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 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 (24). 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 (1722).


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.


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 (2629).

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 (3741). 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 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 ( (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 ( 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 (nucfemA) in multiplex formats to differentiate between MRSA and other methicillin-resistant staphylococci (5658). 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 vanAvanBvanDvanEvanGvanL (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 (vanAvanBvanD and vanM) or D-serine (vanCvanEvanGvanL, and vanN) for which vancomycin has lower affinity than the normal D-alanine side chain terminus (7376). Their characteristics and species distribution are summarized in Table 9.3. Both vanAvanBvanGvanM, 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 (7985). In contrast to vanA, the vanB ligase gene has been divided into three subtypes, vanB1–3, based on phylogenetic diversity (8688). The most prevalent vanB2 subtype (89100) has been identified in adapted bacterial genera of the normal intestinal flora such as AtopobiumClostridiumRuminococcusEggerthella, and Streptococcus (101104). 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 (105107). 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 (107111), whereas vanAdetection is more specific (111113).

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 vanBvanD, 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 ddlE. faecium recG) or genus-specific (tuf) genes for identification of enterococci or staphylococci (S. aureus nucStaphylococcus 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 vanAvanBvanCvanDvanE, and vanG including the subtypes of vanBvanD, 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 (116119). A recently updated database on MLS resistance genes is available at 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 pertussisCampylobacter 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 ( 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 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 (126128). 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 (139141).

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) ( 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 ( In addition to TEM- and SHV-ESBL variants, the CTX-M ESBLs have emerged as the most prevalent ESBLs on a global scale (147,149151). Currently, more than 130 CTX-M variants have been identified ( 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 (151153). 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 ( (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 ( 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, or Clinical and Laboratory Standards Institute (CLSI, 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 (162164). 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 blaCTX-MK. pneumoniae ST258 and blaKPC, and A. baumannii clones and blaOXA-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 blaCTX-M and ST258 and blaKPC (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 blaTEM or blaSHV 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 (175177), 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 (173,180182) have been developed. Real-time PCR assays for direct detection of blaCTX-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, blaOXA-23-likeblaOXA-24/-40-like, and blaOXA-58-like, mainly identified in Acinetobacter spp (189). This PCR has been updated with the addition of primers for blaOXA-143 (190). Further, different multiplex PCRs have been described for the detection of class A and class B carbapenemases (191193).

With respect to real-time PCRs for carbapenemases, different detection methods such as melting-curve analysis (194196) or fluorescent probes (170,197203) have been developed (Table 9.8). For the detection of blaNDM, an assay using LAMP has been described with the potential of being a rapid test with low cost (204). Detection of blaNDM and blaKPC 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 blaKPC 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 blaKPC 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 (214218).


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 (208,225229). 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 (231233). 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 (237239). 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 (237239,241,242). Mutations in ribosomal proteins L3 and L4 have also been shown to mediate linezolid resistance in staphylococci (237239). In streptococci mutations in ribosomal protein, L4 have been the main mechanism identified in linezolid nonsusceptible clinical strains but 23S rRNA and L22 mutations (239,243245) 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 (250252) 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 (262264), Macrococcus caseolyticusJeotgalicoccus 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 (254,261265) 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 (284285) 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 qnrAqnrBqnrSqnrC, and qnrD; for reviews, see Rodríguez-Martínez et al. (288) and Strahilevitz et al. (289). A classification scheme and database repository ( 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 (294296). Recently, a real-time multiplex using high-resolution melting (HRM) and ResoLight dye have been described for the detection of five qnr genes: qnrAqnrBqnrSqnrC, 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 ( 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 (293,300302), 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.


  1.  Kumar A, Roberts D, Wood KE, et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit Care Med 2006;34:1589–1596.

  2.  Diekema DJ, Dodgson KJ, Sigurdardottir B, et al. Rapid detection of antimicrobial-resistant organism carriage: an unmet clinical need. J Clin Microbiol 2004;42:2879–2883.

  3.  Derde LP, Dautzenberg MJ, Bonten MJ. Chlorhexidine body washing to control antimicrobial-resistant bacteria in intensive care units: a systematic review. Intensive Care Med 2012;38:931–939.

  4.  Savard P, Perl TM. A call for action: managing the emergence of multidrug-resistant Enterobacteriaceae in the acute care settings. Curr Opin Infect Dis 2012;25:371–377.

  5.  Morar M, Wright GD. The genomic enzymology of antibiotic resistance. Annu Rev Genet 2010;44:25–51.

  6.  Livermore DM, Winstanley TG, Shannon KP. Interpretative reading: recognizing the unusual and inferring resistance mechanisms from resistance phenotypes. J Antimicrob Chemother 2001;48(Suppl 1):87–102.

  7.  Courvalin P, Trieu-Cuot P. Minimizing potential resistance: the molecular view. Clin Infect Dis 2001;33(Suppl 3):S138–S146.

  8.  Fernandez L, Hancock RE. Adaptive and mutational resistance: role of porins and efflux pumps in drug resistance. Clin Microbiol Rev 2012;25:661–681.

  9.  Canton R, Morosini MI. Emergence and spread of antibiotic resistance following exposure to antibiotics. FEMS Microbiol Rev 2011;35:977–991.

 10.  Andersson DI, Hughes D. Persistence of antibiotic resistance in bacterial populations. FEMS Microbiol Rev 2011;35:901–911.

 11.  Depardieu F, Podglajen I, Leclercq R, et al. Modes and modulations of antibiotic resistance gene expression. Clin Microbiol Rev 2007;20:79–114.

 12.  Winstanley T, Courvalin P. Expert systems in clinical microbiology. Clin Microbiol Rev 2011;24:515–556.

 13.  Courvalin P. Interpretative reading of antimicrobial susceptibility tests. ASM news 1992;58:368–375.

 14.  Engström A, Morcillo N, Imperiale B, et al. Detection of first- and second-line drug resistance in Mycobacterium tuberculosis clinical isolates by pyrosequencing. J Clin Microbiol 2012;50:2026–2033.

 15.  Courvalin P. Genotypic approach to the study of bacterial resistance to antibiotics. Antimicrob Agents Chemother 1991;35:1019–1023.

 16.  Sundsfjord A, Simonsen GS, Haldorsen BC, et al. Genetic methods for detection of antimicrobial resistance. APMIS 2004;112:815–837.

 17.  Bennedsen M, Stuer-Lauridsen B, Danielsen M, et al. Screening for antimicrobial resistance genes and virulence factors via genome sequencing. Appl Environ Microbiol 2011;77:2785–2787.

 18.  Didelot X, Bowden R, Wilson DJ, et al. Transforming clinical microbiology with bacterial genome sequencing. Nat Rev Genet 2012;13:601–612.

 19.  Fricke WF, Rasko DA. Bacterial genome sequencing in the clinic: bioinformatic challenges and solutions. Nat Rev Genet 2014;15:49–55.

 20.  Hasman H, Saputra D, Sicheritz-Ponten T, et al. Rapid whole-genome sequencing for detection and characterization of microorganisms directly from clinical samples. J Clin Microbiol 2014;52:139–146.

 21.  Köser CU, Ellington MJ, Cartwright EJ, et al. Routine use of microbial whole genome sequencing in diagnostic and public health microbiology. PLoS Pathog 2012;8:e1002824.

 22.  Reuter S, Ellington MJ, Cartwright EJ, et al. Rapid bacterial whole-genome sequencing to enhance diagnostic and public health microbiology. JAMA Intern Med 2013;173:1397–1404.

 23.  Schena M, Shalon D, Davis RW, et al. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 1995;270:467–470.

 24.  Dufva M. Introduction to microarray technology. Methods Mol Biol 2009;529:1–22.

 25.  Bodrossy L, Sessitsch A. Oligonucleotide microarrays in microbial diagnostics. Curr Opin Microbiol 2004;7:245–254.

 26.  Hrabak J, Chudackova E, Walkova R. Matrix-assisted laser desorption ionization-time of flight (maldi-tof) mass spectrometry for detection of antibiotic resistance mechanisms: from research to routine diagnosis. Clin Microbiol Rev 2013;26:103–114.

 27.  Wieser A, Schneider L, Jung J, et al. MALDI-TOF MS in microbiological diagnostics-identification of microorganisms and beyond (mini review). Appl Microbiol Biotechnol 2012;93:965–974.

 28.  Douthwaite S, Kirpekar F. Identifying modifications in RNA by MALDI mass spectrometry. Methods Enzymol 2007;425:1–20.

 29.  Blondal T, Waage BG, Smarason SV, et al. A novel MALDI-TOF based methodology for genotyping single nucleotide polymorphisms. Nucleic Acids Res 2003;31:e155.

 30.  Griffin PM, Price GR, Schooneveldt JM, et al. Use of matrix-assisted laser desorption ionization-time of flight mass spectrometry to identify vancomycin-resistant enterococci and investigate the epidemiology of an outbreak. J Clin Microbiol 2012;50:2918–2931.

 31.  Edwards-Jones V, Claydon MA, Evason DJ, et al. Rapid discrimination between methicillin-sensitive and methicillin-resistant Staphylococcus aureus by intact cell mass spectrometry. J Med Microbiol 2000;49:295–300.

 32.  Hrabak J, Studentova V, Walkova R, et al. Detection of NDM-1, VIM-1, KPC, OXA-48, and OXA-162 carbapenemases by matrix-assisted laser desorption ionization-time of flight mass spectrometry. J Clin Microbiol 2012;50:2441–2443.

 33.  Sparbier K, Schubert S, Weller U, et al. Matrix-assisted laser desorption ionization-time of flight mass spectrometry-based functional assay for rapid detection of resistance against beta-lactam antibiotics. J Clin Microbiol 2012;50:927–937.

 34.  Kehrenberg C, Schwarz S, Jacobsen L, et al. A new mechanism for chloramphenicol, florfenicol and clindamycin resistance: methylation of 23S ribosomal RNA at A2503. Mol Microbiol 2005;57:1064–1073.

 35.  Ikryannikova LN, Shitikov EA, Zhivankova DG, et al. A MALDI TOF MS-based minisequencing method for rapid detection of TEM-type extended-spectrum beta-lactamases in clinical strains of EnterobacteriaceaeJ Microbiol Methods 2008;75:385–391.

 36.  Ikryannikova LN, Afanas’ev MV, Akopian TA, et al. Mass-spectrometry based minisequencing method for the rapid detection of drug resistance in Mycobacterium tuberculosisJ Microbiol Methods 2007;70:395–405.

 37.  Xu C, Lin X, Ren H, et al. Analysis of outer membrane proteome of Escherichia coli related to resistance to ampicillin and tetracycline. Proteomics 2006;6:462–473.

 38.  Siroy A, Cosette P, Seyer D, et al. Global comparison of the membrane subproteomes between a multidrug-resistant Acinetobacter baumannii strain and a reference strain. J Proteome Res 2006;5:3385–3398.

 39.  Vashist J, Tiwari V, Kapil A, et al. Quantitative profiling and identification of outer membrane proteins of beta-lactam resistant strain of Acinetobacter baumanniiJ Proteome Res 2010;9:1121–1128.

 40.  Grobner S, Linke D, Schutz W, et al. Emergence of carbapenem-non-susceptible extended-spectrum beta-lactamase-producing Klebsiella pneumoniae isolates at the university hospital of Tubingen, Germany. J Med Microbiol 2009;58:912–922.

 41.  Imperi F, Ciccosanti F, Perdomo AB, et al. Analysis of the periplasmic proteome of Pseudomonas aeruginosa, a metabolically versatile opportunistic pathogen. Proteomics 2009;9:1901–1915.

 42.  McGinn S, Gut IG. DNA sequencing—spanning the generations. N Biotechnol 2013;30:366–372.

 43.  Shendure JA, Porreca GJ, Church GM, et al. Overview of DNA sequencing strategies. Curr Protoc Mol Biol 2011;Chapter 7:Unit 7.1.

 44.  Köser CU, Holden MT, Ellington MJ, et al. Rapid whole-genome sequencing for investigation of a neonatal MRSA outbreak. N Engl J Med 2012;366:2267–2275.

 45.  Snitkin ES, Zelazny AM, Thomas PJ, et al. Tracking a hospital outbreak of carbapenem-resistant Klebsiella pneumoniae with whole-genome sequencing. Sci Transl Med 2012;4:148ra116.

 46.  Rolain JM, Diene SM, Kempf M, et al. Real-time sequencing to decipher the molecular mechanism of resistance of a clinical pan-drug-resistant Acinetobacter baumannii isolate from Marseille, France. Antimicrob Agents Chemother 2013;57:592–596.

 47.  Zankari E, Hasman H, Cosentino S, et al. Identification of acquired antimicrobial resistance genes. J Antimicrob Chemother 2012;67:2640–2644.

 48.  Underwood A, Green J. Call for a quality standard for sequence-based assays in clinical microbiology: necessity for quality assessment of sequences used in microbial identification and typing. J Clin Microbiol 2011;49:23–26.

 49.  te Witt R, van Belkum A, MacKay WG, et al. External quality assessment of the molecular diagnostics and genotyping of meticillin-resistant Staphylococcus aureusEur J Clin Microbiol Infect Dis 2010;29:295–300.

 50.  Mattarucchi E, Marsoni M, Binelli G, et al. Different real time PCR approaches for the fine quantification of SNP’s alleles in DNA pools: assays development, characterization and pre-validation. J Biochem Mol Biol 2005;38:555–562.

 51.  Chambers HF. Methicillin resistance in staphylococci: molecular and biochemical basis and clinical implications. Clin Microbiol Rev 1997;10:781–791.

 52.  Tomasz A, Nachman S, Leaf H. Stable classes of phenotypic expression in methicillin-resistant clinical isolates of staphylococci. Antimicrob Agents Chemother 1991;35:124–129.

 53.  File TM Jr, Wilcox MH, Stein GE. Summary of ceftaroline fosamil clinical trial studies and clinical safety. Clin Infect Dis 2012;55(Suppl 3):S173–S180.

 54.  Cosgrove SE, Sakoulas G, Perencevich EN, et al. Comparison of mortality associated with methicillin-resistant and methicillin-susceptible Staphylococcus aureus bacteremia: a meta-analysis. Clin Infect Dis 2003;36:53–59.

 55.  International Working Group on the Classification of Staphylococcal Cassette Chromosome Elements. Classification of staphylococcal cassette chromosome mec (SCCmec): guidelines for reporting novel SCCmec elements. Antimicrob Agents Chemother 2009;53:4961–4967.

 56.  Brakstad OG, Maeland JA, Tveten Y. Multiplex polymerase chain reaction for detection of genes for Staphylococcus aureus thermonuclease and methicillin resistance and correlation with oxacillin resistance. APMIS 1993;101:681–688.

 57.  Vannuffel P, Gigi J, Ezzedine H, et al. Specific detection of methicillin-resistant Staphylococcus species by multiplex PCR. J Clin Microbiol 1995;33:2864–2867.

 58.  Paule SM, Pasquariello AC, Thomson RB Jr, et al. Real-time PCR can rapidly detect methicillin-susceptible and methicillin-resistant Staphylococcus aureus directly from positive blood culture bottles. Am J Clin Pathol 2005;124:404–407.

 59.  Huletsky A, Giroux R, Rossbach V, et al. New real-time PCR assay for rapid detection of methicillin-resistant Staphylococcus aureus directly from specimens containing a mixture of staphylococci. J Clin Microbiol 2004;42:1875–1884.

 60.  Garcia-Alvarez L, Holden MT, Lindsay H, et al. Methicillin-resistant Staphylococcus aureus with a novel mecA homologue in human and bovine populations in the UK and Denmark: a descriptive study. Lancet Infect Dis 2011;11:595–603.

 61.  Ito T, Hiramatsu K, Tomasz A, et al. Guidelines for reporting novel mecA gene homologues. Antimicrob Agents Chemother 2012;56:4997–4999.

 62.  Stegger M, Andersen PS, Kearns A, et al. Rapid detection, differentiation and typing of methicillin-resistant Staphylococcus aureus harbouring either mecA or the new mecA homologue mecA(LGA251). Clin Microbiol Infect 2012;18:395–400.

 63.  Pichon B, Hill R, Laurent F, et al. Development of a real-time quadruplex PCR assay for simultaneous detection of nuc, Panton-Valentine leucocidin (PVL), mecA and homologue mecALGA251J Antimicrob Chemother 2012;67:2338–2341.

 64.  Monecke S, Muller E, Schwarz S, et al. Rapid microarray-based identification of different mecA alleles in Staphylococci. Antimicrob Agents Chemother 2012;56:5547–5554.

 65.  Shah HN, Rajakaruna L, Ball G, et al. Tracing the transition of methicillin resistance in sub-populations of Staphylococcus aureus, using SELDI-TOF Mass Spectrometry and Artificial Neural Network Analysis. Syst Appl Microbiol 2011;34:81–86.

 66.  Malhotra-Kumar S, Haccuria K, Michiels M, et al. Current trends in rapid diagnostics for methicillin-resistant Staphylococcus aureus and glycopeptide-resistant enterococcus species. J Clin Microbiol 2008;46:1577–1587.

 67.  Hidron AI, Edwards JR, Patel J, et al. NHSN annual update: antimicrobial-resistant pathogens associated with healthcare-associated infections: annual summary of data reported to the National Healthcare Safety Network at the Centers for Disease Control and Prevention, 2006–2007. Infect Control Hosp Epidemiol 2008;29:996–1011.

 68.  Reinert RR, Low DE, Rossi F, et al. Antimicrobial susceptibility among organisms from the Asia/Pacific Rim, Europe and Latin and North America collected as part of TEST and the in vitro activity of tigecycline. J Antimicrob Chemother 2007;60:1018–1029.

 69.  Hegstad K, Mikalsen T, Coque TM, et al. Mobile genetic elements and their contribution to the emergence of antimicrobial resistant Enterococcus faecalis and E. faeciumClin Microbiol Infect 2010;16:541–554.

 70.  Cattoir V, Leclercq R. Twenty-five years of shared life with vancomycin-resistant enterococci: is it time to divorce? J Antimicrob Chemother 2013;68:731–742.

 71.  Xu X, Lin D, Yan G, et al. vanM, a new glycopeptide resistance gene cluster found in Enterococcus faeciumAntimicrob Agents Chemother 2010;54:4643–4647.

 72.  Lebreton F, Depardieu F, Bourdon N, et al. D-Ala-d-Ser VanN-type transferable vancomycin resistance in Enterococcus faeciumAntimicrob Agents Chemother 2011;55:4606–4612.

 73.  Arthur M, Molinas C, Bugg TD, et al. Evidence for in vivo incorporation of D-lactate into peptidoglycan precursors of vancomycin-resistant enterococci. Antimicrob Agents Chemother 1992;36:867–869.

 74.  Billot Klein D, Gutmann L, Sable S, et al. Modification of peptidoglycan precursors is a common feature of the low-level vancomycin-resistant VANB-type Enterococcus D366 and of the naturally glycopeptide-resistant species Lactobacillus caseiPediococcus pentosaceusLeuconostoc mesenteroides, and Enterococcus gallinarumJ Bacteriol 1994;176:2398–2405.

 75.  Evers S, Courvalin P. Regulation of VanB-type vancomycin resistance gene expression by the VanS(B)-VanR (B) two-component regulatory system in Enterococcus faecalis V583. J Bacteriol 1996;178:1302–1309.

 76.  Handwerger S, Pucci MJ, Volk KJ, et al. The cytoplasmic peptidoglycan precursor of vancomycin-resistant Enterococcus faecalis terminates in lactate. J Bacteriol 1992;174:5982–5984.

 77.  Perichon B, Courvalin P. VanA-type vancomycin-resistant Staphylococcus aureusAntimicrob Agents Chemother 2009;53:4580–4587.

 78.  Ray AJ, Pultz NJ, Bhalla A, et al. Coexistence of vancomycin-resistant enterococci and Staphylococcus aureus in the intestinal tracts of hospitalized patients. Clin Infect Dis 2003;37:875–881.

 79.  Werner G, Coque TM, Hammerum AM, et al. Emergence and spread of vancomycin resistance among enterococci in Europe. Euro Surveill 2008;13:1–11.

 80.  Granlund M, Carlsson C, Edebro H, et al. Nosocomial outbreak of vanB2 vancomycin-resistant Enterococcus faecium in Sweden. J Hosp Infect 2006;62:254–256.

 81.  Werner G, Klare I, Fleige C, et al. Vancomycin-resistant vanB-type Enterococcus faecium isolates expressing varying levels of vancomycin resistance and being highly prevalent among neonatal patients in a single ICU. Antimicrob Resist Infect Control 2012;1:21.

 82.  Bourdon N, Fines-Guyon M, Thiolet JM, et al. Changing trends in vancomycin-resistant enterococci in French hospitals, 2001–08. J Antimicrob Chemother 2011;66:713–721.

 83.  Söderblom T, Aspevall O, Erntell M, et al. Alarming spread of vancomycin resistant enterococci in Sweden since 2007. Euro Surveill 2010;15:19620.

 84.  Bjørkeng EK, Rasmussen G, Sundsfjord A, et al. Clustering of polyclonal VanB-type vancomycin-resistant Enterococcus faecium in a low-endemic area was associated with CC17-genogroup strains harbouring transferable vanB2-Tn5382 and pRUM-like repA containing plasmids with axe-txe plasmid addiction systems. APMIS 2011;119:247–258.

 85.  Johnson PD, Ballard SA, Grabsch EA, et al. A sustained hospital outbreak of vancomycin-resistant Enterococcus faecium bacteremia due to emergence of vanB E. faecium sequence type 203. J Infect Dis 2010;202:1278–1286.

 86.  Dahl KH, Simonsen GS, Olsvik Ø, et al. Heterogeneity in the vanB gene cluster of genomically diverse clinical strains of vancomycin-resistant enterococci. Antimicrob Agents Chemother 1999;43:1105–1510.

 87.  Gold HS, Unal S, Cercenado E, et al. A gene conferring resistance to vancomycin but not teicoplanin in isolates of Enterococcus faecalis and Enterococcus faecium demonstrates homology with vanBvanA, and vanC genes of enterococci. Antimicrob Agents Chemother1993;37:1604–1609.

 88.  Patel R, Uhl JR, Kohner P, et al. DNA sequence variation within vanAvanBvanC-1, and vanC-2/3 genes of clinical Enterococcus isolates. Antimicrob Agents Chemother 1998;42:202–205.

 89.  Dahl KH, Lundblad EW, Røkenes TP, et al. Genetic linkage of the vanB2 gene cluster to Tn5382 in vancomycin-resistant enterococci and characterization of two novel insertion sequences. Microbiology 2000;146:1469–1479.

 90.  McGregor KF, Nolan C, Young HK, et al. Prevalence of the vanB2 gene cluster in vanB glycopeptide-resistant enterococci in the United Kingdom and the Republic of Ireland and its association with a Tn5382-like element. Antimicrob Agents Chemother 2001;45:367–368.

 91.  Dahl KH, Røkenes TP, Lundblad EW, et al. Nonconjugative transposition of the vanB-containing Tn5382-like element in Enterococcus faeciumAntimicrob Agents Chemother 2003;47:786–789.

 92.  Zheng B, Tomita H, Inoue T, et al. Isolation of VanB-type Enterococcus faecalis strains from nosocomial infections: first report of the isolation and identification of the pheromone-responsive plasmids pMG2200, encoding VanB-type vancomycin resistance and a Bac41-type bacteriocin, and pMG2201, encoding erythromycin resistance and cytolysin (Hly/Bac). Antimicrob Agents Chemother 2009;53:735–747.

 93.  Demertzi E, Palepou MF, Kaufmann ME, et al. Characterisation of VanA and VanB elements from glycopeptide-resistant Enterococcus faecium from Greece. J Med Microbiol 2001;50:682–687.

 94.  Hanrahan J, Hoyen C, Rice LB. Geographic distribution of a large mobile element that transfers ampicillin and vancomycin resistance between Enterococcus faecium strains. Antimicrob Agents Chemother 2000;44:1349–1351.

 95.  Lee WG, Kim W. Identification of a novel insertion sequence in vanB2-containing Enterococcus faeciumLett Appl Microbiol 2003;36:186–190.

 96.  Lopez M, Hormazabal JC, Maldonado A, et al. Clonal dissemination of Enterococcus faecalis ST201 and Enterococcus faecium CC17-ST64 containing Tn5382-vanB2 among 16 hospitals in Chile. Clin Microbiol Infect 2009;15:586–588.

 97.  Lorenzo-Diaz F, Delgado T, Reyes-Darias JA, et al. Characterization of the first VanB vancomycin-resistant Enterococcus faecium isolated in a Spanish hospital. Curr Microbiol 2004;48:199–203.

 98.  Lu JJ, Chang TY, Perng CL, et al. The vanB2 gene cluster of the majority of vancomycin-resistant Enterococcus faecium isolates from Taiwan is associated with the pbp5 gene and is carried by Tn5382 containing a novel insertion sequence. Antimicrob Agents Chemother2005;49:3937–3939.

 99.  Torres C, Escobar S, Portillo A, et al. Detection of clonally related vanB2-containing Enterococcus faecium strains in two Spanish hospitals. J Med Microbiol 2006;55:1237–1243.

100.  Valdezate S, Labayru C, Navarro A, et al. Large clonal outbreak of multidrug-resistant CC17 ST17 Enterococcus faecium containing Tn5382 in a Spanish hospital. J Antimicrob Chemother 2009;63:17–20.

101.  Ballard SA, Pertile KK, Lim M, et al. Molecular characterization of vanB elements in naturally occurring gut anaerobes. Antimicrob Agents Chemother 2005;49:1688–1694.

102.  Dahl KH, Sundsfjord A. Transferable vanB2 Tn5382-containing elements in fecal streptococcal strains from veal calves. Antimicrob Agents Chemother 2003;47:2579–2583.

103.  Domingo MC, Huletsky A, Bernal A, et al. Characterization of a Tn5382-like transposon containing the vanB2 gene cluster in a Clostridium strain isolated from human faeces. J Antimicrob Chemother 2005;55:466–474.

104.  Marvaud JC, Mory F, Lambert T. Clostridium clostridioforme and Atopobium minutum clinical isolates with vanB-type resistance in France. J Clin Microbiol 2011;49:3436–3438.

105.  Domingo MC, Huletsky A, Giroux R, et al. High prevalence of glycopeptide resistance genes vanBvanD, and vanG not associated with enterococci in human fecal flora. Antimicrob Agents Chemother 2005;49:4784–4786.

106.  Graham M, Ballard SA, Grabsch EA, et al. High rates of fecal carriage of nonenterococcal vanB in both children and adults. Antimicrob Agents Chemother 2008;52:1195–1197.

107.  Young HL, Ballard SA, Roffey P, et al. Direct detection of vanB2 using the Roche LightCycler vanA/B detection assay to indicate vancomycin-resistant enterococcal carriage—sensitive but not specific. J Antimicrob Chemother 2007;59:809–810.

108.  Usacheva EA, Ginocchio CC, Morgan M, et al. Prospective, multicenter evaluation of the BD GeneOhm VanR assay for direct, rapid detection of vancomycin-resistant Enterococcus species in perianal and rectal specimens. Am J Clin Pathol 2010;134:219–226.

109.  Gazin M, Lammens C, Goossens H, et al. Evaluation of GeneOhm VanR and Xpert vanA/vanB molecular assays for the rapid detection of vancomycin-resistant enterococci. Eur J Clin Microbiol Infect Dis 2012;31:273–276.

110.  Bourdon N, Berenger R, Lepoultier R, et al. Rapid detection of vancomycin-resistant enterococci from rectal swabs by the Cepheid Xpert vanA/vanB assay. Diagn Microbiol Infect Dis 2010;67:291–293.

111.  Mak A, Miller MA, Chong G, et al. Comparison of PCR and culture for screening of vancomycin-resistant enterococci: highly disparate results for vanA and vanBJ Clin Microbiol 2009;47:4136–4137.

112.  Stamper PD, Cai M, Lema C, et al. Comparison of the BD GeneOhm VanR assay to culture for identification of vancomycin-resistant enterococci in rectal and stool specimens. J Clin Microbiol 2007;45:3360–3365.

113.  Seo JY, Kim PW, Lee JH, et al. Evaluation of PCR-based screening for vancomycin-resistant enterococci compared with a chromogenic agar-based culture method. J Med Microbiol 2011;60:945–949.

114.  Liu TY, Tsai KT, Wang HH, et al. Functionalized arrays of Raman-enhancing nanoparticles for capture and culture-free analysis of bacteria in human blood. Nat Commun 2011;2:538.

115.  Cassone M, Del Grosso M, Pantosti A, et al. Detection of genetic elements carrying glycopeptide resistance clusters in Enterococcus by DNA microarrays. Mol Cell Probes 2008;22:162–167.

116.  Roberts MC, Sutcliffe J, Courvalin P, et al. Nomenclature for macrolide and macrolide-lincosamide-streptogramin B resistance determinants. Antimicrob Agents Chemother 1999;43:2823–2830.

117.  Luthje P, Schwarz S. Molecular basis of resistance to macrolides and lincosamides among staphylococci and streptococci from various animal sources collected in the resistance monitoring program BfT-GermVet. Int J Antimicrob Agents 2007;29:528–535.

118.  Varaldo PE, Montanari MP, Giovanetti E. Genetic elements responsible for erythromycin resistance in streptococci. Antimicrob Agents Chemother 2009;53:343–353.

119.  Le Bouter A, Leclercq R, Cattoir V. Molecular basis of resistance to macrolides, lincosamides and streptogramins in Staphylococcus saprophyticus clinical isolates. Int J Antimicrob Agents 2011;37:118–123.

120.  Klaassen CH, Mouton JW. Molecular detection of the macrolide efflux gene: to discriminate or not to discriminate between mef(A) and mef(E). Antimicrob Agents Chemother 2005;49:1271–1278.

121.  Tu D, Blaha G, Moore PB, et al. Structures of MLSBK antibiotics bound to mutated large ribosomal subunits provide a structural explanation for resistance. Cell 2005;121:257–270.

122.  Leclercq R. Mechanisms of resistance to macrolides and lincosamides: nature of the resistance elements and their clinical implications. Clin Infect Dis 2002;34:482–492.

123.  de Vries LE, Christensen H, Agersø Y. The diversity of inducible and constitutively expressed erm(C) genes and association to different replicon types in staphylococci plasmids. Mob Genet Elements 2012;2:72–80.

124.  Sutcliffe J, Tait-Kamradt A, Wondrack L. Streptococcus pneumoniae and Streptococcus pyogenes resistant to macrolides but sensitive to clindamycin: a common resistance pattern mediated by an efflux system. Antimicrob Agents Chemother 1996;40:1817–1824.

125.  Santagati M, Iannelli F, Oggioni MR, et al. Characterization of a genetic element carrying the macrolide efflux gene mef(A) in Streptococcus pneumoniaeAntimicrob Agents Chemother 2000;44:2585–2587.

126.  Malbruny B, Werno AM, Murdoch DR, et al. Cross-resistance to lincosamides, streptogramins A, and pleuromutilins due to the lsa(C) gene in Streptococcus agalactiae UCN70. Antimicrob Agents Chemother 2011;55:1470–1474.

127.  Luthje P, von Kockritz-Blickwede M, Schwarz S. Identification and characterization of nine novel types of small staphylococcal plasmids carrying the lincosamide nucleotidyltransferase gene lnu(A). J Antimicrob Chemother 2007;59:600–606.

128.  Petinaki E, Guerin-Faublee V, Pichereau V, et al. Lincomycin resistance gene lnu(D) in Streptococcus uberisAntimicrob Agents Chemother 2008;52:626–630.

129.  Phuc Nguyen MC, Woerther PL, Bouvet M, et al. Escherichia coli as reservoir for macrolide resistance genes. Emerg Infect Dis 2009;15:1648–1650.

130.  Seo YS, Srinivasan U, Oh KY, et al. Changing molecular epidemiology of group B streptococcus in Korea. J Korean Med Sci 2010;25:817–823.

131.  World Health Organization. Multidrug and extensively drug-resistant TB (M/XDR-TB): 2010 global report on surveillance and response. Geneva: World Health Organization, 2010.

132.  Van Deun A, Martin A, Palomino JC. Diagnosis of drug-resistant tuberculosis: reliability and rapidity of detection. Int J Tuberc Lung Dis 2010;14:131–140.

133.  Müller B, Borrell S, Rose G, et al. The heterogeneous evolution of multidrug-resistant Mycobacterium tuberculosisTrends Genet 2013;29:160–169.

134.  Zhang Y, Yew WW. Mechanisms of drug resistance in Mycobacterium tuberculosisInt J Tuberc Lung Dis 2009;13:1320–1330.

135.  Palomino JC. Molecular detection, identification and drug resistance detection in Mycobacterium tuberculosisFEMS Immunol Med Microbiol 2009;56:103–111.

136.  Campbell EA, Korzheva N, Mustaev A, et al. Structural mechanism for rifampicin inhibition of bacterial RNA polymerase. Cell 2001;104:901–912.

137.  Johnsson K, Schultz PG. Mechanistic studies of the oxidation of isoniazid by the catalase peroxidase from Mycobacterium tuberculosisJ Am Chem Soc 1994;116:7425–7426.

138.  Banerjee A, Dubnau E, Quemard A, et al. inhA, a gene encoding a target for isoniazid and ethionamide in Mycobacterium tuberculosisScience 1994;263:227–230.

139.  Helb D, Jones M, Story E, et al. Rapid detection of Mycobacterium tuberculosis and rifampin resistance by use of on-demand, near-patient technology. J Clin Microbiol 2010;48:229–237.

140.  Hillemann D, Rusch-Gerdes S, Richter E. Evaluation of the GenoType MTBDRplus assay for rifampin and isoniazid susceptibility testing of Mycobacterium tuberculosis strains and clinical specimens. J Clin Microbiol 2007;45:2635–2640.

141.  Hillemann D, Rusch-Gerdes S, Richter E. Feasibility of the GenoType MTBDRsl assay for fluoroquinolone, amikacin-capreomycin, and ethambutol resistance testing of Mycobacterium tuberculosis strains and clinical specimens. J Clin Microbiol 2009;47:1767–1772.

142.  Boehme CC, Nabeta P, Hillemann D, et al. Rapid molecular detection of tuberculosis and rifampin resistance. N Engl J Med 2010;363:1005–1015.

143.  Clouse K, Page-Shipp L, Dansey H, et al. Implementation of Xpert MTB/RIF for routine point-of-care diagnosis of tuberculosis at the primary care level. S Afr Med J 2012;102:805–807.

144.  Moore DA, Shah NS. Alternative methods of diagnosing drug resistance—what can they do for me? J Infect Dis 2011;204(Suppl 4):S1110–S1119.

145.  Abraham EP, Chain E. An enzyme from bacteria able to destroy penicillin. Nature 1940;146:837.

146.  Bush K, Jacoby GA. Updated functional classification of beta-lactamases. Antimicrob Agents Chemother 2010;54:969–976.

147.  Pitout JD. Infections with extended-spectrum beta-lactamase-producing enterobacteriaceae: changing epidemiology and drug treatment choices. Drugs 2010;70:313–333.

148.  Tzouvelekis LS, Markogiannakis A, Psichogiou M, et al. Carbapenemases in Klebsiella pneumoniae and other Enterobacteriaceae: an evolving crisis of global dimensions. Clin Microbiol Rev 2012;25:682–707.

149.  Paterson DL, Bonomo RA. Extended-spectrum beta-lactamases: a clinical update. Clin Microbiol Rev 2005;18:657–686.

150.  Canton R, Coque TM. The CTX-M beta-lactamase pandemic. Curr Opin Microbiol 2006;9:466–475.

151.  Naseer U, Sundsfjord A. The CTX-M conundrum: dissemination of plasmids and Escherichia coli clones. Microb Drug Resist 2011;17:83–97.

152.  Zhao WH, Hu ZQ. Epidemiology and genetics of CTX-M extended-spectrum beta-lactamases in Gram-negative bacteria. Crit Rev Microbiol 2013;39:79–101.

153.  Bonnet R. Growing group of extended-spectrum beta-lactamases: the CTX-M enzymes. Antimicrob Agents Chemother 2004;48:1–14.

154.  Naas T, Poirel L, Nordmann P. Minor extended-spectrum beta-lactamases. Clin Microbiol Infect 2008;14(Suppl 1):42–52.

155.  Walsh TR. Emerging carbapenemases: a global perspective. Int J Antimicrob Agents 2010;36(Suppl 3):S8–S14.

156.  Poirel L, Naas T, Nordmann P. Diversity, epidemiology, and genetics of class D beta-lactamases. Antimicrob Agents Chemother 2010;54:24–38.

157.  Poirel L, Potron A, Nordmann P. OXA-48-like carbapenemases: the phantom menace. J Antimicrob Chemother 2012;67:1597–1606.

158.  Livermore DM, Mushtaq S, Barker K, et al. Characterization of beta-lactamase and porin mutants of Enterobacteriaceae selected with ceftaroline + avibactam (NXL104). J Antimicrob Chemother 2012;67:1354–1358.

159.  Nordmann P, Gniadkowski M, Giske CG, et al. Identification and screening of carbapenemase-producing EnterobacteriaceaeClin Microbiol Infect 2012;18:432–438.

160.  Bernabeu S, Poirel L, Nordmann P. Spectrophotometry-based detection of carbapenemase producers among EnterobacteriaceaeDiagn Microbiol Infect Dis 2012;74:88–90.

161.  Bonnin RA, Naas T, Poirel L, et al. Phenotypic, biochemical, and molecular techniques for detection of metallo-beta-lactamase NDM in Acinetobacter baumanniiJ Clin Microbiol 2012;50:1419–1421.

162.  Nordmann P, Poirel L, Dortet L. Rapid detection of carbapenemase-producing EnterobacteriaceaeEmerg Infect Dis 2012;18:1503–1507.

163.  Nordmann P, Dortet L, Poirel L. Rapid detection of extended-spectrum-beta-lactamase-producing EnterobacteriaceaeJ Clin Microbiol 2012;50:3016–3022.

164.  Dortet L, Poirel L, Nordmann P. Rapid identification of carbapenemase types in Enterobacteriaceae and Pseudomonas spp. by using a biochemical test. Antimicrob Agents Chemother 2012;56:6437–6440.

165.  Burckhardt I, Zimmermann S. Using matrix-assisted laser desorption ionization-time of flight mass spectrometry to detect carbapenem resistance within 1 to 2.5 hours. J Clin Microbiol 2011;49:3321–3324.

166.  Hrabak J, Walkova R, Studentova V, et al. Carbapenemase activity detection by matrix-assisted laser desorption ionization-time of flight mass spectrometry. J Clin Microbiol 2011;49:3222–3227.

167.  Woodford N, Turton JF, Livermore DM. Multiresistant Gram-negative bacteria: the role of high-risk clones in the dissemination of antibiotic resistance. FEMS Microbiol Rev 2011;35:736–755.

168.  Karah N, Sundsfjord A, Towner K, et al. Insights into the global molecular epidemiology of carbapenem non-susceptible clones of Acinetobacter baumanniiDrug Resist Updat 2012;15:237–247.

169.  Dhanji H, Doumith M, Clermont O, et al. Real-time PCR for detection of the O25b-ST131 clone of Escherichia coli and its CTX-M-15-like extended-spectrum beta-lactamases. Int J Antimicrob Agents 2010;36:355–358.

170.  Chen L, Chavda KD, Mediavilla JR, et al. Multiplex real-time PCR for detection of an epidemic KPC-producing Klebsiella pneumoniae ST258 clone. Antimicrob Agents Chemother 2012;56:3444–3447.

171.  Tofteland S, Haldorsen B, Dahl KH, et al. Effects of phenotype and genotype on methods for detection of extended-spectrum-beta-lactamase-producing clinical isolates of Escherichia coli and Klebsiella pneumoniae in Norway. J Clin Microbiol 2007;45:199–205.

172.  Jones CH, Ruzin A, Tuckman M, et al. Pyrosequencing using the single-nucleotide polymorphism protocol for rapid determination of TEM- and SHV-type extended-spectrum beta-lactamases in clinical isolates and identification of the novel beta-lactamase genes blaSHV-48, blaSHV-105, and blaTEM-155. Antimicrob Agents Chemother 2009;53:977–986.

173.  Randegger CC, Hachler H. Real-time PCR and melting curve analysis for reliable and rapid detection of SHV extended-spectrum beta-lactamases. Antimicrob Agents Chemother 2001;45:1730–1736.

174.  Nijhuis R, van Zwet A, Stuart JC, et al. Rapid molecular detection of extended-spectrum beta-lactamase gene variants with a novel ligation-mediated real-time PCR. J Med Microbiol 2012;61:1563–1567.

175.  Dallenne C, Da Costa A, Decre D, et al. Development of a set of multiplex PCR assays for the detection of genes encoding important beta-lactamases in EnterobacteriaceaeJ Antimicrob Chemother 2010;65:490–495.

176.  Woodford N, Fagan EJ, Ellington MJ. Multiplex PCR for rapid detection of genes encoding CTX-M extended-spectrum (beta)-lactamases. J Antimicrob Chemother 2006;57:154–155.

177.  Xu L, Ensor V, Gossain S, et al. Rapid and simple detection of blaCTX-M genes by multiplex PCR assay. J Med Microbiol 2005;54:1183–1187.

178.  Xu L, Evans J, Ling T, et al. Rapid genotyping of CTX-M extended-spectrum beta-lactamases by denaturing high-performance liquid chromatography. Antimicrob Agents Chemother 2007;51:1446–1454.

179.  Naas T, Oxacelay C, Nordmann P. Identification of CTX-M-type extended-spectrum-beta-lactamase genes using real-time PCR and pyrosequencing. Antimicrob Agents Chemother 2007;51:223–230.

180.  Birkett CI, Ludlam HA, Woodford N, et al. Real-time TaqMan PCR for rapid detection and typing of genes encoding CTX-M extended-spectrum beta-lactamases. J Med Microbiol 2007;56:52–55.

181.  Oxacelay C, Ergani A, Naas T, et al. Rapid detection of CTX-M-producing Enterobacteriaceae in urine samples. J Antimicrob Chemother 2009;64:986–989.

182.  Vanstone GL, Yorgancioglu A, Wilkie L, et al. A real-time multiplex PCR assay for the rapid detection of CTX-M-type extended spectrum beta-lactamases directly from blood cultures. J Med Microbiol 2012;61:1631–1632.

183.  Fujita S, Yosizaki K, Ogushi T, et al. Rapid identification of Gram-negative bacteria with and without CTX-M extended-spectrum beta-lactamase from positive blood culture bottles by PCR followed by microchip gel electrophoresis. J Clin Microbiol 2011;49:1483–1488.

184.  Lee S, Park YJ, Kim M, et al. Prevalence of Ambler class A and D beta-lactamases among clinical isolates of Pseudomonas aeruginosa in Korea. J Antimicrob Chemother 2005;56:122–127.

185.  Naas T, Poirel L, Karim A, et al. Molecular characterization of In50, a class 1 integron encoding the gene for the extended-spectrum beta-lactamase VEB-1 in Pseudomonas aeruginosaFEMS Microbiol Lett 1999;176:411–419.

186.  Poirel L, Cabanne L, Vahaboglu H, et al. Genetic environment and expression of the extended-spectrum beta-lactamase blaPER-1 gene in Gram-negative bacteria. Antimicrob Agents Chemother 2005;49:1708–1713.

187.  Poirel L, Le Thomas I, Naas T, et al. Biochemical sequence analyses of GES-1, a novel class A extended-spectrum beta-lactamase, and the class 1 integron In52 from Klebsiella pneumoniaeAntimicrob Agents Chemother 2000;44:622–632.

188.  Bogaerts P, Bauraing C, Deplano A, et al. Emergence and dissemination of BEL-1-producing Pseudomonas aeruginosa isolates in Belgium. Antimicrob Agents Chemother 2007;51:1584–1585.

189.  Woodford N, Ellington MJ, Coelho JM, et al. Multiplex PCR for genes encoding prevalent OXA carbapenemases in Acinetobacter spp. Int J Antimicrob Agents 2006;27:351–353.

190.  Higgins PG, Lehmann M, Seifert H. Inclusion of OXA-143 primers in a multiplex polymerase chain reaction (PCR) for genes encoding prevalent OXA carbapenemases in Acinetobacter spp. Int J Antimicrob Agents 2010;35:305.

191.  Voets GM, Fluit AC, Scharringa J, et al. A set of multiplex PCRs for genotypic detection of extended-spectrum beta-lactamases, carbapenemases, plasmid-mediated AmpC beta-lactamases and OXA beta-lactamases. Int J Antimicrob Agents 2011;37:356–359.

192.  Ellington MJ, Kistler J, Livermore DM, et al. Multiplex PCR for rapid detection of genes encoding acquired metallo-beta-lactamases. J Antimicrob Chemother 2007;59:321–322.

193.  Poirel L, Walsh TR, Cuvillier V, et al. Multiplex PCR for detection of acquired carbapenemase genes. Diagn Microbiol Infect Dis 2011;70:119–123.

194.  Monteiro J, Widen RH, Pignatari AC, et al. Rapid detection of carbapenemase genes by multiplex real-time PCR. J Antimicrob Chemother 2012;67:906–909.

195.  Mendes RE, Kiyota KA, Monteiro J, et al. Rapid detection and identification of metallo-beta-lactamase-encoding genes by multiplex real-time PCR assay and melt curve analysis. J Clin Microbiol 2007;45:544–547.

196.  Roth AL, Hanson ND. Rapid detection and statistical differentiation of KPC gene variants in Gram-negative pathogens by use of high-resolution melting and ScreenClust analyses. J Clin Microbiol 2013;51:61–65.

197.  Swayne RL, Ludlam HA, Shet VG, et al. Real-time TaqMan PCR for rapid detection of genes encoding five types of non-metallo- (class A and D) carbapenemases in EnterobacteriaceaeInt J Antimicrob Agents 2011;38:35–38.

198.  Richter SN, Frasson I, Biasolo MA, et al. Ultrarapid detection of blaKPC(1)/(2)-(1)(2) from perirectal and nasal swabs by use of real-time PCR. J Clin Microbiol 2012;50:1718–1720.

199.  Cole JM, Schuetz AN, Hill CE, et al. Development and evaluation of a real-time PCR assay for detection of Klebsiella pneumoniae carbapenemase genes. J Clin Microbiol 2009;47:322–326.

200.  Diene SM, Bruder N, Raoult D, et al. Real-time PCR assay allows detection of the New Delhi metallo-beta-lactamase (NDM-1)-encoding gene in France. Int J Antimicrob Agents 2011;37:544–546.

201.  Naas T, Ergani A, Carrer A, et al. Real-time PCR for detection of NDM-1 carbapenemase genes from spiked stool samples. Antimicrob Agents Chemother 2011;55:4038–4043.

202.  Ong DC, Koh TH, Syahidah N, et al. Rapid detection of the blaNDM-1 gene by real-time PCR. J Antimicrob Chemother 2011;66:1647–1649.

203.  Kruttgen A, Razavi S, Imohl M, et al. Real-time PCR assay and a synthetic positive control for the rapid and sensitive detection of the emerging resistance gene New Delhi Metallo-beta-lactamase-1 (bla(NDM-1)). Med Microbiol Immunol 2011;200:137–141.

204.  Liu W, Zou D, Li Y, et al. Sensitive and rapid detection of the new Delhi metallo-beta-lactamase gene by loop-mediated isothermal amplification. J Clin Microbiol 2012;50:1580–1585.

205.  Hindiyeh M, Smollen G, Grossman Z, et al. Rapid detection of blaKPC carbapenemase genes by real-time PCR. J Clin Microbiol 2008;46:2879–2883.

206.  Spanu T, Fiori B, D’inzeo T, et al. Evaluation of the New NucliSENS EasyQ KPC test for rapid detection of Klebsiella pneumoniae carbapenemase genes (blaKPC). J Clin Microbiol 2012;50:2783–2785.

207.  Batchelor M, Hopkins KL, Liebana E, et al. Development of a miniaturised microarray-based assay for the rapid identification of antimicrobial resistance genes in Gram-negative bacteria. Int J Antimicrob Agents 2008;31:440–451.

208.  Frye JG, Lindsey RL, Rondeau G, et al. Development of a DNA microarray to detect antimicrobial resistance genes identified in the National Center for Biotechnology Information database. Microb Drug Resist 2010;16:9–19.

209.  Grimm V, Ezaki S, Susa M, et al. Use of DNA microarrays for rapid genotyping of TEM beta-lactamases that confer resistance. J Clin Microbiol 2004;42:3766–3774.

210.  Leinberger DM, Grimm V, Rubtsova M, et al. Integrated detection of extended-spectrum-beta-lactam resistance by DNA microarray-based genotyping of TEM, SHV, and CTX-M genes. J Clin Microbiol 2010;48:460–471.

211.  Peter H, Berggrav K, Thomas P, et al. Direct detection and genotyping of Klebsiella pneumoniae carbapenemases from urine by use of a new DNA microarray test. J Clin Microbiol 2012;50:3990–3998.

212.  Rubtsova MY, Ulyashova MM, Edelstein MV, et al. Oligonucleotide microarrays with horseradish peroxidase-based detection for the identification of extended-spectrum beta-lactamases. Biosens Bioelectron 2010;26:1252–1260.

213.  Kaase M, Szabados F, Wassill L, et al. Detection of carbapenemases in Enterobacteriaceae by a commercial multiplex PCR. J Clin Microbiol 2012;50:3115–3118.

214.  Cohen Stuart J, Dierikx C, Al Naiemi N, et al. Rapid detection of TEM, SHV and CTX-M extended-spectrum beta-lactamases in Enterobacteriaceae using ligation-mediated amplification with microarray analysis. J Antimicrob Chemother 2010;65:1377–1381.

215.  Naas T, Cuzon G, Bogaerts P, et al. Evaluation of a DNA microarray (Check-MDR CT102) for rapid detection of TEM, SHV, and CTX-M extended-spectrum beta-lactamases and of KPC, OXA-48, VIM, IMP, and NDM-1 carbapenemases. J Clin Microbiol 2011;49:1608–1613.

216.  Woodford N, Warner M, Pike R, et al. Evaluation of a commercial microarray to detect carbapenemase-producing EnterobacteriaceaeJ Antimicrob Chemother 2011;66:2887–2888.

217.  Cuzon G, Naas T, Bogaerts P, et al. Evaluation of a DNA microarray for the rapid detection of extended-spectrum beta-lactamases (TEM, SHV and CTX-M), plasmid-mediated cephalosporinases (CMY-2-like, DHA, FOX, ACC-1, ACT/MIR and CMY-1-like/MOX) and carbapenemases (KPC, OXA-48, VIM, IMP and NDM). J Antimicrob Chemother 2012;67:1865–1869.

218.  Stuart JC, Voets G, Scharringa J, et al. Detection of carbapenemase-producing Enterobacteriaceae with a commercial DNA microarray. J Med Microbiol 2012;61:809–812.

219.  Veyssier P, Bryskier A. Aminocyclitol aminoglycosides. In: Bryskier A, ed. Antimicrobial agents: antibacterials and antifungals. Washington, DC: ASM Press, 2005:453–469.

220.  Majumder K, Wei L, Annedi SC, et al. Aminoglycoside antibiotics. In: Bonomo RA, Tolmasky M, eds. Enzyme-mediated resistance to antibiotics: mechanismsdisseminationand prospects for inhibition. Washington, DC: ASM Press, 2007:7–20.

221.  Ramirez MS, Tolmasky ME. Aminoglycoside modifying enzymes. Drug Resist Updat 2010;13:151–171.

222.  Wachino J, Arakawa Y. Exogenously acquired 16S rRNA methyltransferases found in aminoglycoside-resistant pathogenic Gram-negative bacteria: an update. Drug Resist Updat 2012;15:133–148.

223.  Shaw KJ, Rather PN, Hare RS, et al. Molecular genetics of aminoglycoside resistance genes and familial relationships of the aminoglycoside-modifying enzymes. Microbiol Rev 1993;57:138–163.

224.  Tolmasky ME. Aminoglycoside-modifying enzymes: characteristics, localization, and dissemination. In: Bonomo RA, Tolmasky M, eds. Enzyme-mediated resistance to antibiotics: mechanismsdisseminationand prospects for inhibition. Washington, DC: ASM Press, 2007:35–52.

225.  Perreten V, Vorlet-Fawer L, Slickers P, et al. Microarray-based detection of 90 antibiotic resistance genes of gram-positive bacteria. J Clin Microbiol 2005;43:2291–2302.

226.  Diarra MS, Rempel H, Champagne J, et al. Distribution of antimicrobial resistance and virulence genes in Enterococcus spp. and characterization of isolates from broiler chickens. Appl Environ Microbiol 2010;76:8033–8043.

227.  Champagne J, Diarra MS, Rempel H, et al. Development of a DNA microarray for enterococcal species, virulence, and antibiotic resistance gene determinations among isolates from poultry. Appl Environ Microbiol 2011;77:2625–2633.

228.  Garneau P, Labrecque O, Maynard C, et al. Use of a bacterial antimicrobial resistance gene microarray for the identification of resistant Staphylococcus aureusZoonoses Public Health 2010;57(Suppl 1):94–99.

229.  Frye JG, Jesse T, Long F, et al. DNA microarray detection of antimicrobial resistance genes in diverse bacteria. Int J Antimicrob Agents 2006;27:138–151.

230.  Vakulenko SB, Mobashery S. Versatility of aminoglycosides and prospects for their future. Clin Microbiol Rev 2003;16:430–450.

231.  Hidalgo-Grass C, Strahilevitz J. High-resolution melt curve analysis for identification of single nucleotide mutations in the quinolone resistance gene aac(6’)-Ib-crAntimicrob Agents Chemother 2010;54:3509–3511.

232.  Bell JM, Turnidge JD, Andersson P. aac(6’)-Ib-cr genotyping by simultaneous high-resolution melting analyses of an unlabeled probe and full-length amplicon. Antimicrob Agents Chemother 2010;54:1378–1380.

233.  Lindemann PC, Risberg K, Wiker HG, et al. Aminoglycoside resistance in clinical Escherichia coli and Klebsiella pneumoniae isolates from Western Norway. APMIS 2012;120:495–502.

234.  Doi Y, Arakawa Y. 16S ribosomal RNA methylation: emerging resistance mechanism against aminoglycosides. Clin Infect Dis 2007;45:88–94.

235.  Bercot B, Poirel L, Nordmann P. Updated multiplex polymerase chain reaction for detection of 16S rRNA methylases: high prevalence among NDM-1 producers. Diagn Microbiol Infect Dis 2011;71:442–445.

236.  Savic M, Lovric J, Tomic TI, et al. Determination of the target nucleosides for members of two families of 16S rRNA methyltransferases that confer resistance to partially overlapping groups of aminoglycoside antibiotics. Nucleic Acids Res 2009;37:5420–5431.

237.  Flamm RK, Farrell DJ, Mendes RE, et al. ZAAPS Program results for 2010: an activity and spectrum analysis of linezolid using clinical isolates from 75 medical centres in 24 countries. J Chemother 2012;24:328–337.

238.  Ross JE, Farrell DJ, Mendes RE, et al. Eight-year (2002–2009) summary of the linezolid (Zyvox(R) Annual Appraisal of Potency and Spectrum; ZAAPS) program in European countries. J Chemother 2011;23:71–76.

239.  Flamm RK, Mendes RE, Ross JE, et al. Linezolid surveillance results for the United States: LEADER surveillance program 2011. Antimicrob Agents Chemother 2013;57:1077–1081.

240.  Wilson DN, Schluenzen F, Harms JM, et al. The oxazolidinone antibiotics perturb the ribosomal peptidyl-transferase center and effect tRNA positioning. Proc Natl Acad Sci U S A 2008;105:13339–13344.

241.  Diaz L, Kiratisin P, Mendes RE, et al. Transferable plasmid-mediated resistance to linezolid due to cfr in a human clinical isolate of Enterococcus faecalisAntimicrob Agents Chemother 2012;56:3917–3922.

242.  Gu B, Kelesidis T, Tsiodras S, et al. The emerging problem of linezolid-resistant StaphylococcusJ Antimicrob Chemother 2013;68:4–11.

243.  Farrell DJ, Morrissey I, Bakker S, et al. In vitro activities of telithromycin, linezolid, and quinupristin-dalfopristin against Streptococcus pneumoniae with macrolide resistance due to ribosomal mutations. Antimicrob Agents Chemother 2004;48:3169–3171.

244.  Wolter N, Smith AM, Farrell DJ, et al. Novel mechanism of resistance to oxazolidinones, macrolides, and chloramphenicol in ribosomal protein L4 of the pneumococcus. Antimicrob Agents Chemother 2005;49:3554–3557.

245.  Ross JE, Anderegg TR, Sader HS, et al. Trends in linezolid susceptibility patterns in 2002: report from the worldwide Zyvox Annual Appraisal of Potency and Spectrum Program. Diagn Microbiol Infect Dis 2005;52:53–58.

246.  Lobritz M, Hutton-Thomas R, Marshall S, et al. Recombination proficiency influences frequency and locus of mutational resistance to linezolid in Enterococcus faecalisAntimicrob Agents Chemother 2003;47:3318–3320.

247.  Marshall SH, Donskey CJ, Hutton-Thomas R, et al. Gene dosage and linezolid resistance in Enterococcus faecium and Enterococcus faecalisAntimicrob Agents Chemother 2002;46:3334–3336.

248.  Meka VG, Pillai SK, Sakoulas G, et al. Linezolid resistance in sequential Staphylococcus aureus isolates associated with a T2500A mutation in the 23S rRNA gene and loss of a single copy of rRNA. J Infect Dis 2004;190:311–317.

249.  Long KS, Poehlsgaard J, Kehrenberg C, et al. The Cfr rRNA methyltransferase confers resistance to phenicols, lincosamides, oxazolidinones, pleuromutilins, and streptogramin A antibiotics. Antimicrob Agents Chemother 2006;50:2500–2505.

250.  Morales G, Picazo JJ, Baos E, et al. Resistance to linezolid is mediated by the cfr gene in the first report of an outbreak of linezolid-resistant Staphylococcus aureusClin Infect Dis 2010;50:821–825.

251.  Sanchez Garcia M, De la Torre MA, Morales G, et al. Clinical outbreak of linezolid-resistant Staphylococcus aureus in an intensive care unit. JAMA 2010;303:2260–2264.

252.  Locke JB, Morales G, Hilgers M, et al. Elevated linezolid resistance in clinical cfr-positive Staphylococcus aureus isolates is associated with co-occurring mutations in ribosomal protein L3. Antimicrob Agents Chemother 2010;54:5352–5355.

253.  Bonilla H, Huband MD, Seidel J, et al. Multicity outbreak of linezolid-resistant Staphylococcus epidermidis associated with clonal spread of a cfr-containing strain. Clin Infect Dis 2010;51:796–800.

254.  Gopegui ER, Juan C, Zamorano L, et al. Transferable multidrug resistance plasmid carrying cfr associated with tet(L)ant(4’)-Ia, and dfrK genes from a clinical methicillin-resistant Staphylococcus aureus ST125 strain. Antimicrob Agents Chemother 2012;56:2139–2142.

255.  Cai JC, Hu YY, Zhang R, et al. Linezolid-resistant clinical isolates of meticillin-resistant coagulase-negative staphylococci and Enterococcus faecium from China. J Med Microbiol 2012;61:1568–1573.

256.  Bongiorno D, Campanile F, Mongelli G, et al. DNA methylase modifications and other linezolid resistance mutations in coagulase-negative staphylococci in Italy. J Antimicrob Chemother 2010;65:2336–2340.

257.  LaMarre JM, Locke JB, Shaw KJ, et al. Low fitness cost of the multidrug resistance gene cfrAntimicrob Agents Chemother 2011;55:3714–3719.

258.  Schwarz S, Werckenthin C, Kehrenberg C. Identification of a plasmid-borne chloramphenicol-florfenicol resistance gene in Staphylococcus sciuriAntimicrob Agents Chemother 2000;44:2530–2533.

259.  Kehrenberg C, Schwarz S. Distribution of florfenicol resistance genes fexA and cfr among chloramphenicol-resistant Staphylococcus isolates. Antimicrob Agents Chemother 2006;50:1156–1163.

260.  Liu Y, Wang Y, Wu C, et al. First report of the multidrug resistance gene cfr in Enterococcus faecalis of animal origin. Antimicrob Agents Chemother 2012;56:1650–1654.

261.  Liu Y, Wang Y, Schwarz S, et al. Transferable multiresistance plasmids carrying cfr in Enterococcus spp from swine and farm environment. Antimicrob Agents Chemother 2013;57:42–48.

262.  Dai L, Wu CM, Wang MG, et al. First report of the multidrug resistance gene cfr and the phenicol resistance gene fexA in a Bacillus strain from swine feces. Antimicrob Agents Chemother 2010;54:3953–3955.

263.  Wang Y, Schwarz S, Shen Z, et al. Co-location of the multiresistance gene cfr and the novel streptomycin resistance gene aadY on a small plasmid in a porcine Bacillus strain. J Antimicrob Chemother 2012;67:1547–1549.

264.  Zhang WJ, Wu CM, Wang Y, et al. The new genetic environment of cfr on plasmid pBS-02 in a Bacillus strain. J Antimicrob Chemother 2011;66:1174–1175.

265.  Wang Y, Wang Y, Schwarz S, et al. Detection of the staphylococcal multiresistance gene cfr in Macrococcus caseolyticus and Jeotgalicoccus pinnipedialisJ Antimicrob Chemother 2012;67:1824–1827.

266.  Wang Y, He T, Schwarz S, et al. Detection of the staphylococcal multiresistance gene cfr in Escherichia coli of domestic-animal origin. J Antimicrob Chemother 2012;67:1094–1098.

267.  Wang Y, Wang Y, Wu CM, et al. Detection of the staphylococcal multiresistance gene cfr in Proteus vulgaris of food animal origin. J Antimicrob Chemother 2011;66:2521–2526.

268.  Qi J, Du Y, Zhu R, et al. A loop-mediated isothermal amplification method for rapid detection of the multidrug-resistance gene cfrGene 2012;504:140–143.

269.  Bonora MG, Solbiati M, Stepan E, et al. Emergence of linezolid resistance in the vancomycin-resistant Enterococcus faecium multilocus sequence typing C1 epidemic lineage. J Clin Microbiol 2006;44:1153–1155.

270.  Toh SM, Xiong L, Arias CA, et al. Acquisition of a natural resistance gene renders a clinical strain of methicillin-resistant Staphylococcus aureus resistant to the synthetic antibiotic linezolid. Mol Microbiol 2007;64:1506–1514.

271.  Werner G, Strommenger B, Klare I, et al. Molecular detection of linezolid resistance in Enterococcus faecium and Enterococcus faecalis by use of 5’ nuclease real-time PCR compared to a modified classical approach. J Clin Microbiol 2004;42:5327–5331.

272.  Werner G, Bartel M, Wellinghausen N, et al. Detection of mutations conferring resistance to linezolid in Enterococcus spp. by fluorescence in situ hybridization. J Clin Microbiol 2007;45:3421–3423.

273.  Woodford N, Tysall L, Auckland C, et al. Detection of oxazolidinone-resistant Enterococcus faecalis and Enterococcus faecium strains by real-time PCR and PCR-restriction fragment length polymorphism analysis. J Clin Microbiol 2002;40:4298–4300.

274.  Woodford N, North SE, Ellington MJ. Detecting mutations that confer oxazolidinone resistance in Gram-positive bacteria. Methods Mol Biol 2007;373:103–114.

275.  Zhu W, Tenover FC, Limor J, et al. Use of pyrosequencing to identify point mutations in domain V of 23S rRNA genes of linezolid-resistant Staphylococcus aureus and Staphylococcus epidermidisEur J Clin Microbiol Infect Dis 2007;26:161–165.

276.  Locke JB, Rahawi S, Lamarre J, et al. Genetic environment and stability of cfr in methicillin-resistant Staphylococcus aureus CM05. Antimicrob Agents Chemother 2012;56:332–340.

277.  Pillai SK, Sakoulas G, Wennersten C, et al. Linezolid resistance in Staphylococcus aureus: characterization and stability of resistant phenotype. J Infect Dis 2002;186:1603–1607.

278.  Bourgeois-Nicolaos N, Massias L, Couson B, et al. Dose dependence of emergence of resistance to linezolid in Enterococcus faecalis in vivoJ Infect Dis 2007;195:1480–1488.

279.  Farrell DJ, Douthwaite S, Morrissey I, et al. Macrolide resistance by ribosomal mutation in clinical isolates of Streptococcus pneumoniae from the PROTEKT 1999–2000 study. Antimicrob Agents Chemother 2003;47:1777–1783.

280.  Tait-Kamradt A, Davies T, Cronan M, et al. Mutations in 23S rRNA and ribosomal protein L4 account for resistance in pneumococcal strains selected in vitro by macrolide passage. Antimicrob Agents Chemother 2000;44:2118–2125.

281.  Prystowsky J, Siddiqui F, Chosay J, et al. Resistance to linezolid: characterization of mutations in rRNA and comparison of their occurrences in vancomycin-resistant enterococci. Antimicrob Agents Chemother 2001;45:2154–2156.

282.  Sorlozano A, Gutierrez J, Martinez T, et al. Detection of new mutations conferring resistance to linezolid in glycopeptide-intermediate susceptibility Staphylococcus hominis subspecies hominis circulating in an intensive care unit. Eur J Clin Microbiol Infect Dis 2010;29:73–80.

283.  Tsiodras S, Gold HS, Sakoulas G, et al. Linezolid resistance in a clinical isolate of Staphylococcus aureusLancet 2001;358:207–208.

284.  Locke JB, Hilgers M, Shaw KJ. Mutations in ribosomal protein L3 are associated with oxazolidinone resistance in staphylococci of clinical origin. Antimicrob Agents Chemother 2009;53:5275–5278.

285.  Miller K, Dunsmore CJ, Fishwick CW, et al. Linezolid and tiamulin cross-resistance in Staphylococcus aureus mediated by point mutations in the peptidyl transferase center. Antimicrob Agents Chemother 2008;52:1737–1742.

286.  Hooper DC. Emerging mechanisms of fluoroquinolone resistance. Emerg Infect Dis 2001;7:337–341.

287.  Martinez-Martinez L, Pascual A, Jacoby GA. Quinolone resistance from a transferable plasmid. Lancet 1998;351:797–799.

288.  Rodriguez-Martinez JM, Cano ME, Velasco C, et al. Plasmid-mediated quinolone resistance: an update. J Infect Chemother 2011;17:149–182.

289.  Strahilevitz J, Jacoby GA, Hooper DC, et al. Plasmid-mediated quinolone resistance: a multifaceted threat. Clin Microbiol Rev 2009;22:664–689.

290.  Jacoby G, Cattoir V, Hooper D, et al. qnr Gene nomenclature. Antimicrob Agents Chemother 2008;52:2297–2299.

291.  Robicsek A, Strahilevitz J, Jacoby GA, et al. Fluoroquinolone-modifying enzyme: a new adaptation of a common aminoglycoside acetyltransferase. Nat Med 2006;12:83–88.

292.  Yamane K, Wachino J, Suzuki S, et al. New plasmid-mediated fluoroquinolone efflux pump, QepA, found in an Escherichia coli clinical isolate. Antimicrob Agents Chemother 2007;51:3354–3360.

293.  Kim HB, Wang M, Park CH, et al. oqxAB encoding a multidrug efflux pump in human clinical isolates of EnterobacteriaceaeAntimicrob Agents Chemother 2009;53:3582–3584.

294.  Robicsek A, Strahilevitz J, Sahm DF, et al. qnr prevalence in ceftazidime-resistant Enterobacteriaceae isolates from the United States. Antimicrob Agents Chemother 2006;50:2872–2874.

295.  Cattoir V, Poirel L, Rotimi V, et al. Multiplex PCR for detection of plasmid-mediated quinolone resistance qnr genes in ESBL-producing enterobacterial isolates. J Antimicrob Chemother 2007;60:394–397.

296.  Kim HB, Park CH, Kim CJ, et al. Prevalence of plasmid-mediated quinolone resistance determinants over a 9-year period. Antimicrob Agents Chemother 2009;53:639–645.

297.  Guillard T, Moret H, Brasme L, et al. Rapid detection of qnr and qepA plasmid-mediated quinolone resistance genes using real-time PCR. Diagn Microbiol Infect Dis 2011;70:253–259.

298.  Wang M, Guo Q, Xu X, et al. New plasmid-mediated quinolone resistance gene, qnrC, found in a clinical isolate of Proteus mirabilisAntimicrob Agents Chemother 2009;53:1892–1897.

299.  Veldman K, Cavaco LM, Mevius D, et al. International collaborative study on the occurrence of plasmid-mediated quinolone resistance in Salmonella enterica and Escherichia coli isolated from animals, humans, food and the environment in 13 European countries. J Antimicrob Chemother2011;66:1278–1286.

300.  Minarini LA, Poirel L, Cattoir V, et al. Plasmid-mediated quinolone resistance determinants among enterobacterial isolates from outpatients in Brazil. J Antimicrob Chemother 2008;62:474–478.

301.  Yamane K, Wachino J, Suzuki S, et al. Plasmid-mediated qepA gene among Escherichia coli clinical isolates from Japan. Antimicrob Agents Chemother 2008;52:1564–1566.

302.  Liu BT, Wang XM, Liao XP, et al. Plasmid-mediated quinolone resistance determinants oqxAB and aac(6’)-Ib-cr and extended-spectrum beta-lactamase gene blaCTX-M-24 co-located on the same plasmid in one Escherichia coli strain from China. J Antimicrob Chemother2011;66:1638–1639.

303.  Park CH, Robicsek A, Jacoby GA, et al. Prevalence in the United States of aac(6’)-Ib-cr encoding a ciprofloxacin-modifying enzyme. Antimicrob Agents Chemother 2006;50:3953–3955.

304.  Guillard T, Duval V, Moret H, et al. Rapid detection of aac(6’)-Ib-cr quinolone resistance gene by pyrosequencing. J Clin Microbiol 2010;48:286–289.

305.  Warburg G, Korem M, Robicsek A, et al. Changes in aac(6’)-Ib-cr prevalence and fluoroquinolone resistance in nosocomial isolates of Escherichia coli collected from 1991 through 2005. Antimicrob Agents Chemother 2009;53:1268–1270.

306.  Zankari E, Hasman H, Kaas RS, et al. Genotyping using whole-genome sequencing is a realistic alternative to surveillance based on phenotypic antimicrobial susceptibility testing. J Antimicrob Chemother 2013;68:771–777.

307.  Sambrook J, Fritsch EF, Maniatis T. Molecular cloning: a laboratory manual. New York: Cold Spring Harbor Laboratory Press, 1989.

308.  Elsayed S, Hamilton N, Boyd D, et al. Improved primer design for multiplex PCR analysis of vancomycin-resistant Enterococcus spp. J Clin Microbiol 2001;39:2367–2368.

309.  Parks SB, Popovich BW, Press RD. Real-time polymerase chain reaction with fluorescent hybridization probes for the detection of prevalent mutations causing common thrombophilic and iron overload phenotypes. Am J Clin Pathol 2001;115:439–447.

310.  Oleastro M, Menard A, Santos A, et al. Real-time PCR assay for rapid and accurate detection of point mutations conferring resistance to clarithromycin in Helicobacter pyloriJ Clin Microbiol 2003;41:397–402.

311.  Holland PM, Abramson RD, Watson R, et al. Detection of specific polymerase chain reaction product by utilizing the 5’—3’ exonuclease activity of Thermus aquaticus DNA polymerase. Proc Natl Acad Sci U S A 1991;88:7276–7280.

312.  Ramirez MV, Cowart KC, Campbell PJ, et al. Rapid detection of multidrug-resistant Mycobacterium tuberculosis by use of real-time PCR and high-resolution melt analysis. J Clin Microbiol 2010;48:4003–4009.

313.  Kutyavin IV, Afonina IA, Mills A, et al. 3’-minor groove binder-DNA probes increase sequence specificity at PCR extension temperatures. Nucleic Acids Res 2000;28:655–661.

314.  Wada T, Maeda S, Tamaru A, et al. Dual-probe assay for rapid detection of drug-resistant Mycobacterium tuberculosis by real-time PCR. J Clin Microbiol 2004;42:5277–5285.

315.  Fang H, Ohlsson AK, Jiang GX, et al. Screening for vancomycin-resistant enterococci: an efficient and economical laboratory-developed test. Eur J Clin Microbiol Infect Dis 2012;31:261–265.

316.  Tyagi S, Kramer FR. Molecular beacons: probes that fluoresce upon hybridization. Nat Biotechnol 1996;14:303–308.

317.  Drake TJ, Tan W. Molecular beacon DNA probes and their bioanalytical applications. Appl Spectrosc 2004;58:269A–280A.

318.  Sinsimer D, Leekha S, Park S, et al. Use of a multiplex molecular beacon platform for rapid detection of methicillin and vancomycin resistance in Staphylococcus aureusJ Clin Microbiol 2005;43:4585–4591.

319.  Chakravorty S, Kothari H, Aladegbami B, et al. Rapid, high-throughput detection of rifampin resistance and heteroresistance in Mycobacterium tuberculosis by use of sloppy molecular beacon melting temperature coding. J Clin Microbiol 2012;50:2194–2202.

320.  Taylor CF. Mutation scanning using high-resolution melting. Biochem Soc Trans 2009;37:433–437.

321.  Choi GE, Lee SM, Yi J, et al. High-resolution melting curve analysis for rapid detection of rifampin and isoniazid resistance in Mycobacterium tuberculosis clinical isolates. J Clin Microbiol 2010;48:3893–3898.

322.  Gabriel EM, Douarre PE, Fitzgibbon S, et al. High-resolution melting analysis for rapid detection of linezolid resistance (mediated by G2576T mutation) in Staphylococcus epidermidisJ Microbiol Methods 2012;90:134–136.

323.  Compton J. Nucleic acid sequence-based amplification. Nature 1991;350:91–92.

324.  Deiman B, Jay C, Zintilini C, et al. Efficient amplification with NASBA of hepatitis B virus, herpes simplex virus and methicillin resistant Staphylococcus aureus DNA. J Virol Methods 2008;151:283–293.

325.  Notomi T, Okayama H, Masubuchi H, et al. Loop-mediated isothermal amplification of DNA. Nucleic Acids Res 2000;28:E63.

326.  Misawa Y, Yoshida A, Saito R, et al. Application of loop-mediated isothermal amplification technique to rapid and direct detection of methicillin-resistant Staphylococcus aureus (MRSA) in blood cultures. J Infect Chemother 2007;13:134–140.

327.  Vincent M, Xu Y, Kong H. Helicase-dependent isothermal DNA amplification. EMBO Rep 2004;5:795–800.

328.  Ao W, Aldous S, Woodruff E, et al. Rapid detection of rpoB gene mutations conferring rifampin resistance in Mycobacterium tuberculosisJ Clin Microbiol 2012;50:2433–2440.

329.  Goldmeyer J, Li H, McCormac M, et al. Identification of Staphylococcus aureus and determination of methicillin resistance directly from positive blood cultures by isothermal amplification and a disposable detection device. J Clin Microbiol 2008;46:1534–1536.

330.  Paule SM, Hacek DM, Kufner B, et al. Performance of the BD GeneOhm methicillin-resistant Staphylococcus aureus test before and during high-volume clinical use. J Clin Microbiol 2007;45:2993–2998.

331.  Depardieu F, Courvalin P, Msadek T. A six amino acid deletion, partially overlapping the VanSB G2 ATP-binding motif, leads to constitutive glycopeptide resistance in VanB-type Enterococcus faeciumMol Microbiol 2003;50:1069–1083.

332.  Hayden MK, Trenholme GM, Schultz JE, et al. In vivo development of teicoplanin resistance in a VanB Enterococcus faecium isolate. J Infect Dis 1993;167:1224–1227.

333.  Kawalec M, Gniadkowski M, Kedzierska J, et al. Selection of a teicoplanin-resistant Enterococcus faecium mutant during an outbreak caused by vancomycin-resistant enterococci with the vanB phenotype. J Clin Microbiol 2001;39:4274–4282.

334.  Lefort A, Arthur M, Depardieu F, et al. Expression of glycopeptide-resistance gene in response to vancomycin and teicoplanin in the cardiac vegetations of rabbits infected with VanB-type Enterococcus faecalis. J Infect Dis 2004;189:90–97.

335.  San Millan A, Depardieu F, Godreuil S, et al. VanB-type Enterococcus faecium clinical isolate successively inducibly resistant to, dependent on, and constitutively resistant to vancomycin. Antimicrob Agents Chemother 2009;53:1974–1982.

336.  Dutka-Malen S, Evers S, Courvalin P. Detection of glycopeptide resistance genotypes and identification to the species level of clinically relevant enterococci by PCR. J Clin Microbiol 1995;33:24–27.

337.  Patel R, Uhl JR, Kohner P, et al. Multiplex PCR detection of vanAvanBvanC-1, and vanC-2/3 genes in enterococci. J Clin Microbiol 1997;35:703–707.

338.  Bell JM, Paton JC, Turnidge J. Emergence of vancomycin-resistant enterococci in Australia: phenotypic and genotypic characteristics of isolates. J Clin Microbiol 1998;36:2187–2190.

339.  Jayaratne P, Rutherford C. Detection of clinically relevant genotypes of vancomycin-resistant enterococci in nosocomial surveillance specimens by PCR. J Clin Microbiol 1999;37:2090–2092.

340.  Petrich AK, Luinstra KE, Groves D, et al. Direct detection of vanA and vanB genes in clinical specimens for rapid identification of vancomycin resistant enterococci (VRE) using multiplex PCR. Mol Cell Probes 1999;13:275–281.

341.  Kariyama R, Mitsuhata R, Chow JW, et al. Simple and reliable multiplex PCR assay for surveillance isolates of vancomycin-resistant enterococci. J Clin Microbiol 2000;38:3092–3095.

342.  Lu JJ, Perng CL, Chiueh TS, et al. Detection and typing of vancomycin-resistance genes of enterococci from clinical and nosocomial surveillance specimens by multiplex PCR. Epidemiol Infect 2001;126:357–363.

343.  Perez-Hernandez X, Mendez-Alvarez S, Claverie-Martin F. A PCR assay for rapid detection of vancomycin-resistant enterococci. Diagn Microbiol Infect Dis 2002;42:273–277.

344.  Mac K, Wichmann-Schauer H, Peters J, et al. Species identification and detection of vancomycin resistance genes in enterococci of animal origin by multiplex PCR. Int J Food Microbiol 2003;88:305–309.

345.  Depardieu F, Perichon B, Courvalin P. Detection of the van alphabet and identification of enterococci and staphylococci at the species level by multiplex PCR. J Clin Microbiol 2004;42:5857–5860.

346.  Benadof D, San Martin M, Aguirre J, et al. A new multiplex PCR assay for the simultaneous detection of vancomycin-resistant enterococci from rectal swabs. J Infect 2010;60:354–359.

347.  Lee SY, Park KG, Lee GD, et al. Comparison of Seeplex VRE detection kit with ChromID VRE agar for detection of vancomycin-resistant enterococci in rectal swab specimens. Ann Clin Lab Sci 2010;40:163–166.

348.  Gurtler V, Grando D, Mayall BC, et al. A novel method for simultaneous Enterococcus species identification/typing and van genotyping by high resolution melt analysis. J Microbiol Methods 2012;90:167–181.

349.  Palladino S, Kay ID, Flexman JP, et al. Rapid detection of vanA and vanB genes directly from clinical specimens and enrichment broths by real-time multiplex PCR assay. J Clin Microbiol 2003;41:2483–2486.

350.  Palladino S, Kay ID, Costa AM, et al. Real-time PCR for the rapid detection of vanA and vanB genes. Diagn Microbiol Infect Dis 2003;45:81–84.

351.  Sloan LM, Uhl JR, Vetter EA, et al. Comparison of the Roche LightCycler vanA/vanB detection assay and culture for detection of vancomycin-resistant enterococci from perianal swabs. J Clin Microbiol 2004;42:2636–2643.

352.  Marner ES, Wolk DM, Carr J, et al. Diagnostic accuracy of the Cepheid GeneXpert vanA/vanB assay ver. 1.0 to detect the vanA and vanB vancomycin resistance genes in Enterococcus from perianal specimens. Diagn Microbiol Infect Dis 2011;69:382–389.

353.  Leclercq R. Macrolides, lincosamides, and streptogramins. In: Courvalin P, Leclercq R, Rice LB, eds. Antibiogram. Portland, OR: Eska Publishing, 2010:305–326.

354.  Scott LE, McCarthy K, Gous N, et al. Comparison of Xpert MTB/RIF with other nucleic acid technologies for diagnosing pulmonary tuberculosis in a high HIV prevalence setting: a prospective study. PLoS Med 2011;8:e1001061.

355.  Marme N, Friedrich A, Müller M, et al. Identification of single-point mutations in mycobacterial 16S rRNA sequences by confocal single-molecule fluorescence spectroscopy. Nucleic Acids Res 2006;34:e90.

356.  De Beenhouwer H, Lhiang Z, Jannes G, et al. Rapid detection of rifampicin resistance in sputum and biopsy specimens from tuberculosis patients by PCR and line probe assay. Tuber Lung Dis 1995;76:425–430.

357.  Crudu V, Stratan E, Romancenco E, et al. First evaluation of an improved assay for molecular genetic detection of tuberculosis as well as rifampin and isoniazid resistances. J Clin Microbiol 2012;50:1264–1269.

358.  Espasa M, Gonzalez-Martin J, Alcaide F, et al. Direct detection in clinical samples of multiple gene mutations causing resistance of Mycobacterium tuberculosis to isoniazid and rifampicin using fluorogenic probes. J Antimicrob Chemother 2005;55:860–865.

359.  Blaschitz M, Hasanacevic D, Hufnagl P, et al. Real-time PCR for single-nucleotide polymorphism detection in the 16S rRNA gene as an indicator for extensive drug resistance in Mycobacterium tuberculosisJ Antimicrob Chemother 2011;66:1243–1246.

360.  Vakulenko SB, Donabedian SM, Voskresenskiy AM, et al. Multiplex PCR for detection of aminoglycoside resistance genes in enterococci. Antimicrob Agents Chemother 2003;47:1423–1426.

361.  Schmitz FJ, Fluit AC, Gondolf M, et al. The prevalence of aminoglycoside resistance and corresponding resistance genes in clinical isolates of staphylococci from 19 European hospitals. J Antimicrob Chemother 1999;43:253–259.

362.  Ardic N, Sareyyupoglu B, Ozyurt M, et al. Investigation of aminoglycoside modifying enzyme genes in methicillin-resistant staphylococci. Microbiol Res 2006;161:49–54.

363.  Ida T, Okamoto R, Shimauchi C, et al. Identification of aminoglycoside-modifying enzymes by susceptibility testing: epidemiology of methicillin-resistant Staphylococcus aureus in Japan. J Clin Microbiol 2001;39:3115–3121.

364.  Qu TT, Chen YG, Yu YS, et al. Genotypic diversity and epidemiology of high-level gentamicin resistant Enterococcus in a Chinese hospital. J Infect 2006;52:124–130.

365.  Mahbub Alam M, Kobayashi N, Ishino M, et al. Detection of a novel aph(2”) allele (aph[2”]-Ie) conferring high-level gentamicin resistance and a spectinomycin resistance gene ant(9)-Ia (aad 9) in clinical isolates of enterococci. Microb Drug Resist 2005;11:239–247.

366.  Hauschild T, Vukovic D, Dakic I, et al. Aminoglycoside resistance in members of the Staphylococcus sciuri group. Microb Drug Resist 2007;13:77–84.

367.  Watanabe S, Kobayashi N, Quinones D, et al. Genetic diversity of enterococci harboring the high-level gentamicin resistance gene aac(6’)-Ie-aph(2”)-Ia or aph(2”)-Ie in a Japanese hospital. Microb Drug Resist 2009;15:185–194.

368.  Leelaporn A, Yodkamol K, Waywa D, et al. A novel structure of Tn4001-truncated element, type V, in clinical enterococcal isolates and multiplex PCR for detecting aminoglycoside resistance genes. Int J Antimicrob Agents 2008;31:250–254.

369.  Miro E, Grunbaum F, Gomez L, et al. Characterization of aminoglycoside-modifying enzymes in Enterobacteriaceae clinical strains and characterization of the plasmids implicated in their diffusion. Microb Drug Resist 2013;19:94–99.

370.  Kim JY, Park YJ, Kwon HJ, et al. Occurrence and mechanisms of amikacin resistance and its association with beta-lactamases in Pseudomonas aeruginosa: a Korean nationwide study. J Antimicrob Chemother 2008;62:479–483.

371.  Noppe-Leclercq I, Wallet F, Haentjens S, et al. PCR detection of aminoglycoside resistance genes: a rapid molecular typing method for Acinetobacter baumanniiRes Microbiol 1999;150:317–322.

372.  Akers KS, Chaney C, Barsoumian A, et al. Aminoglycoside resistance and susceptibility testing errors in Acinetobacter baumannii-calcoaceticus complex. J Clin Microbiol 2010;48:1132–1138.

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