MALDI-TOF MS: an upcoming tool for rapid detection of antibiotic resistance in microorganisms

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1 Proteomics Clin. Appl. 2013, 7, DOI /prca REVIEW MALDI-TOF MS: an upcoming tool for rapid detection of antibiotic resistance in microorganisms Markus Kostrzewa 1, Katrin Sparbier 1, Thomas Maier 1 and Sören Schubert 2 1 Bruker Daltonik GmbH, Bremen, Germany 2 Max von Pettenkofer-Institute, Munich, Germany MALDI-TOF MS profiling for microorganism detection has already been demonstrated in the 1990s, but has evolved to the first-line identification method in many laboratories just during the past five years. While this application of MALDI-TOF MS has proven its broad applicability, accuracy, robustness, and cost-effectiveness it is of particular interest to expand the capabilities of the mass spectrometric platform. Resistance detection is the most desirable further application of MALDI-TOF MS in microbiology, but maybe also the most challenging. Different approaches have been published regarding diverse antibiotic drugs and distinct microorganism classes. The current review shall give an overview about the developments of the recent years and their potential to get transformed in clinical useful assays in the future. Received: June 10, 2013 Revised: August 1, 2013 Accepted: August 8, 2013 Keywords: Clinical microbiology / Diagnostic / MALDI-TOF MS / Resistance detection 1 Introduction MALDI-TOF MS profiling for microorganism detection has already been demonstrated in the 1990s [1 3], but has evolved to the first-line identification method in many laboratories just during the past five years. The technique, in combination with adopted software and reference databases, now has become a routine tool for microorganism identification in the microbiology laboratory and is being considered as a revolution in clinical microbiology [4]. Reasons for this rapid success of a technology, which was unknown to most microbiologists less than ten years ago, are its accuracy of identification, speed of analysis, and significant cost-effectiveness [5 7]. Excellent performance data in accuracy of identification has been reported for very diverse groups of microorganisms, including Gram-negative nonfermenting bacteria [8, 9], anaerobes [10 14], yeasts [15 18], fastidious bacteria [19,20], highly Correspondence: Dr. Markus Kostrzewa, Fahrenheitstrasse 4, Bremen, Germany km@bdal.de Fax: Abbreviations: CC, clonal complex; CCI, composite correlation index; CLSI, Clinical and Laboratory Standards Institute; CNS, coagulase negative staphylococci; ESBL, extended spectrum betalactamase; ICMS, intact cell mass spectrometry; MIC, minimal inhibitory concentration; MPCC, minimal profile changing concentration; MRSA, methicillin-resistant Staphylococcus aureus; MSBL, mass spectrometric beta-lactamase; MSSA, methicillin susceptible Staphylococcus aureus; RQ, resistance quotient; VRE, vancomycin-resistant enterococci pathogenic bacteria [21 23], mycobacteria [24, 25], multicellular fungi [26, 27], and even pathogenic algae [28, 29]. Reproducibility and comparability of the method between different instruments and laboratories has been proven [30]. The extension of identification directly from specimen, for example, from urine [31 33] and positive blood cultures [34 36], as well as after short precultivation in liquid media, as shown for Salmonella from stool [37], further have increased the value of the technology for clinical microbiologists. As MALDI-TOF MS microorganism identification now has entered the laboratories with such a revolutionary performance, a demand has come up to broaden its utility in clinical microbiology. Besides typing of microorganisms and toxin detection, two applications which are also just in the infancy of their capabilities, resistance detection is one of the great challenges and opportunities for MALDI-TOF MS as a microbiology platform. The reason for this is not only to use the same platform for a further cost-efficient analysis but in particular the idea that resistance detection can significantly be accelerated, just like the rapid microorganism identification. This review shall give an overview on the potential and restrictions of the technology in this field, first successful implementations, and future directions. 2 MALDI-TOF MS resistance detection 2.1 Genotypic approaches The simplest possibility to use MALDI-TOF MS for resistance detection would be to find characteristic differences in

2 768 M. Kostrzewa et al. Proteomics Clin. Appl. 2013, 7, the spectra of susceptible and resistant strains of a species. As the protein pattern can be envisioned as a reflection of gene sequences encoding the multitude of characteristic protein peaks in the spectrum, this can be called a genotypic approach. Where such a differentiation is possible, the spectra from the identification process might be used directly, on-the-fly, to determine resistance status, in parallel. 2.2 Methicillin-resistant Staphylococcus aureus (MRSA) The studies to investigate the potential of MALDI-TOF MS for resistance detection started with analysis of MRSA and methicillin susceptible Staphylococcus aureus (MSSA) strains one of the biggest challenges for patient treatment and infection control in the recent years. First attempts to differentiate S. aureus in MRSA and MSSA were done by a group from Manchester University [38]. The authors analyzed MALDI- TOF mass spectra of seven strains of MSSA, seven hospital isolates of MRSA that had been typed by PFGE and conventional phage typing, as well as six different species of coagulase negative Staphylococci (CNS) in the mass range from 500 to m/z. The presence and absence of peaks were considered as fingerprints for the particular isolate where most peaks were found in the range m/z. Some peaks were present in all isolates, some were invariably present in, and unique to MRSA or MSSA, and many were unique to individual strains. MSSA strains produced small numbers of peaks (37 67) and MRSA strains produced more (82 209), allowing ready visual discrimination based on the amount of peak numbers. The spectra of the CNS showed interspecies differences, but could be divided into two groups, one with few peaks (30 48) comprising S. epidermidis and S. warneri, and the other with peaks, comprising S. haemolyticus, S. saprophyticus, and S. cohnii. From these preliminary results even a visual discrimination seemed to be possible, the authors claimed that intact cell mass spectrometry (ICMS) spectra might contain data that are relevant at three levels: species identification, typing at a gross level into MRSA or MSSA, and typing even at the fine level attained in PFGE. In a further study the Manchester University group reported the effects of culture media and the intra- and interlaboratory reproducibility of ICMS for identification and subtyping of MRSA [39]. Twenty-six staphylococcal isolates, MRSA (n = 14), MSSA (n = 6), and CNS (n = 6), were included in this study. Altered mass spectra were observed after growth with different cultivation media yielding different mass peaks specific for cultivation media. Such media-derived peaks were mainly in the range of m/z. Spectra from intra- and interlaboratory variation were demonstrated as good with >75% (intra) and >60% (inter) of peaks remaining constant between experiments. The authors claimed the possibility of differentiation between MRSA and MSSA with simple sample preparation and ICMS. Du and coworkers analyzed 76 strains of S. aureus performing data analysis with the MicrobeLynx software (Micromass, UK), with most peaks observed in a mass range from 800 to 3500 m/z [40]. A significant influence of environmental conditions such as temperature or culture media was observed and species identification was gained with low success ( 74%) against the MicrobeLynx database. Strains of S. aureus could be clustered in two separate branches of a dendrogram, presumptive MRSA (43) and MSSA (33). Five of the resistant isolates were not confirmed in reference testing. A further group from Germany [41] reported MALDI- TOF MS differentiation of two well-characterized S. aureus strains, ATCC (MSSA) and ATCC (MRSA), as well as nine clinical isolates. MALDI-TOF mass spectra were recorded in linear as well as reflector mode, within a mass range from 2000 to m/z and from 800 to 4000 m/z,respectively. Consistent strain-specific data were obtained over a period of 3 months and for Mueller Hinton and blood agar, indicating the reliability of the method. A uniform signature profile for MRSA could not be identified; however, bacterial fingerprints were specific for any given strain indicating typing capability of the method. Also Jackson and co-workers presented a standardized method for subtyping applications of ICMS [42]. After developing a standardized method for the analysis of MRSA they were able to differentiate between different strains including EMRSA 15 and 16. The discriminatory power of MALDI-TOF MS for detecting subtle differences was further demonstrated in isogenic (revertant) isolates for two isogenic strains of S. aureus differing in their expression of resistance to methicillin or teicoplanin [43]. More recently, a variation of MALDI-TOF MS, surfaceenhanced laser/desorption ionization (SELDI)-TOF MS, was tested for discrimination of MRSA and MSSA combined with artificial neural network analysis [44]. Seven peaks were defined to calculate MRSA probability. Of 49 MRSA and 50 MSSA strains only two MSSA strains were miss-classified. Up to now, these results could not be reproduced in other laboratories. In contrast, Wolters et al. [45] demonstrated the potential of MALDI-TOF MS as a typing tool in comparison to molecular-derived typing methods like spa typing or PFGE. Using a set of 25 isolates representing the five major MRSA clonal complexes (CC5, CC8, CC22, CC30, and CC45) these could be characterized by 13 characteristic m/z values allowing their robust discrimination. When 60 independent clinical MRSA isolates were tested for the presence or absence of the 13 characteristic MALDI-TOF MS peaks, 15 different profiles ( MALDI-types ) could be detected. Hierarchical clustering of the MALDI types showed high concordance with the clonal complexes. The results suggest that MALDI-TOF MS has the potential to become a valuable first-line tool for inexpensive and rapid typing of MRSA infection control. The results could be confirmed in a second study, which also identified the molecular identity of the peaks characteristic for certain clonal complexes [46]. An indirect MRSA detection

3 Proteomics Clin. Appl. 2013, 7, could be possible by this approach for those clonal MRSA complexes, which show unique peak pattern not existing in any MSSA strain. A study with the aim to identify potential biomarkers for rapid identification of community-associated (CA)-MRSA, hospital-associated MRSA (HA-MRSA), and vancomycinresistant S. aureus isolates by MALDI-TOF did analyze 99 MRSA isolates from an earlier study, newly collected 109 MSSA isolates, and 213 MRSA isolates collected from different patients [47]. It was not possible to distinguish between MSSA and MRSA, but profiles of SCCmec I-III MRSA isolates were different from those of SCCmec IV and V MRSA isolates in the range of m/z. Finally, Szabados et al. tried to differentiate an SCCmec-harboring parent and an SCCmec-lacking daughter strain, with the same genetic background (isogenic) [48]. No differences in the MALDI-TOF MS peak profiles could be found in the range from 2000 to m/z in the MRSA and MSSA strain, all detected peaks in that range are therefore not likely to be associated with the presence of the meca gene. Taken together, after many years of investigation the simple prediction of MRSA based on MALDI-TOF MS profiles seems to be impossible. On the other hand several studies are pointing on the chance to use this technique as a fast typing tool. 2.3 Vancomycin-resistant enterococci (VRE) Recently, Griffin and coworkers have described the detection of VRE in New Zealand using MALDI-TOF MS [49]. Basis of their VRE detection was the creation of a statistical model based on whole bacteria MALDI-TOF mass spectra. Using a support vector machine to describe VRE-specific characteristics in Enterococcus faecium protein profiles, they were able to rapidly and accurately identify vanb positive E. faecium from susceptible isolates directly using the profile spectra of whole cells. Internal cross-validation of the optimal statistical model resulted in a sensitivity of 92.4% and specificity of 85.2%. A subsequent external validation study with other isolates, after incorporation of the algorithm into the routine laboratory workflow, surprisingly showed an even higher sensitivity and specificity of 96.7 and 98.1%, respectively. A further advantage of the MALDI-TOF profiling was the reliable differentiation from other, intrinsically vancomycin-resistant species. Forty-four such intrinsically VRE were analyzed as part of the prospective validation study, without any misidentification as E. faecium. These excellent results did lead to incorporation of the analysis into the authors routine. Although very exciting, the reproducibility of these findings has not been published by other laboratories up to now, so the broad applicability of the method might be questionable. Perhaps the results are reflecting just a favorable epidemiological situation in the authors geographical area, where a typing can differentiate the vanb carrying strains from susceptible ones. This might be not transferable to most other regions. 2.4 Bacteroides fragilis Something near it has recently been shown for an important Gram-negative anaerobic pathogen, B. fragilis. Two groups of this species are described and detectable by various molecular methods, for example, DNA DNA hybridization (division I and division II). These groups can also be differentiated by specific peaks in their MALDI-TOF profile spectra, which are unique for the respective division [50,51]. Only B. fragilis division II harbors the gene cfia encoding a very potent metallobeta-lactamase, an enzyme which can cleave (and thereby inactivate) nearly every beta-lactam antibiotic. Therefore, this group of B. fragilis strains is potentially resistant against the most commonly used antibiotics for Gram-negative bacteria. Although the presence of the cfia gene in the bacterial genome alone is not leading to resistance, as in most cases this gene is not expressed, even susceptible strains can get resistant under antibiotic therapy through the selective pressure and the integration of an insertion element in its promoter. Therefore, the detection of division II in addition to species identification of B. fragilis is very desirable. Wybo et al. [50] could show in a set of 248 well-characterized strains of B. fragilis that both divisions are grouped in distinct clusters in a dendrogram, which was calculated based on their MALDI profile pattern. Nagy and coworkers were able to show that a set of peak shifts can be assigned to division II, which can be used for differentiation of both groups and thereby for the prediction of the cfia gene [51]. Some peak differences of a division I and a division II strain are depicted in Fig. 1. It was possible to create a model for separation of both clusters by these peak shifts and the authors could validate this model with a set of 28 independent strains (9 cfia+,19cfia ) with 100% accuracy. Meanwhile, the algorithm to differentiate both divisions could be validated with the spectra from Wybo and coworkers as well as with further isolates (own unpublished data). Future integration of such an algorithm in the species identification process will be a valuable extension of MALDI-TOF MS capabilities in the clinical microbiology laboratory. This is particularly true as it will enable the identification of B. fragilis with the potential of an importance resistance directly from the spectra acquired for routine identification. 2.5 Functional approaches In contrast to the mass spectrometric approaches described, which are essentially a MALDI-TOF equivalent to genotypic analyses, recent developments used the MALDI-TOF mass spectrometer not to find a characteristic resistance peak pattern in a given strain of a microorganism. Instead, MALDI- TOF MS was applied as a fast monitoring tool for the different effects of an antibiotic to resistant or susceptible strains. Thereby, such methods much more resemble an equivalent to traditional, biochemical resistance tests. The advantage of such MALDI-TOF-based tests compared to the currently

4 770 M. Kostrzewa et al. Proteomics Clin. Appl. 2013, 7, Figure 1. MALDI-TOF profile mass spectra from two B. fragilis strains, one positive for cfia, the other cfia negative. In (A) the overall similarity is obvious, zoomed picture (B) shows some characteristic peak shifts in the region of m/z. established standard methods is the reduction of time-toresult, which may give it any chance to substitute the current tests in the future routine laboratory. The aim of such assays always should be to enable identification and resistance detection in a single day. 2.6 Yeast profiling The first of such phenotypically oriented tests was described for yeast [52]. In their work, Marinach and coworkers incubated yeast cells harvested from solid cultures in a liquid medium containing different concentrations of the frequently used antifungal drug fluconazole. The cultivation in these media was performed for 24 h. Subsequently, the yeast cells were harvested from the medium and MALDI-TOF profile spectra were acquired of cells from each antibiotic level. Comparison of the spectra of the yeast incubated at different antibiotic levels revealed that at a certain concentration the profile spectrum changed significantly (Fig. 2, own unpublished data). The lowest concentration of fluconazole, which induced the spectrum change was called minimal profile changing concentration (MPCC). Surprisingly, the point of profile change did not differ more than one dilution step from the minimal inhibitory concentration (MIC) determined by the Clinical and Laboratory Standards Institute microdilution reference method for all investigated strains. De Carolis et al. did apply the test with slight modifications to other Candida species and also Aspergillus species testing the resistance to the antifungal drug caspofungin [53]. For their data analyses, they did apply the composite correlation index (CCI) analysis, which is part of the MALDI Biotyper software package

5 Proteomics Clin. Appl. 2013, 7, Figure 2. Spectra series (in the pseudo-gel mode) of two strains of Candida albicans after overnight incubation in medium containing different concentrations of the antimycoticum fluconazole. The arrows indicate at which minimal concentration the mass spectra change ( MPCC ), at 16 g/ml for the susceptible strain (Strain 1) and 64 g/ml for the resistant strain (Strain 2), respectively. (Bruker Daltonics, Bremen, Germany). For this, they calculated a correlation matrix based on the mass spectra acquired from the yeast cells after incubation in different caspofungin concentrations. After matching of each concentration and its spectrum against each of the two extreme concentrations (zero or maximum) of caspofungin, the MPCC was assessed as the CCI value, at which a spectrum is more similar to the one observed at the maximum caspofungin concentration (maximum CCI) than the spectrum observed at the zero caspofungin concentration (null CCI). Although this was a first important step toward a real functional MALDI-TOF MS resistance test, the drawback of the reported method was that still an overnight incubation was necessary, so no acceleration in time-to-result was achieved. Recently, however, Vella and coworkers demonstrated that this approach can be significantly accelerated [54]. In their version of the assay they had set up a kind of breakpoint analysis with only 3 h of incubation time, incubating the yeast cells in three concentrations of antifungal drug, only: no antifungal, breakpoint concentration, maximum concentration, respectively. The decision about resistance was concluded by the comparison of the spectra at the breakpoint with those of the zero and the maximum concentration: if the spectrum was more similar to the spectrum from yeast after incubation without antifungal drug the strain was considered as susceptible, if it was more similar to the maximum concentration derived spectrum the strain was called resistant. The bioinformatics analysis again was done using the correlation analysis. Comparison with standard laboratory methods did give good correlation of results. The speed of analysis shown in these experiments and automated data interpretation, which could be applied suggest that such a test could indeed be introduced into clinical microbiology laboratories. However, reproducibility and robustness of this method still have to be proven. 2.7 Beta-lactamase testing A very different approach to the MALDI-TOF MS assays described is the recently developed mass spectrometric betalactamase (MSBL) assay [55 57]. In contrast to other approaches for resistance detection, this represents a functional assay based on the direct monitoring of the enzymatic activity of the beta-lactamase. Beta-lactam antibiotics are inactivated by hydrolysis of the central beta-lactam ring by specific, hydrolyzing beta-lactamases synthesized by resistant microorganism. Enzymatic cleavage of the beta-lactam ring is characterized by addition of a water residue, resulting in an increase of the molecular weight of the antibiotic by plus 18 Da. This mass shift can easily be monitored by MALDI- TOF MS. Beta-lactamase negative strains do not change the molecular weight of the beta-lactam antibiotic (Fig. 3). Compared to all other routine procedures this approach rapidly provides a result, as the readout is based on an enzymatic activity and not on bacterial growth requiring longer incubation times even for fast growing microorganisms [58, 59]. For most beta-lactamases, activity can already be observed after 1 2 h. Exceptions are OXA-48 beta-lactamases owing a slower hydrolysis rate, which in most cases can only be detected after 3 4 h of incubation (own unpublished data). The evaluation of the MSBL assay is quite simple. The expected masses for the nonhydrolyzed and the hydrolyzed forms of the different antibiotics are known to lead to a

6 772 M. Kostrzewa et al. Proteomics Clin. Appl. 2013, 7, Figure 3. MALDI-TOF mass spectra of ampicillin after incubation for 3 h in the presence of an E. coli without ß-lactamase activity (A) and of a ß-lactamase producing E. coli strain (B). In (A) after 3 h still the uncleaved ampicillin molecules (350.1, for sodium adduct, for adduct with two sodiums) are visible and virtually no cleavage products. In (B) the educt is gone and the hydrolysis product and its adducts can be observed (368.1, 390.1, 412.1), further the peak corresponding to the decarboxylation product of the hydrolyzed molecule (324.2 is more prominent). characteristic peak pattern for beta-lactamase active and inactive strains, respectively. The different peak pattern facilitates a qualitative differentiation between the two classes. A direct comparison of peak intensities from different mass spectra for a quantitative evaluation is not feasible as MALDI-TOF MS acquires only relative intensities. Only intensities within the same spectrum can be compared. Since the hydrolysis reaction is characterized by the decrease of the peaks corresponding to the nonhydrolyzed form and an increase of the peaks corresponding to the hydrolyzed form, the change of the ratio of these peak intensities within the same spectrum can be employed for a quantitative evaluation. Calculation of the ratio of the sum of the peak intensities corresponding to the hydrolyzed form and the sum of the peak intensities corresponding to the nonhydrolyzed form resulted in the resistance quotient (RQ), which is a measure of the hydrolysis activity. The RQ can comprise several orders of magnitude. To get a clear representation the logarithm of the RQ is calculated and used for evaluations. The quantitative analysis of the hydrolysis reaction facilitates assay optimization, reproducibility studies, kinetic studies, and direct comparison with MIC values. Software tools automatically calculating log RQ values are under development. Different antibiotics have been analyzed with the MSBL assay [56]. Each antibiotic represented its own peak pattern. For the two carbapenems meropenem and imipenem, it was impossible to detect the classical hydrolysis pattern of +18 Da compared to intact antibiotic and 44 Da compared to the hydrolyzed antibiotic with the standard MALDI matrix alphacyano-4-hydroxycinnamic acid [56,60]. Kempf et al. described a metabolite of imipenem corresponding to the elimination of carbon dioxide and water after hydrolysis resulting in a mass shift of 44 Da compared to the intact antibiotic [61]. For meropenem, only the decrease of the peaks corresponding to the intact antibiotic could be observed with CHCA. As shown by Hrabák and coworkers, the 2,5-dihydroxybenzoic acid (DHB) as matrix facilitates the detection of the hydrolysis products of meropenem [55, 62]. For imipenem, the use of DHB has not yet been tested. The DHB as matrix usually forms heterogeneous preparations complicating automated spectra acquisition [63]. Therefore, this matrix is not preferred for automated workflows. All investigated antibiotics tend to accumulate sodium, resulting in adduct peaks with a characteristic peak shift of +22 Da. For all antibiotics except of piperacillin the hydrolyzed beta-lactam ring is labile resulting in a spontaneous elimination of carbon dioxide represented by a mass shift of 44 Da. In the case of ertapenem, this peak corresponding to the hydrolyzed, decarboxylated form is already detectable in freshly prepared solutions. Additionally, ertapenem accumulates potassium resulting in more complex peak pattern compared to other antibiotics. All of the so far analyzed cephalosporins were instable under MALDI- TOF MS conditions and eliminate specific side groups. Accordingly, the characteristic hydrolysis pattern of +18 Da and 44 Da is found in the lower mass range. The setup of the MSBL assay allows for implementation of inhibition approaches [56, 64], which are commonly used in routine diagnostics; for example, execution of classical extended spectrum beta-lactamase (ESBL) confirmation tests with tazobactam or clavulanic acid [65], the detection of metallo-beta-lactamases by inhibition with EDTA (own unpublished data) or dipicolinic acid [59], and the detection of

7 Proteomics Clin. Appl. 2013, 7, AmpC and Klebsiella pneumoniae carbapenemase (KPC) betalactamases by inhibition with boronic acid derivatives [66 68]. Additionally, the MSBL assay can directly be performed with bacteria derived from freshly tagged positive blood cultures [56]. Bacterial cells are isolated by a series of lysis and washing steps to remove blood cells and other blood components and subsequently are directly used for the MSBL assay. Usually, a result is available 2 3 h after the blood culture has been flagged positive. Standard routine assays need an overnight incubation and even for fast growing microorganisms automated routine systems require at least 5 h until a result can be obtained [59]. Especially in the context of blood culture analytics, the combination of quick mass spectrometric identification of the infection causing species [30, 69] and the rapid MSBL assay provides valuable information to start an early therapy. Limitation of the MSBL assay is the detection of betalactamase activity in the presence of alternative resistance mechanisms. Porin defects and specific efflux pumps commonly observed in Pseudomonas spp. and Acinetobacter spp. prevent the interaction between beta-lactamase and antibiotic drug [70 72]. This leads to reduced or even missing hydrolysis of the beta-lactam antibiotic. To overcome this problem, Hrabák and coworkers added sodium dodecyl sulfate at a concentration of 0.1% to the incubation set up [62]. This detergent perforates the outer cell membrane and makes it permeable for the antibiotics independently of any porins or efflux pumps facilitating the direct interaction between beta-lactamase and antibiotic. Another possibility to avoid this problem is working with completely lysed cells. Hooff and coworkers had established a protocol for detection of beta-lactamase activity based on cells disrupted by sequential freeze/thaw cycles [64]. This is a very time-consuming procedure not applicable in any routine workflow. Further development of the lysis protocol resulted in the use of the detergent mixture, which Poirel and coworkers employed for their photometric beta-lactamase assay (personal communication, [73]). By this protocol the bacterial cells are completely destroyed and the beta-lactamase is released into the supernatant providing unhindered hydrolysis of the antibiotic. The applicability of the MALDI-TOF MS-based detection of hydrolysis activity has been shown for different betalactam antibiotics, like penicillin, ampicillin, piperacillin, cephalosporin (ceftazidime, cefotaxime), and carbapenems (ertapenem, meropenem, and imipenem). The list of investigated organisms comprises E. coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, Citrobacter freundii, Enterobacter cloacae, andsalmonella spp. Different types of beta-lactamases have been successfully analyzed including TEM, ESBL, AmpC, Klebsiella pneumoniae carbapenemase, OXA-type, NDM, and VIM beta-lactamases. In all cases, the detection of beta-lactamase activity was in concordance with the expected results. In addition, the MSBL assay was also applied to detect carbapenem resistance in B. fragilis. The cfia is a class B metallo-beta-lactamase hydrolyzing ertapenem. Beta-lactamase activity was detected in cfia-positive strains but not in cfia-negative strains. Hydrolysis was inhibited in the presence of dipicolinic acid (ep682, ECCMID 2013). Different readouts have been employed to analyze the MSBL assay. Hooff and coworkers applied MALDI-TOF MS as well as MALDI triple quadrupole (QqQ) MS as readout for their data [64]. Both analytical approaches revealed similar results. MALDI QqQ was preferred in terms of quantitative analysis. Grundt and coworkers employed LC/MS in combination with an HCT Ultra mass spectrometer with an ESI interface. This analytical set up provides higher sensitivity and facilitates quantitative evaluations [74]. Summarized, the MSBL assay is a powerful tool allowing for a fast and reliable detection of beta-lactamase activity. In most cases, a qualitative evaluation of the results on the spectrum level is possible without any additional software. Of course, this procedure is more time-consuming than software-based automated evaluations and needs some expert knowledge in MS. Therefore, automated interpretation software is urgently needed. Of course, this test will have to compete with other rapid methods like the Carba NP test [75]. In contrast to the Carba NP test, the MSBL assay is applicable for the detection of carbapenemase activity, the MSBL assay can be employed for the detection of different beta-lactamases in combination with different beta-lactam antibiotics. The field of application for the MSBL assay is manifold comprising screening for hygiene management in hospitals and rapid monitoring for beta-lactamase activity in clinical isolates. Additionally, the MSBL assay supports scientific investigations according to the behavior of different beta-lactamases and their kinetic properties. These might reveal important information with respect to the use of different antibiotics in certain clinical settings. Nevertheless, the MSBL assay might also be interesting for the pharmaceutical industry. The short analysis time might accelerate development of new antibiotics against beta-lactamase-resistant microorganisms. 2.8 Aminoglycosides Resistance against aminoglycosides can be based on different mechanisms, like changed cell permeability, altered binding sites of the antibiotic on the ribosome, and inactivation of the antibiotic by modification of the antibiotic, respectively [76]. Similar to the main resistance mechanism against beta-lactam antibiotics, the main resistance mechanism against aminoglycoside is also based on the enzymatic modification of the antibiotic [77]. For aminoglycosides, inactivation can be performed by different enzymatic reactions comprising modification by acyltransferase, phosphotransferases, and nucleotidyltransferases. The mainly occurring mechanism is the inactivation by acyltranferases. These transferase reactions are more complex than hydrolysis reactions, because additional cofactors are required for activity. These cofactors comprise ATP, acetyl-coa, NAD +,UDP glucose, or glutathione. Acylation can affect hydroxyl and/or

8 774 M. Kostrzewa et al. Proteomics Clin. Appl. 2013, 7, Figure 4. Profile mass spectra in the mass range of approximately m/z of two K. pneumoniae strains, shown in the pseudo-gel mode, one susceptible for, the other resistant against Meropenem. Each strain was incubated in three different media: normal (Normal), with isotopically labeled lysin (Heavy), and with isotopically labeled lysin plus meropenem (Heavy/AB). While for the susceptible strain the Heavy/AB spectrum still is very similar to the Normal spectrum, in the case of the resistant strain it is nearly identical to the Heavy spectrum. amine groups on the antibiotic. This further complicates the evaluation. Green and coworkers tested the influence of the addition of different acyl-coas on the modification of different aminoglycosides [78]. The acyltransferases show different preferences of the CoA substrate for the modification of different aminoglycosides. Several attempts have been performed to establish an equal mass spectrometric-based assay for the detection of resistance against aminoglycosides (personal communication S. Schubert and J. Jung). Gentamicin as the natural member of the aminoglycosides was not suitable for this assay, because the substance is a mixture of different molecules varying in different side chains. Mass spectrometric detection of the modification reaction had been shown for tobramycin, kanamycin, and neomycin [79]. Still, the reproducibility of this approach is insufficient for employing it in any routine context. Further development and standardization will be necessary. 2.9 Stable isotope labeling In a very recent study, Demirev et al. have described experiments to detect resistance of bacteria by the incorporation of stable isotope-labeled nutrients during continued growth in a broth with antibiotic [80]. For their assay they did grow intact microorganisms in drug-containing stable isotope-labeled media and acquired mass spectra from these microorganisms. These spectra were compared with mass spectra of the intact microorganism grown in nonlabeled media without the drug present. Drug resistance was detected by characteristic mass shifts of one or more biomarker peaks. As isotope-labeled medium they did choose 13 C-labeled medium. In this commercially available medium, 98% of the C-atoms are 13 C, which in nature only occurs at about 1%. Therefore, the incorporation of 13 C-labeled compounds from the medium into a bacterial macromolecule, for example, protein, leads to a mass shift. The growth of bacteria in a medium in the presence of an antibiotic is the evidence of its resistance against this drug. This evidence is given by the peak shifts caused by the 13 C incorporation into the biomarkers. In practice not all antibiotics might cause a sudden stop of protein synthesis in susceptible bacteria. Thus, an alternative is proposed by Demirev and coworkers. For this, the bacterium is grown in three different media: normal, isotope labeled, and isotope labeled plus antibiotic. The mass spectra derived from such an experiment are shown in Fig. 4 where a susceptible and a resistant strain of K. pneumoniae were incubated in normal medium, medium with isotopelabeled lysin ( 13 C 6 15 N 2 -L-lysine, Fisher Scientific, Germany), and labeled medium with meropenem (Sparbier et al., unpublished results). In this case only one amino acid was used as a labeled media compound, making the assay much more cost-effective. After 2 h of incubation, the spectrum acquired from the resistant bacterium in the labeled medium with antibiotic is nearly identical to the spectrum from the organism grown in labeled medium without meropenem. In contrast, as the growth and thereby protein synthesis of the susceptible strain is inhibited, its spectrum after incubation in the labeled and antibiotic-containing medium is still similar to the normal spectrum, although some additional peaks can be detected. This assay format has already been successfully tested for different species and antibiotics (own unpublished

9 Proteomics Clin. Appl. 2013, 7, results) and might be the first broad applicable resistance test using MALDI-TOF MS Outlook The detection of antibiotic resistances in bacteria is a hallmark of clinical microbiological diagnostic. Though timeconsuming, culture-based methods for antibiotic resistance testing are still the gold standard in diagnostic laboratories around the world. The introduction of MALDI-TOF MS in medical microbiology has yet tremendously changed the way of identifying bacteria and fungi. Now, the first steps are being made to exploit MALDI-TOF MS for a fast detection of antibiotic and antimycotic resistances. These results are very promising and will encourage a further agile development of this technique. The future work will have to answer several questions. These regard the correlation of MALDI-TOF results with determined MIC values and breakpoints currently used in resistance testing. Ideally, studies will have to prove the impact of the MALDI-TOF MS results on the appropriate treatment and the clinical course of infection. As soon as these issues are addressed and the MALDI-TOF resistance testing is automated and tailored for easy and parallel testing of multiple antibiotics, this novel method is going to be a serious competitor for classical antibiotic resistance testing. The authors have declared the following potential conflict of interest: M. Kostrzewa, K. Sparbier, and T. Maier are employees of Bruker Daltonik GmbH, the manufacturer of an MS system used in clinical microbiology laboratories. 3 References [1] Holland, R. D., Wilkes, J. G., Rafii, F., Sutherland, J. B. et al., Rapid identification of intact whole bacteria based on spectral patterns using matrix-assisted laser desorption/ionization with time-of-flight mass spectrometry. Rapid Commun. Mass Spectrom. RCM 1996, 10, [2] Claydon, M. A., Davey, S. N., Edwards-Jones, V., Gordon, D. 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