-spectrum MLS resistance, whereas efflux and enzymatic inactivation affect only specific molecules. Resistance phenotypes affecting MLS antimicrobials and their genetic counterparts are presented in Table 9.5.

High-level resistance to macrolides is most often mediated by the enzyme-catalyzed methylation of the 23S rRNA by Erm (erythromycin ribosome methylase) methyltransferases encoded by erm genes that confer constitutive or inducible macrolide-lincosamide-streptogramin B (MLSB) resistance phenotypes (122). The number of described erm genes has already passed 40 (http://faculty.washington.edu/marilynr/). Four major erm classes are detected in pathogenic bacteria: erm(A), erm(B), erm(C), and erm(F) (118,122). Although erm(A) and erm(C) are typically detected in staphylococci, erm(B) class genes are mostly observed in streptococci and enterococci, whereas erm(F) are mostly described in Bacteroides and other anaerobes. In addition to the erm(B) genes, the ermTR genes (a subset of the erm[A] class) are widely distributed in β-hemolytic streptococci (118). The notion that each erm class may have a relatively specific distribution, but not strictly confined to a bacterial genus, reflects their association to mobile genetic elements and various mechanisms for horizontal gene transfer (118,123).

Low-level macrolide resistance is mainly associated with streptococci and linked to the production of an efflux pump (M phenotype) conferring resistance to erythromycin but not to clindamycin and/or streptogramins (122). A macrolide efflux system in streptococci was firmly established in 1996 (124). This system was phenotypically recognized and characterized to confer low-level resistance to 14- and 15-membered macrolides only. Several mefdeterminants have been described and the number varies dependent on criteria for definition of new elements (118,120).

A number of reports has shown marked differences between mef(A) and mef(E) (118). For instance, the different genetic elements carrying mef(A) or mef(E) and their contexts have been studied (125). Moreover, the two genes have disseminated markedly different in an ever growing number of species (120).

Molecular Detection Macrolide, Lincosamide, and Streptogramin Resistance Determinants

It is not much of a surprise to find that PCR is by far the most established method for the detection of MLS resistance genes and their genetic support. The high degree of similarity between major groups of resistance determinants does not allow a reliable discrimination to be made by using DNA hybridization experiments. Recommended primers for detection of MLS genes are available at http://faculty.washington.edu/marilynr/. Moreover, a diversity of different PCR primer combinations for amplification of the mef gene have been reported creating amplification products ranging from 202 to 1,759 bp (Table 3 in [120]). However, when using PCR to target resistance determinants with nucleotide diversity, one must take into account mismatches and in particular those located at the ultimate 3′-end of the primer sequence or multiple mismatches that may be present along the sequence of the primer(s). The use of such primers may result in an inefficient PCR or preferential amplification of mef gene subpopulations without the mismatch. A straightforward method for discrimination between mef(A) and mef(E) is based on the differential presence of restriction enzyme recognition sites in the two genes. Restriction enzyme digest resolved by agarose gel electrophoresis is sufficient to establish the difference (120).

The complexity of MLS-related resistance phenotypes are increasing. Several additional phenotypes affecting L or S antibiotics only (L phenotype) or in combination (LS phenotype) and their respective resistance determinants have been described lately (126–128). Importantly, lincosamide nucleotidyltransferases encoded by plasmid-mediated lnu genotypes and affecting the bactericidal activity of clindamycin have been described in staphylococci (117,122,127). Moreover, clinically relevant macrolide resistance in gram-negative bacilli has recently been described. Emerging plasmid-mediated mph(A) determinants encoding macrolide kinases was associated with azithromycin treatment failure in pediatric shigellosis (129).

In conclusion, the identification of MLS resistance mechanisms is important to guide the clinical use of MLS antimicrobials. The presence of various resistance determinants is highly dynamic and varies considerably between countries, species, and infections. Thus, it is important for empiric therapy guidelines that the phenotypic surveillance data on MLS susceptibility data are complemented with genotypic data showing the resistance determinants involved (122,130).

The Problem

Drug-resistant M. tuberculosis (tuberculosis [TB]) represents a global public health threat (131). Diagnostic delays lead to increased mortality, selection for secondary resistance, and further transmission. Consequently, it is important to deliver reliable drug susceptibility test (DST) results in a clinically useful time frame.

Conventional phenotypic drug susceptibility testing of M. tuberculosis takes weeks to complete, although more rapid, commercialized, broth-based methods have been developed (132). Moreover, culture-based DSTs are labor-intensive and time-consuming and handling of TB cultures represents a potential biologic hazard. Thus, WHO has endorsed the development of molecular approaches to provide a rapid, relevant DST result to time-appropriate treatment.

Initial TB treatment is empirical, based on clinical suspicion and positive direct smears. Isoniazid (INH), rifampin (RMP), pyrazinamide (PZA), and ethambutol (EMB) are considered to be used as standard first-line treatment. Other antimicrobials including fluoroquinolones (FQs) are considered second-line drugs prescribed in case of resistance or intolerance. Multidrug-resistant TB (MDR-TB) is defined as resistant to at least the two main first-line anti-TB drugs, RMP and INH. In contrast, extensively drug-resistant TB (XDR-TB) is an MDR isolate that, in addition, express resistance to an FQ and at least one of the following second-line injectable drugs: amikacin (AMK), kanamycin (KAN), and capreomycin (CAP). The evolution of drug resistance in M. tuberculosis, including mechanisms and genetic regions involved in resistance formation has recently been reviewed (133).

Drug Resistance Mechanisms in Mycobacterium tuberculosis and Their Molecular Detection

M. tuberculosis is intrinsically resistant to a number of antimicrobials. This is partially due to a thick, lipid-rich cell wall that prevents antimicrobials for reaching their target as well as drug-inactivating enzymes such as β-lactamases (133). Thus, only a limited number of antimicrobials are effective treatment options. Acquired clinically relevant drug resistance in M. tuberculosis is not due to horizontal gene transfer. M. tuberculosis has not been shown to harbor plasmids. Further, the clonal population structure of TB indicates a limited role of horizontal gene transfer in the evolution of the species.

Hence, the genetic basis for acquired clinically relevant drug resistance in M. tuberculosis is chromosomal mutations that occur spontaneously during error-prone polymerization of DNA (134). Favorable mutations are selected for during antimicrobial selection and passed further through vertical transmission. The mutations are localized in genes for the antimicrobial target and affects drug–target affinity (RMP, FQs, aminoglycosides [AGs], and EMB). Mutations may also involve genes encoding drug-activation enzymes affecting the transformation of inactive antimicrobials to an active metabolite (INH, PZA, and para-amino salicylic acid [PAS]). A diverse array of commercial and in-house genotypic DSTs has been developed based on direct or indirect detection of resistance-conferring mutations of which some of them are selectively presented in Table 9.6 (135). Sequence- or hybridization-based detection of mutations in amplified products has become the standard techniques. Their success and limitations are partially based on the current knowledge of the factual mutations that account for phenotypic resistance (14).

The mechanisms conferring resistance to the two main first-line drugs, RMP and INH, are the most relevant diagnostic targets in genotypic DSTs. RMP and/or INH resistance trigger therapeutic modifications, extended DST, and individual drug tailoring. Detection of MDR-TB requires the use of second-line drugs, and monoresistance leads to therapeutic adjustments in the consolidation phase to avoid unintended monotherapy and resistance development. RMP inhibits the early steps in transcription, binding the β-subunit encoded by rpoB (136). Phenotypic resistance is mostly confined to rpoB mutations in an 81-bp region named RMP resistance-determining region (RRDR). INH is a prodrug, activated by the catalase-peroxidase enzyme encoded by katG (137). Activated INH is believed to target a mycolic acid synthesis enzyme, enoyl-acyl carrier protein reductase InhA (138). Thus, phenotypic resistance to INH has been associated with mutations in katG affecting the activation of INH as well as inhA promoter mutations mediating InhA hyperexpression. Several in-house and commercial tests are available and proven effective in detection of both RMP and INH resistance including point-of-care diagnostics (139–141).

Although resistance mechanisms toward RMP, INH, and other anti-TB drugs are extensively investigated, they remain to be completely resolved. A recent comprehensive study of 290 clinical M. tuberculosisstrains from four continents comparing phenotypic DST with pyrosequencing targeting mutations associated with resistance to RMP, INH, EMB, FQ, AG, and CAP showed a very high specificity in detection of MDR- and XDR-TB strains (14). However, the sensitivity of genotypic detection of phenotypic resistance to individual drugs varied considerably from 95% for RMP and 94% for INH to 61% for EMB, reflecting our incomplete understanding of clinically relevant resistance mechanisms.

In conclusion, specific and sensitive rapid commercial molecular tests for detection of both M. tuberculosis and RMP resistance directly from sputum samples have been validated and made available (142). The choice of molecular methods must take into consideration the local or national prevalence of M. tuberculosis and MDR-TB as well as available resources, technology, and competencies. Implementation of these technologies for routine point-of-care diagnosis of M. tuberculosis and MDR-TB at the primary care level is quite promising (143). Although feasible, high-burden countries are often associated with limitations in resources, personnel, and technology, restricting the use of these techniques to reference laboratories. Thus, to make a real impact in TB control, large scale implementation needs sustainable financial and operational support to meet the urgent need of cost-effective, simplistic methods for rapid, sensitive, and specific detection of M. tuberculosis and clinically relevant drug resistance outside reference centers. This is very important, as empiric treatment of TB without timely DST in regions with a burden of drug-resistant TB will continue to amplify drug-resistant TB at a high cost (144).

The Growing Diversity of β-Lactamase

The first β-lactamase was identified as early as 1940 (145), before β-lactams were introduced into clinical use. Since then, the introduction of new β-lactam antibiotics in clinical practice and the corresponding emergence of new β-lactamases in human pathogens have evolved in parallel. Currently, the number of identified β-lactamases and variants has probably reached more than 1,000 (146) (http://www.lahey.org/Studies). In the last two decades, the dissemination and alarming prevalence of extended-spectrum β-lactamases (ESBLs) and carbapenemases have been the main concern. They are now threatening the use of β-lactams, which has been our largest and most valuable group of antimicrobials (147,148).

ESBLs are characterized by their hydrolytic activity against extended-spectrum cephalosporins (oxyimino-β-lactams) such as ceftazidime and cefotaxime, as well as being inhibited by the classical β-lactamase inhibitors (146). Carbapenems and cephamycins (e.g., cefoxitin) are generally not affected by ESBLs. The first ESBLs identified were variants of the TEM-1 and SHV-1 β-lactamases (149). The ESBL variants of TEM-1 and SHV-1 only differs from their progenitors by a few to a single amino acid change (149). The current number of TEM- and SHV-ESBL variants and the amino acid changes can be found on the β-lactamase Web site (http://www.lahey.org/Studies). In addition to TEM- and SHV-ESBL variants, the CTX-M ESBLs have emerged as the most prevalent ESBLs on a global scale (147,149–151). Currently, more than 130 CTX-M variants have been identified (http://www.lahey.org/Studies). Based on the amino acid sequence, the CTX-M ESBL can be grouped into five to seven subgroups/clusters: CTX-M-1/-3, CTX-M-2, CTX-M-8, CTX-M-9/-14, CTX-M-25, CTX-M-45, and CTX-M-64 (151–153). Other less prevalent ESBLs include GES, VEB, PER, BEL, BES, TLA, SFO, IBC, and OXA variants (149,154).

In contrast, carbapenemases are β-lactamases with the ability to hydrolyze carbapenems such as meropenem, imipenem, ertapenem, and doripenem (146). In addition, many of the carbapenemases have hydrolytic activity against all β-lactams. Consequently, the presence of one carbapenemase can give resistance to the whole β-lactam group of antimicrobials. Currently, the most significant problem is the global dissemination of mobile or acquired carbapenemases among various gram-negative bacteria (148,155).

Acquired carbapenemases have been identified in three Ambler classes of β-lactamases (A, B, and D). Acquired class A carbapenemases includes KPC, IMI, NMC-A, and SME where KPC is the most prevalent and 18 different variants (KPC-2 to KPC-19) have been identified so far (http://www.lahey.org/Studies) (148,155). The acquired class B carbapenemases includes the metallo-β-lactamases (MBLs) such as VIM, IMP, NDM, SPM, GIM, SIM, AIM, DIM, KHM, TMB, and SMB (148,155). The MBLs VIM, IMP, and NDM have shown a global dissemination and are the most prevalent MBLs (148,155). For these MBLs, several variants have also been identified to date with 41 VIM variants, 48 IMP variants, and 12 NDM variants identified to date (http://www.lahey.org/Studies). The acquired class D carbapenemases includes the OXA-carbapenemases, which can be grouped into two subgroups: (a) the OXA-carbapenemases, OXA-23–like, OXA-24/-40–like, OXA-58–like, and OXA-143, which are almost exclusively found among Acinetobacter spp and (b) the OXA-48–like carbapenemases found among Enterobacteriaceae (156,157). Although variable, all of these acquired carbapenemases have activity toward carbapenems. However, their activity toward other β-lactams varies. OXA-carbapenemases have limited or no activities toward extended-spectrum cephalosporins, and MBLs have no activities toward monobactams (aztreonam) (156,157).

Molecular Detection of β-Lactamases

Molecular methods for detection of ESBLs and carbapenemases are challenging for the clinical microbiology laboratory due to the large number of β-lactamase groups and diversity within groups. Further, the continuously changing epidemiologic landscape and emergence of new ESBLs or carbapenemases requires molecular methods to be adaptable to these changes. The presence of ESBLs and carbapenemases does not always result in clinical resistance according to the current breakpoints set by clinical breakpoints committees such as the European Committee for Antimicrobial Susceptibility Testing (EUCAST, http://www.eucast.org) or Clinical and Laboratory Standards Institute (CLSI, http://www.clsi.org). Further, it is advised that susceptibility results can be “reported as found” irrespective of the presence of an ESBL or carbapenemase. Consequently, molecular identification of ESBL or carbapenemase genes is not required for guidance of treatment. It should be noted that these guidelines are controversial and discussed (158).

Biochemical Methods for Detection of Extended-Spectrum β-Lactamases and Carbapenemases

The gold standard method for detection of β-lactamase activity is analysis of β-lactam hydrolysis by spectrophotometry. This method is mainly used in reference laboratories, as it requires specialized equipment and training in interpretation of the hydrolytic curves. Further, the method is relatively slow, as it requires overnight growth of liquid bacterial cultures and preparation of a protein extract (159,160). Recent evaluations of this method also indicate that detection of carbapenem hydrolysis by NDM and OXA-carbapenemases in A. baumannii is difficult (161).

Another, novel biochemical approach has been described for detection of ESBLs and carbapenemases where the hydrolysis of β-lactams is detected due to color changes of a pH indicator (phenol red) as the pH changes during hydrolysis (162–164). Inclusion of β-lactamase inhibitors to these assays also allows the discrimination between subclasses of carbapenemases (164). These novel assays can be implemented in clinical laboratories, as they are relatively easy to perform and bacterial colonies can be used, resulting in a total turnover time of less than 2 hours (162).

The availability of MALDI-TOF MS in microbiologic laboratories has led to the investigation into its possible application for detection of antimicrobial resistance (26). Several promising reports are now emerging where MALDI-TOF MS has been used for the identification of β-lactamase activity, particularly carbapenemase activity, by detecting degradation products of different β-lactams with good results (32,33,165,166). The use of MALDI-TOF MS for detection of carbapenemase activity has the potential to be implemented in a routine clinical microbiologic laboratory. However, as no specialized software or kits have been developed, expertise in manual interpretation of the spectra is required.

DNA-Based Molecular Methods for Detection of Extended-Spectrum β-Lactamases and Carbapenemases

Over the years, various molecular methods, including conventional PCRs, real-time PCRs, LAMP, and DNA microarrays, have been described for detection of ESBLs and carbapenemases. The majority of methods are developed by the scientific community and there are only a limited number of methods that are commercially available. The description of molecular assays in the following texts is an attempt to provide examples of methods that have been described and used and to provide a platform for selection of methods based on the possibilities in different laboratories.

An important aspect before selecting a molecular method for detection of ESBLs or carbapenemases is the purpose of the assay. The large number of genes/variants and the constant emergence of new ESBLs and carbapenemases make it difficult for clinical laboratories to be up-to-date. Specific assays are therefore limited to reference laboratories. In epidemiologic studies, it might be important to use assays that cover a broad range of genes while in outbreak settings, and for infection control purposes, more targeted specific molecular assays could be considered. From epidemiologic studies, it is known that the dissemination of ESBL and carbapenemase genes is often associated with specific bacterial clones such as Escherichia coli sequence type (ST) 131 and bla_CTX-M, K. pneumoniae ST258 and bla_KPC, and A. baumannii clones and bla_OXA-carbapenemases (151,167,168). Molecular assays for rapid detection of some specific clones and associated ESBL or carbapenemase are developed, such as the detection of ST131 and bla_CTX-M and ST258 and bla_KPC (169,170).

Conventional and Real-Time Polymerase Chain Reactions for Detection of Extended-Spectrum β-Lactamases and Carbapenemases

Conventional PCR and real-time PCR are the most commonly used molecular methods for detection of ESBLs and carbapenemases. Numerous PCRs, including conventional single and multiplex PCRs as well as real-time PCRs, have been described (Tables 9.7 and 9.8). For the detection of TEM and SHV ESBLs and variants of GES with carbapenemase activity, the identification of mutations are required to distinguish from the progenitor variants that are not ESBLs or lack carbapenemase activity. In conventional PCRs, sequencing of the bla_TEM or bla_SHV PCR products and analysis for mutations in the sequence are required either through standard Sanger sequencing (171) or pyrosequencing (172). Real-time PCR methods for discrimination of SHV variants and non-ESBL variants have also been described using melting-curve analysis (173).

A commercially available ligation-mediated real-time PCR from Check-Points designed for the detection of specific common mutations of SHV and TEM ESBL variants as well as CTX-M have been evaluated (174). Although PCR detection of CTX-M do not require discrimination from a non-ESBL variant, it is often desirable to determine which subgroup the CTX-M variant belongs to. Multiple PCR assays including conventional PCRs (175–177), conventional PCR followed by denaturing high-performance liquid chromatography (178), real-time PCR followed by pyrosequencing (179), and real-time PCR using probe-based detection or melting-curve analysis (173,180–182) have been developed. Real-time PCR assays for direct detection of bla_CTX-M in urine (181) and blood cultures (182,183) have also been reported. For the detection of the less prevalent ESBLs such as VEB (175,184,185), PER (175,184,186), GES (175,184,187), and BEL (188), conventional PCRs either as single or multiplex are mainly used for detection.

Various conventional PCRs and real-time PCRs have also been described for the detection of carbapenemase genes either as single or multiplex PCRs (Tables 9.7 and 9.8). There are also PCRs described which includes both detection of ESBLs and carbapenemases (175). Further, the developed PCRs vary with respect to the number of targets included. Conventional PCRs for detection of carbapenemases include a multiplex PCR for detection of the class D OXA-carbapenemases, bla_OXA-23-like, bla_{OXA-24/-40-like}, and bla_OXA-58-like, mainly identified in Acinetobacter spp (189). This PCR has been updated with the addition of primers for bla_OXA-143 (190). Further, different multiplex PCRs have been described for the detection of class A and class B carbapenemases (191–193).

With respect to real-time PCRs for carbapenemases, different detection methods such as melting-curve analysis (194–196) or fluorescent probes (170,197–203) have been developed (Table 9.8). For the detection of bla_NDM, an assay using LAMP has been described with the potential of being a rapid test with low cost (204). Detection of bla_NDM and bla_KPC using real-time PCRs has been examined for their ability to detect these genes directly from clinical specimens such as perianal or rectal swabs (198,201,205). This can be particularly useful in outbreak settings or for screening of large populations. One commercially available real-time PCR assay from bioMérieux for the detection bla_KPC has been evaluated by Spanu et al. (206).

Oligonucleotide Array–Based Technology for Detection of Extended-Spectrum β-Lactamases and Carbapenemases

DNA microarray or oligo-based technology has the potential for detection of a large number of resistance genes and discrimination of variants within each class or family in a single test. In-house microarray assays have been developed for the detection of various resistance genes that also includes β-lactamases (207,208). However, the number of specific ESBL and carbapenemase genes in these arrays is limited. For the specific detection of ESBLs and carbapenemases, different approaches to this technology has been developed (Table 9.9). Grimm et al. (209) developed a DNA microarray for the detection of TEM ESBLs using Cy-labelled PCR products followed by hybridization on glass slides containing oligonucleotide probes. A further development of this assay has been done to include detection of SHV ESBL and CTX-M genes (210). A specific microarray for the direct detection and genotyping of bla_KPC variants also using Cy labelling and glass slides has been reported (211). This assay has also been evaluated using spiked urine samples.

An alternative approach by incorporating biotin into the DNA in the PCR reaction followed by hybridization to oligonucleotides on nitrocellulose membranes and detection using horseradish peroxidase have also been described for the detection of TEM, SHV, and CTX-M ESBLs (212). Two commercially available systems from AmplexDiagnostics (Gars Bahnhof, Germany) and Check-Points (Wageningen, The Netherlands) using different approaches are described. The hyplex SuperBug ID (AmplexDiagnostics, Gars Bahnhof, Germany) includes a multiplex PCR for detection of KPC, VIM, NDM, and OXA-48 carbapenemases followed by detection of PCR products by reverse hybridization in microtiter plates precoated with specific oligonucleotide probes similar to a traditional antigen ELISA (213). The Check-Points (Wageningen, The Netherlands) technology includes a ligation-mediated PCR step where specific probes with primer sequences and zip codes will be ligated together if they match to the template DNA. This is followed by amplification PCR, hybridization, and detection in a microarray tube. Different Check-Points (Wageningen, The Netherlands) assays for detection of ESBLs and carbapenemases have been developed and evaluated (214–218).

Aminoglycosides—Mechanisms of Action and Resistance

Aminoglycosides (AGs) are an important group of antimicrobials often used in combination with β-lactams or glycopeptides for the treatment of invasive infections caused by both gram-negative and gram-positive bacteria. AGs include 4,6-disubstituted 2-deoxystreptamines (gentamicin, tobramycin, AMK, arbekacin, and KAN), 4,5-disubstituted deoxystreptamines (neomycin), monosubstituted deoxystreptamine (apramycin), and streptomycin, which has no deoxystreptamine ring (219). The primary target for AGs is the 16S RNA A-site located on the 30S subunit of the bacterial ribosome (220). Target site binding of AGs results in conformational changes of the A-site, which promotes mistranslation and concentration-dependent bactericidal effects.

Acquired antimicrobial resistance to AGs follows the major biochemical mechanisms of resistance: (a) enzymatic modification/inactivation, (b) mutations or modification of target, and (c) reduced accumulation in the cytoplasm through efflux or reduced permeability. The most prevalent mechanisms are associated with mobile genetic elements such as plasmids and/or transposons. The mechanisms mainly include aminoglycoside-modifying enzymes (AMEs) and 16S rRNA methylases (221,222). AMEs can be divided into three different classes based on the molecular mechanism of inactivation of AGs (221). Aminoglycoside N-acetyltransferases (AACs) uses acetyl coenzyme A to catalyze the acetylation of −NH₂ groups on AGs. Aminoglycoside O-nucleotidyltransferases (ANTs) modify AGs using adenosine triphosphate (ATP) to transfer adenosine monophosphate (AMP) to −OH groups, whereas aminoglycoside O-phosphotransferases (APHs) catalyze the transfer of a phosphate group to the AG molecule (221). The modification and substrate specificity of the different AMEs and within each AME class varies. To date, numerous AMEs have been identified and the nomenclature is complex. For recent reviews, see Ramirez and Tolmasky (221), Shaw et al. (223), and Tolmasky (224).

Aminoglycoside Resistance Genes and Their Detection

The large number of genes encoding AMEs makes molecular detection of AMEs a complex and difficult exercise. DNA microarrays or WGS followed by bioinformatics analysis is probably the only methods that can offer the possibility of complete coverage for detection of all known AMEs. Various DNA microarrays that include probes for AME genes have been developed and used to characterize both gram-negative and gram-positive bacteria (208,225–229). The number of AME genes included in the DNA microarrays varies.

Aminoglycoside-Modifying Enzyme Genes in Gram-Positive Bacteria

Streptococci are considered intrinsically resistant to AGs due to reduced permeability. For enterococci and staphylococci, the number of AME genes identified in clinical isolates is relatively limited and conserved (230). The most prevalent AME genes in clinical samples include aac(6′)-Ie-aph(2″)-Ia encoding a bifunctional enzyme [AAC(6′)-APH(20″)], ant(4′)-Ia encoding ANT(4′)-Ia, and aph(3′)-IIIaencoding APH(3′)-III. Consequently, conventional PCR assays either as single or multiplex can often be sufficient and usually provide a good correlation with the phenotypic profile. Several epidemiologic studies have described primers and conditions for detection of various AMEs in enterococci and staphylococci (Table 9.10).

Aminoglycoside-Modifying Enzyme in Gram-Negative Bacteria

The number of AME genes identified in gram-negative bacteria is more extensive compared to gram-positive bacteria making molecular detection more complex. However, specific AME genes are more prevalent than others (230). These include genes encoding AMEs belonging to the subclasses ANT(2″)-I, AAC(6′)-I, AAC(3)-I, AAC(3)-II, AAC(3)-III, AAC(3)-IV, and AAC(3)-VI. The epidemiology of AME genes varies by geographical location and selective pressure influencing the selection of AME genes to be targeted (230). Conventional PCR is the most used molecular method for detection of AME genes in gram-negative bacteria. Real-time PCRs have been designed for some specific AME genes. Particular attention has been given to aac(6′)-Ib and detection of the aac(6′)-Ib-cr variant that encodes a variant of aac(6′)-Ib that are able to modify the FQs, ciprofloxacin, and norfloxacin (231–233). Table 9.11 shows illustrative studies describing PCRs for detection of AME genes in gram-negative bacteria.

Making Aminoglycosides Useless—The Emergence of Transferable 16S rRNA Methylases

16S rRNA methylases have recently emerged as a major mobile AG resistance mechanism among gram-negative bacteria (222). The enzymes methylate specific nucleotide residues in the binding site of AGs in the 16S rRNA conferring high-level and broad-spectrum AG resistance. Two subclasses of 16S rRNA methylases have been described: N7-G1405 and N1-A1408. To date, seven N7-G1405 16S rRNA methylases (ArmA, RmtA, RmtB, RmtC, RmtD, RmtD2, and RmtE) and one N1-A1408 16S rRNA methylase (NpmA) have been identified among gram-negative bacteria. The hallmark of N7-G1405 16S rRNA methylases is high level of resistance (minimum inhibitory concentration [MIC] ≥128 mg/L) to 4,6-disubstituted 2-deoxytreptamines such as gentamicin, tobramycin, AMK, arbekacin, and KAN. The dissemination of genes encoding 16S rRNA methylases is often associated with the spread of ESBL and carbapenemases. Molecular detection methods of 16S rRNA methylases described so far includes conventional multiplex PCRs (234,235). Bercot et al. (235) describe two multiplex PCRs that covers all 16S rRNA methylases identified to date. The increasing diversity of 16S rRNA methylases may soon undermine the practical use of PCR in the detection of encoding genes and support the use of alternative molecular detection techniques such as MALDI-TOF MS (236). A recent review stated, however, that the template preparation needed to be simplified to be used for routine and reference purposes (45).

Linezolid Resistance Mechanisms

The overall high linezolid susceptibility rates (>99 %) for staphylococci, enterococci, and streptococci monitored in medical centers in Europe, Canada, Latin America, the United States, and the Asia-Pacific region remains stable (237–239). Linezolid inhibits bacterial protein synthesis by binding to the A-site pocket at the ribosomal peptidyltransferase center in domain V of the 23S rRNA (240). Resistance to linezolid is caused by target site modification. Point mutations in 23S rRNA domain V, in particular a G2576U mutation, and the presence of a transferable ribosomal methyltransferase encoded by the cfr gene are most often associated with linezolid resistance in clinical strains of staphylococci and enterococci (237–239,241,242). Mutations in ribosomal proteins L3 and L4 have also been shown to mediate linezolid resistance in staphylococci (237–239). In streptococci mutations in ribosomal protein, L4 have been the main mechanism identified in linezolid nonsusceptible clinical strains but 23S rRNA and L22 mutations (239,243–245) have also been reported.

The development of mutational-based linezolid resistance in staphylococci and enterococci was initially considered unlikely due to the presence of multiple copies of the 23S rRNA gene. The rate-limiting step in the development of linezolid resistance in enterococci appears to be the initial mutation occurring under antimicrobial selective pressure, as subsequent replacement of wild-type genes with mutant copies occurs rapidly by homologous recombination (246). The level of linezolid resistance expressed correlates with the number of mutated 23S rRNA genes (247). Mutations in a single copy of the 23S rRNA gene can contribute to increased linezolid MIC (248).

Linezolid Resistance Determinants

The transferable linezolid multiresistance gene, cfr (chloramphenicol–florfenicol resistance) gene, encodes a methyltransferase-catalyzing methylation of A2503 in the 23S rRNA V domain. Methylation of A2503 affects the binding of at least five antimicrobial classes (phenicols, lincosamides, oxazolidinones, pleuromutilins, and streptogramin A), leading to a multidrug-resistant phenotype (249).

The cfr gene has been reported as the underlying resistance mechanism in outbreaks of linezolid resistance S. aureus (250–252) and S. epidermidis (253) and has been detected on transferable plasmids in clinical isolates of S. aureus (254), CoNS (255,256), and recently also in E. faecalis (241). Acquisition of cfr in S. aureus was associated with a generally low fitness cost (257). The cfr encoding plasmids have, since their first discovery in year 2000 (258), been found in domestic animal isolates of staphylococci (259), enterococci (260,261), Bacillus (262–264), Macrococcus caseolyticus, Jeotgalicoccus pinnipedialis (265), and E. coli (266). The cfr gene has also been found on the chromosome of a Proteus vulgaris isolated from a pig (267). The cfr gene is expressed in both gram-positive and gram-negative bacteria (249) and is often located on plasmids that carry additional resistance genes (254,261–265) to important antimicrobial agents used in both human and veterinary medicine; thus, selection pressure and risk of further spread of cfr plasmids are likely.

Molecular Methods in Detection of Linezolid Resistance

The cfr gene can be amplified using PCR primers (cfr-fw TGA AGT ATA AAG CAG GTT GGG AGT CAC and cfr-rv ACC ATA TAA TTG ACC ACA AGC AGC) (259), giving a 100% match to the cfrgenes detected as of early 2013 in both staphylococci and enterococci. Confirmation of PCR products of the correct size can be achieved either by restriction digestion or direct sequencing. Alternatively, the cfr gene may be detected by Southern blot (259) or LAMP (268).

Several approaches have been described to detect the most common 23S rRNA single nucleotide mutation (G2576T) conferring linezolid resistance in enterococci and staphylococci. Traditional SNP analysis used to detect the G2576T comprises PCR amplification of the domain V region of the 23S rRNA gene using primers for enterococci (247,269), staphylococci (270), or both (256) and restriction digestion by enzymes such as MaeI (247) or NheI (G↓CTAGC) (256,269,270). Mutated nucleotide generating new restriction sites is underlined. Quick and easy to perform separation and analyses of the resulting restriction fragments has been tested with LabChip kit, Bioanalyzer, and BioSizing software (Agilent Technologies, Santa Clara, CA), which calculates both size and quantities of fragments (271). Other SNP detection approaches tested in enterococci include fluorescence in situ hybridization (FISH) assay with probes containing locked nucleic acids (LNAs) at the site of point mutation (272) as well as real-time PCRs with hybridization probes discriminating between mutant and wild-type alleles using either Taqman probes (271) or a LightCycler (Roche Diagnostics GmbH, Mannheim, Germany) assay including a fluorescent dye–labelled detection probe (273).

Pyrosequencing is a rapid technology ideal for processing a larger number of isolates that is useful for sequence determination of short DNA regions as well as for providing quantification of the number of mutant versus wild-type alleles. For a thorough description of the pyrosequencing method and suitable primers to detect the main SNPs responsible for linezolid resistance in enterococci (G2576T) and staphylococci (G2576T, T2500A, A2503G, T2504C, G2505A, G2445T, G2447T), see Woodford et al. (274). A modified assay spanning a larger area of the 23S rRNA gene has been used to cover both the G2576T and the C2534T mutations of linezolid-resistant S. epidermidis (275).

To reveal both known and novel mutations involved in linezolid resistance, PCR amplification and subsequent sequencing of individual 23S rRNA alleles has been described for S. aureus (248,276,277), E. faecalis (278), and Streptococcus pneumoniae (279,280). Others perform amplification and direct sequencing on 23S rRNA PCR products containing a mixture of alleles using primers suitable for enterococci and streptococci (281), staphylococci (270), streptococci (280), enterococci and staphylococci (256,282), or all three (283). Furthermore, amplification and sequencing of the genes rplC and rplD encoding ribosomal proteins L3 (284, 285) and L4 (270,284,285) in staphylococci and rplD encoding L4 in S. pneumoniae (280) to reveal mutations involved in linezolid resistance has been reported.

The main mechanisms of resistance to quinolones and FQs have been the accumulation of mutations in the target enzymes DNA gyrase and DNA topoisomerase IV (286). These mutations occur in specific regions termed quinolone resistance-determining regions (QRDR) resulting in mutations in the target enzymes and reduced affinity for FQs. Methods for detection of chromosomal mutations in QRDR is generally determined by PCR followed by sequencing and will not be covered in this section. The dissemination of FQ resistance caused by chromosomal mutations would therefore be associated with clonal spread. Considering the rate of mutations, chromosomal mutations have not been sufficient to explain the relatively rapid frequency and nonclonality of resistance to FQs.

Plasmid-Mediated Quinolone Resistance Mechanisms

In 1998, the first plasmid-mediated quinolone resistance (PMQR) mechanism was reported in a K. pneumoniae isolate (287). The responsible PMQR gene was termed qnr for “quinolone resistance” and later renamed qnrA1. Subsequently, several qnr genes and variants have been discovered including qnrA, qnrB, qnrS, qnrC, and qnrD; for reviews, see Rodríguez-Martínez et al. (288) and Strahilevitz et al. (289). A classification scheme and database repository (http://www.lahey.org/qnrStudies/) for qnr genes have been set up to control the nomenclature (290). In addition to the qnr genes, two additional PMQR mechanisms have been identified. Robicsek et al. (291) showed that two amino acid mutations in the AME aac(6′)-Ib resulted in a variant, aac(6′)-Ib-cr, able to acetylate ciprofloxacin and norfloxacin. Further, two plasmid-mediated quinolone efflux pumps, QepA and OqxAB, have been identified (292,293).

Molecular Detection of Plasmid-Mediated Quinolone Resistance

The most common molecular method for detection of PMQR used has been PCR assays (Table 9.12). For detection of qnr genes, conventional multiplex PCRs have been described for the detection of different sets of qnr genes (294–296). Recently, a real-time multiplex using high-resolution melting (HRM) and ResoLight dye have been described for the detection of five qnr genes: qnrA, qnrB, qnrS, qnrC, and qnrD (297). Due to the large number and variety of qnrB variants, primer design has been a challenge and primer sequences should be evaluated against currently known qnrB sequences in the database (http://www.lahey.org/qnrStudies/). False-positive qnr PCR products have also been observed by multiplex PCR but not by monoplex PCRs (296). Sequencing of the PCR products should therefore be considered for confirmation. Assays for detection of the more recently discovered qnrC and qnrDhas mainly been performed with singleplex conventional PCRs (298,299) except for the inclusions of these genes in some multiplex PCRs as described earlier.

With respect to the two PMQR efflux mechanisms, QepA and OqxAB, methods for the detection of qepA have mainly been described. In addition to conventional PCR assays (293,300–302), Guillard et al. (297) have described a real-time PCR using SYBR Green I for the detection of qepA.

Detection of the aac(6′)-Ib-cr variant of aac(6′)-Ib requires the identification of mutations resulting in amino acid changes at codon 102 (Trp → Arg) and 179 (Asp → Tyr) (291). Various molecular methods have been applied for detection of aac(6′)-Ib-cr. Because aac(6′)-Ib-cr in contrast to aac(6′)-Ib lacks the cut site for the restriction enzymes BstF5I and BstCI, restriction enzyme digestion of purified PCR products have been applied to identify the aac(6′)-Ib-cr variant (303). Alternatively, Sanger sequencing or pyrosequencing of the aac(6′)-Ib PCR product have also been applied (303,304). Two real-time PCR assays using HRM analysis have also been developed to detect the SNPs (231,232). To solve the issue of subtle changes observed with a T → A mutation responsible for the Trp → Arg conversion, Bell et al. (232) included an unlabelled probe with perfect match to the aac(6′)-Ib allele and asymmetric concentrations of primer concentrations. For specific detection of the G535T mutation, a gap ligase chain reaction method has also been used (305).

The exponential increase of acquired genes and SNPs involved in antimicrobial resistance makes it increasingly difficult to test for all possible mechanisms using molecular methods. It is also important to underline that guidance in antimicrobial therapy and individual treatment is based on susceptibility. Thus, phenotypic antimicrobial susceptibility methods will continue to be crucial in routine diagnostics. However, rapid and accurate genotypic detection of particular important resistance mechanisms (i.e., MRSA and carbapenemases) is important for efficient infection control measures. The need for rapid molecular detection of MDR- and XDR-TB is evident in primary health care settings in countries with a high burden of disease (144). Molecular methods are also fundamental in reference academic laboratories for detection of novel mechanisms, confirmation of unusual phenotypes, and emerging mechanisms of potential health importance.

WGS is on the verge of becoming a reality for molecular diagnostics in routine clinical microbiology, as the technological revolution of sequencing has reduced the time, effort, and cost. The potential use of WGS in antimicrobial resistance surveillance programs and infection control is evident (18,21,22). Their promising possibilities in routine diagnostic microbiology have also recently been evaluated (20,306). However, the bioinformatics workflow including more user-friendly programs for data analyses and quality-assured databases for reference sequences is important tools that need to be solved in order for this methodology to become accessible in routine diagnostics (19,42,48).

The increasingly demanding technologies used for molecular diagnostic require skilled, highly trained personnel than currently may be found in the routine laboratories. Other obstacles may be costs of technology and lack of stable electricity. Thus, the advanced technologies may not be available in locations where the resistance problems are of most concern as illustrated by the increase in MDR- and XDR-TB in low- and middle-income countries worldwide associated with a high burden of HIV.

We apologize to all the authors whose work is not referred to in this review. The enormous amount of relevant publications made it impossible to include all.

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