MALDI Biotyper based rapid resistance detection by stable isotope

Transcription

1 JCM Accepts, published online ahead of print on 4 September 2013 J. Clin. Microbiol. doi: /jcm Copyright 2013, American Society for Microbiology. All Rights Reserved. 1 2 MALDI Biotyper based rapid resistance detection by stable isotope labeling Katrin Sparbier 1, Christoph Lange 1, Jette Jung 2, Andreas Wieser 2, Sören Schubert 2, Markus Kostrzewa 1 1 BrukerDaltonik GmbH, Bremen, Germany 2 Max von Pettenkofer-Institut, Ludwig-Maximilians-Universität, Munich, Germany Running title: MALDI-TOF resistance profiling Keywords: MALDI-TOF MS, stable isotope labeling, resistance, Staphylococcus aureus, Oxacillin Corresponding author: Markus Kostrzewa BrukerDaltonik GmbH Fahrenheitstr Bremen 19 Germany 20 Tel.: * Fax: *

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3 23 Abstract Against the background of increasing numbers of resistant microorganisms the fast and costefficient detection of microbial resistance is an important clinical requirement for optimal therapeutic intervention. Current routine assays take at least 5 h but in most cases an overnight incubation is necessary to identify resistant isolates. The usage of MALDI-TOF MS profiling in combination with growth media containing isotopically labeled amino acids facilitates the detection of resistant microorganisms already after 3 h or less directly from the profile spectrum. Growing microorganisms incorporate isotopically labeled amino acids, increasing protein masses and thereby leading to mass shifts of their corresponding peaks in profile spectra. In the presence of antibiotics only resistant microorganisms are able to grow and to incorporate the labeled amino acids. This leads to a difference in the mass spectra of susceptible and resistant isolates allowing for their differentiation. In the presented study, we demonstrated the applicability of this novel approach for the detection of methicillin resistant Staphylococcus aureus and tested different bioinformatics approaches for automated data interpretation.

4 42 Introduction The intensive use of antibiotic drugs leads to an increasing number of microorganisms resistant against these antibiotics. Only the specific and restricted use of antibiotics can help to curtail this problem (1). An important prerequisite for the correct choice of the therapeutic intervention is the rapid detection of resistant strains. Common routine methods are based either on automated microbiology systems such as Phoenix (BD Diagnostic Systems, Heidelberg, Germany), MicroScan (Siemens Healthcare Diagnostics GmbH, Eschborn, Germany ) or Vitek 2 (biomérieux, Nürtingen, Germany) (2),(3), which determine the MIC by monitoring the growth of bacteria and are able to provide results after about 5 h for rapid growing organisms, or on agar diffusion assays generally requiring an overnight incubation. Recently, Matrix-assisted laser-desorption/ionization mass spectrometry(maldi-tof MS) has become a routine method in microbiology laboratories for the identification of microorganism (4 6). For example, the comparison of a profile spectrum acquired from a microorganism with profile signatures stored in a respective reference library allows for the quick and reliable species determination (MALDI Biotyper system, Bruker Daltonik GmbH, Germany). Additionally, MALDI-TOF MS has recently been applied for the detection of ß- lactamase activity providing resistance against ß-lactam antibiotics in gram-negative microorganisms (7 9). This approach, which is a first promising step towards MALDI-TOF resistance detection, monitors the hydrolysis of the respective antibiotic in the presence of the bacteria to be tested. Thereby, it delivers a classification of bacteria according to their ß- lactamase hydrolysis activity within 2 3h (7 9). Unfortunately, this assay is only applicable to detect resistance against ß-lactam antibiotics and in addition, negative results cannot definitely be interpreted as susceptible for all bacteria. Alternative resistance mechanisms might hide the ß-lactamase activity. On the other hand it can be a rapid and cost-effective tool for observation of the spread of ß-lactamase carrying bacteria in hygiene monitoring, e.g. for KPC (Klebsiella pneumoniae carbapenemase).

5 To overcome the restriction of detection of only a single resistance mechanism and to extend mass spectrometric resistance testing also to other than ß-lactam antibiotics, a novel approach was established. This approach is based on the knowledge that growing cells perform protein biosynthesis. The exchange of naturally occurring amino acids with their nonradioactive isotopically labeled versions in a growth medium leads to the incorporation of these heavy amino acids into the newly synthesized proteins. This results in mass shifts of the peaks in the profile mass spectrum of a microorganism. During incubation of bacteria in the presence of antibiotics, resistant strains are still able to grow and to newly synthesize heavy proteins. These proteins are detectable as characteristic peak shifts in the profile spectrum. Susceptible strains do not or only slowly grow under such conditions, resulting in a profile spectrum most similar to the normal profile spectrum of these strains. Thereby, the changes in the profile spectrum should function as indicator for the discrimination between susceptible and resistant strains. In this paper, the novel MALDI-TOF MS based resistance test with stable isotopes (MS- RESIST) is described and its applicability for the classification of Methicillin susceptible Staphylococcus aureus (MSSA) and Methicillin resistant Staphylococcus aureus (MRSA) as model system is demonstrated. First approaches to a bioinformatics data interpretation are shown. Material and methods Bacterial strains and cultivation Clinical isolates of Staphylococcus aureus (Max von Pettenkofer-Institute, Munich, Germany) previously classified by standard routine methods as MRSA and MSSA strains were employed as positive and negative samples (10 negative and 10 positive strains), respectively. MRSA strains were characterized as non-borsa strains by detecting the meca gene and phenotypically a resistance against cefoxitin. Twenty-eight further clinical isolates

6 of Staphylococcus aureus were obtained from the Praxis für Laboratoriumsmedizin, Ärztliche Gemeinschaft für Diagnostik Köln Bonn, Germany. These were used blinded during the analysis. The molecular characterization is given in the supplementary material. Bacteria were cultivated on Columbia blood agar plates (BD, Germany) without selective agents over night at 37 C. Fresh overnight cultures were employed for the tests Resistance profiling assay Dulbecco s modified Eagle medium with low glucose and without lysine, arginine, and leucine (Sigma Aldrich, Germany) was supplemented with all proteinogenic amino acids (Sigma Aldrich, Germany) except of lysine at a concentration of 0.3 g/l, with sodium chloride (4%, Sigma Aldrich, Germany), 4 g/l glucose (Sigma Aldrich, Germany), and 60 mg/l iron- (II) chloride (Sigma Aldrich, Germany). For each strain, three different 100 µl-setups were prepared: normal containing 0.1 g/l normal lysine (Sigma-Aldrich, Germany), heavy containing 0.1 g/l 13 C 15 6 N 2 -L-lysine (Fisher Scientific, Germany), and heavy + Oxa containing 0.1 g/l 13 C 15 6 N 2 -L-lysine and 60 mg/l Oxacillin (Sigma-Aldrich, Germany), respectively. Each medium preparation was inoculated with bacteria of the same strain at a final cell concentration of 3.5x10 6 cells per ml. The bacterial suspensions were incubated at 37 C under agitation in a thermomixer (Eppendorf, Germany) for three hours. After incubation, the cells were centrifuged and washed with 150 µl pure water. Subsequently, bacteria were lysed with 10 µl 70% formic acid and 10 µl of 100 % acetonitrile according to the MALDI Biotyper standard extraction protocol for bacterial profiling (10). Similar experiments were performed with 40 mg/l cefoxitin (Sigma-Aldrich, Germany) instead of Oxacillin. 116 MALDI-TOF MS analysis One µl of the cell-free lysates was directly spotted onto a polished steel MALDI target plate. Each lysate was spotted four times. Dried spots were overlaid with MALDI matrix (α-hcca, 10mg/mL of α-cyano-4-hydroxy-cinnamic acid in 50% acetonitrile/2.5% trifluoroacetic acid; BrukerDaltonik, Bremen). After drying of the matrix, MALDI-TOF MS measurements were

7 performed with a microflex LT/SH bench-top mass spectrometer (BrukerDaltonik GmbH, Bremen) equipped with a 60 Hz nitrogen laser. Parameter settings had been optimized for the mass range between ,000 Da (parameter settings: ion source 1 (IS1), 20 kv; IS2, 17.5 kv; lens, 6.5 kv; detector gain, 7.4 V; and gating: none). Spectra were recorded in the positive linear mode with the maximum laser frequency. An external standard (Bacterial test standard (BTS), Bruker Daltonik GmbH, Bremen) was used for instrument calibration. Data evaluation Different data evaluation procedures were applied. First, spectra were visually compared to search for peak shifts using flexanalysis 3.4 (Bruker Daltonik GmbH, Bremen) and ClinProTools 3.0 (Bruker Daltonik GmbH, Germany). Additionally, automated spectra analysis was performed with the MALDI Biotyper 3.1 software (Bruker Daltonik GmbH, Bremen) using the integrated calculation of the correlation index matrix applying the standard settings of the software considering the mass range between 3,000 to 12,000 Da (correlation analysis). Strains comprising a correlation index for the normal spectra versus the heavy + antibiotic spectra similar or below 0.6 were classified as resistant. Heavy spectra served as a control for growth. For alternative automated evaluation approaches, specific peaks were chosen for normal and heavy peaks. The sums of their intensities were changing their ratio during growth in the presence of isotopically labeled amino acids. The following masses were chosen as normal peaks: , , , , , , , , and Da. The following masses additionally found in the heavy spectra were chosen as heavy peaks: , , , , , , , , , , and Da. The ratio of the summarized peak intensities of the heavy peaks and the summarized peak intensities of the normal peaks was calculated (ratio H/N). This ratio directly correlates with the incorporation of heavy amino acids (incorporation analysis). The four different results of each spectra group were displayed in a box plot indicating the median by the bold line, the minimum and the maximum by the whiskers, and the 25th and

8 th percentiles by the box. The incorporation analysis resulted in three different ratios (H/N) for each strain according to each medium, respectively Considering the ratios of the heavy + antibiotic spectra of the incorporation analysis revealed values similar or greater than 1.0 for resistant strains. For an additional evaluation procedure, the ratios of the incorporation analysis of the heavy spectra and the heavy + antibiotic spectra were subtracted and subsequently divided by the ratio (H/N) of the heavy spectra. This resulted in the normalized difference. Again, these results were displayed in a box plot. Strains with a normalized difference similar or below 0.5 were classified as resistant. The calculations of the incorporation analysis and the normalized duifference were performed with a software tool written in the freely available software package R (11), (12). All threshold values were empirically set and might be adapted when larger sample numbers will have been analyzed. Routine susceptibility testing of isolates for comparison The minimal inhibitory concentration (MIC) against Oxacillin and Cefoxitin were determined employing the Epsilometer test. Briefly, MIC Test Strips (Liofilchem, Italy) were placed on 85 mm Mueller Hinton agar plates (BD Diagnostics Systems), which had been inoculated with a 0.5 McFarland standard suspension of test isolates. All plates were incubated at 37 C for 20 to 24 h before being examined. The MIC was determined to be the value at which the elliptical growth margin intersected the MIC Test strip. The evaluation of resistance status was performed according to the current CLSI guideline CLSI M100-S21 aerobic bacteria Results 171 Principle of the assay

9 In first experiments, the principle of the mass spectrometric resistance test with stable isotopes (MS-RESIST) assay was investigated. Four known MSSA and four known MRSA strains were incubated for 3h under the above described conditions. Each strain was incubated with normal amino acids ( normal ), with isotopically labeled amino acids ( heavy ), and with isotopically labeled amino acids plus antibiotics ( heavy + Oxa ) for 3 h, respectively. After washing and lysing of the cells, MALDI-TOF MS spectra were acquired. The subsequent spectra analysis revealed clear differences in the three spectrum sets. Figure 1 shows a zoom of representative single spectra shown in Flexanalysis (A, B) and the pseudo-gel views in ClinProTools (C, D) of the three different setups ( normal, heavy, heavy + Oxa ) for one of the susceptible strains (A, C) and one of the resistant strains (B, D), respectively. For both strains the heavy spectra contain additional peaks not detectable in the normal spectra (Fig. 1A, 1B, boxes). In addition, peaks present in the normal spectra are reduced in intensity or even absent in the heavy spectra (Fig. 1A, 1B, grey underlay). Analyzing the heavy + Oxa spectra, revealed differences in the relative peak intensities of heavy to normal peaks between the susceptible and the resistant strains. The heavy + Oxa spectrum of the resistant strain is nearly identical to the corresponding heavy spectrum. This is an indication of growth and protein biosynthesis virtually not affected by the antibiotic. In contrast, the heavy+oxa spectra of the susceptible strains were more similar to the normal spectra than to the heavy spectra. This indicates a clearly reduced protein synthesis through the antibiotic action. The ratio of the peak intensities of the normal to the heavy peaks was quite different in the heavy + Oxa spectrum of the susceptible strain. The normal peaks in the heavy + Oxa spectrum were relatively increased compared to the normal peaks in the heavy spectrum and the heavy peaks were decreased compared to the heavy peaks in the heavy spectrum. The display of the spectra in ClinProTools (Fig. 1C, 1D) allows for a direct comparison of the peak intensities because this software normalizes spectra to the total ion count. Additionally, the variance between the different spectra belonging to one set can be easily monitored. In this view, the peaks are displayed as bands and the peak intensities are given as grey scale. The

10 comparison between the normal and the heavy spectra shows the maximum change in the peak pattern which resulted from the incorporation of heavy amino acids by growing cells. As expected, no significant differences can be found between the susceptible and the resistant strain. In contrast, the heavy + Oxa spectra exhibit a different pattern for a susceptible and a resistant strain. In case of the resistant strain (Fig. 1D), the heavy + Oxa spectra look very similar to the heavy spectra. On the other hand, the heavy + Oxa spectra of the susceptible strain (Fig. 1C) show their individual peak pattern, still similar to the normal spectra. In the heavy + Oxa spectra, normal peaks are more intense than the respective peaks in the heavy spectra. In contrast, peaks resulting from the incorporation of heavy amino acids are considerably reduced in their intensities compared to the respective peak intensities of the heavy spectra. The observed relative changes of the peak intensities in the heavy + Oxa spectra compared to the heavy spectra correlated with the reduced growth of the susceptible strains in the presence of the antibiotic and could be used as a measure for the discrimination between susceptible and resistant strains. Using Cefoxitin instead of Oxacillin led to similar results. Figure 2 represents single spectra displayed in FlexAnalysis (A,B) and the pseudo-gel views displayed in ClinProTools (C,D) of a susceptible and a resistant strain. Changes in peak pattern result in reduced spectra similarity which can be calculated by correlation analysis and displayed in a composite correlation index matrix (CCI matrix). Correlation analysis is an established method to compare spectra similarities. Figure 3 shows the CCI matrices of the susceptible (A) and the resistant (B) Staphylococcus aureus strains analyzed before. For the susceptible strain, a correlation index of about 0.7 was calculated for the correlation between the heavy versus the heavy + Oxa spectra (Fig. 3A). A similar index was calculated for the correlation of normal versus heavy + Oxa spectra. This means, that the heavy + Oxa spectra represent similarity to the normal spectra as well as to the heavy spectra. The heavy + Oxa spectra seem to represent the average spectrum of the normal and the heavy spectra. This result was in concordance with the visual analysis using flexanalysis and ClinProTools. For the resistant strain (Fig.

11 B), the correlation indices were quite different. The correlation between the heavy versus heavy + Oxa spectra was very strong, represented by a correlation index above 0.9. In contrast, the correlation between the heavy + Oxa and the normal spectra was quite poor, indicated by a correlation index below 0.6. Again, these results were in good concordance to the visual analysis in flexanalysis and ClinProTools Further bioinformatic methods were developed in order to get defined values which allow for a direct comparison of different strains and thereby, with the results from routine analyses. The incorporation analysis resulted in three different quotients for each strain (A corresponding figure is shown in the supplementary material, Fig. S1). The ratio (H/N) for the normal spectra was near to zero for all different strains because no heavy peaks were present in the spectra derived from growth in normal culture medium. The ratio (H/N) of the heavy spectra was a measure for the maximal incorporation of isotopically labeled amino acids and thereby an important control for the growth of the strains. This value differed somewhat for each of the strains regardless of the resistance status. The ratio (H/N) for heavy + Oxa spectra revealed clear differences for the susceptible and the resistant strains, respectively.the ratios (H/N) were below 1.0 for all susceptible strains. In contrast, the incorporation analysis of the heavy + Oxa spectra of the resistant strains revealed values in the same range as the values of heavy spectra and clearly exceeded 1.0. In the next step, the normalized differences were calculated for each strain (a respective figure is shown in the supplementary materialand Fig. S2). Again, a clear separation between the susceptible and the resistant strains was observed. All susceptible strains revealed a normalized difference above 0.5 and the resistant strains showed normalized differences below Day-to-day reproducibility The reproducibility of the mass spectrometric analysis was investigated by analyzing four strains comprising two susceptible and two resistant strains, respectively, on three different days. The visual inspection of the resulting spectra allowed for a correct classification of the

12 strains according to resistance or susceptibility for all replicates and every day. For an automated classification, the spectra sets were analyzed with the three different evaluation approaches (Fig. 4). Calculation of the correlation index of the heavy + Oxa spectra versus the normal spectra revealed only one misclassification. The detailed analysis on the spectra level showed that these spectra comprise a stronger noise compared to other spectra. This reduced the similarity to all other spectra, the heavy and the normal spectra. All other results were in agreement with the expected results (Fig 4A). The incorporation analysis of the heavy + Oxa spectra was in agreement with the expected classification (Fig. 4B). Only for one of the resistant strains, the achieved classification did not agree with the expected one on day three. The detailed analysis of this strain revealed that the ratios (H/N) of the heavy and the heavy + Oxa spectra were both in the same range but relatively low. This means that the growth of this strain was poor on day three. The calculation of the normalized difference revealed complete concordance with the expected classification for all strains on all analysis days (Fig. 4C). Analysis of routine samples In the following, the novel approach was applied to routine samples of Staphylococcus aureus and the outcome was compared to the results of the MIC determination. In total, 28 strains were analyzed. Table 1 lists the results of the routine testing and the results of the MALDI-TOF MS analyses for Oxacillin and Cefoxitin, respectively. For all spectra sets, the three different evaluation procedures were performed. The results of the automated evaluations (correlation analysis, incorporation analysis of heavy + antibiotic spectra, and calculation of the normalized differences) of the mass spectra were mostly in accordance to the routine results. For strain 260, the calculation of the normalized differences resulted in values which were below the threshold values for susceptible strains resulting in the classification resistant, although this strain was classified by other approaches and the routine method as susceptible. The detailed analysis of the underlying incorporation

13 analysis revealed a very low value for the heavy spectra meaning a very poor growth of this strain. The correlation analysis of the cefoxitin approaches resulted in three cases in a misclassification. The detailed visual inspection of the spectra revealed increased noise in the underlying spectra resulting in decreased similarity to the corresponding normal spectra. All other strains were classified in concordance to the different evaluation procedures for the mass spectrometric data and to the routine results, with all applied bioinformatics algorithms. Discussion The principle of the new approach for resistance detection is based on the incorporation of non-radioactive isotopically labeled amino acids into newly synthesized proteins during growth of cells. The isotopically modified proteins lead to an increased molecular weight of the peptides and proteins detectable by a mass shift in the MALDI-TOF profile spectra. In the presence of antibiotics only resistant cell are able to grow and to perform protein biosynthesis. Susceptible strains stop growing under antibiotic stress and thereby present different profile spectra compared to the setups without antibiotics. Recently, a comparable approach has been published by Demirev et. al.(13). In contrast to this study, they employed completely 13 C labeled culture medium resulting in multiple peak shifts with different mass differences which were determined by the number of carbons within the respective peptide/protein. In addition to the high cost for the culture medium, the evaluation becomes more complicated by this approach. In contrast, in the study presented here, a protocol and different data evaluation approaches were developed based on the incorporation of single isotopically labeled amino acids. The resulting peak shifts in the profile spectra of Staphylococcus aureus strains were monitored and employed for a subsequent classification SILAC (stable isotope labeling by/with amino acids in cell culture) is a common technique for quantitative proteomics [12]. Pre-configured cell culture media without certain amino acids,

14 e.g. lysine, arginine, and leucine, are commercially available. For this work, only lysine was chosen as isotopic amino acid. Lysine occurs frequently in ribosomal proteins which are the main proteins detected in the MALDI Biotyper profile spectra (14, 15). Employing another amino acid as isotopic marker led to different changes in the profile spectra (data not shown). To establish the procedure, a small set of Staphylococcus aureus strains with known resistance properties was analyzed with this approach. Different concentrations of heavy amino acids were tested (data not shown). The concentration used in this work is a compromise between outcome and costs. Additionally, the incubation time was optimized. An incubation time of 2.5 h already allowed a classification for fast growing strains but not for all strains. The reason for this is on the one hand a lag phase before the cells start growing and on the other hand the presence of the proteins from the starting material comprising normal proteins. Several cell divisions were necessary to reduce the relative amount of the normal proteins to get sufficient intensities of the peaks corresponding to the heavy proteins. Further, even the susceptible strains do not immediately stop producing new proteins in the presence of oxacillin or cefoxitin but get slowed down by time. Therefore, a sufficient incubation time is required to facilitate the discrimination between susceptible and resistant strains. Thus, the set up with the heavy amino acids without antibiotics is an important control because this set up represents the maximal possible growth of a respective strain. An incubation time of 3 h was found to be sufficient and was applied in all experiments. The visual inspection on the spectra level is very time consuming and not suitable for the analysis of many spectra. Therefore, different automated evaluation approaches were applied to the spectra. Correlation analysis calculates the similarity between the different spectra sets. A breakpoint had to be defined to get a clear separation between the resistant and the susceptible strains. Since the susceptible strains still perform protein biosynthesis, the heavy + antibiotic spectra comprise normal as well as heavy peaks resulting in similarities to the normal spectra and to the heavy spectra. A correlation index below 0.6 of the comparison between heavy + antibiotic and normal spectra clearly indicated for a resistant strain. Applying this approach to the day-to-day reproducibility test and to 28

15 unknown samples revealed good concordance with the routine results. In some experiments (Fig 4C, strain 4, day 3, strain 260/FOX, Strain 469/FOX, strain 32241/FOX), this approach led to wrong classifications. The investigation on the spectra level revealed that in these cases the quality of the heavy + antibiotic spectra was poor. Strong noise resulted in dissimilarity to the normal as well as to the heavy spectra. This experiment demonstrates the importance of consistent spectra quality to get correct classifications by correlation analyses. The incorporation analysis is based on the pre-definition of peaks deriving from the normal and from heavy peaks within a spectrum, respectively. The ratio of the added intensities of the heavy peaks to the added intensities of the normal peaks was taken as a measure for the growth. High score values correspond to a growing culture. When susceptible strains were cultured in the presence of antibiotics this value was decreased compared to nonsusceptible strains. A breakpoint of 1.0 for the incorporation of heavy lysine in the heavy + antibiotic spectra was found to be suitable for the separation of susceptible and resistant strains. Susceptible strains revealed a value below 1.0 for the heavy + antibiotic spectra. The evaluation of the spectra sets according to this method led to the correct classification of all strains but one. In this experiment (Fig 4A, strain1, day 3) one of the resistant strains showed a value below the previously defined breakpoint. Investigating this result revealed poor growth of this strain in all set ups. Applying the calculation of the normalized difference also revealed good concordance with the routine results. One strain of the unknown clinical isolates was misclassified. The visual inspection of the spectra allowed for a clear classification as susceptible strain. The analysis of more strains and strict standardization will be necessary to confirm the suggested breakpoints and to facilitate the handling of strains comprising intermediate resistance behavior. In general, the approach presented in this study could be applied to classify Staphylococcus aureus strains according to their resistance status. The use of different antibiotics led to similar classifications. The visual inspection on the spectra level allowed for a correct classification of all strains analyzed, in each experiment. The correlation analysis failed in few cases. The reasons for the failure

16 were either on the technical side, e.g.the spectra quality or on the biological side, e.g. the growth of the microorganisms. Therefore, an optimization, adaptation, and further development of the analysis tools will be necessary. Considering that the incorporation analysis and the normalized difference are species specific tools, the development of a species independent analysis algorithm might be preferred Compared to other resistance assays this approach is very quick. Results could be read out after h comprising 3 h for the incubation of the cells and the residual time for setting up the assay, the subsequent sample preparation, the acquisition of spectra, and the evaluation. For other microorganisms and antibiotics even significantly shorter analysis times could be achieved (work in progress, data not shown). Most routine assays need an overnight incubation and automated resistance detection systems need at least 5 h for fast growing bacteria before a result can be stated. In the case that MALDI Biotyper based identification of microorganisms has already been established in a lab, no additional technical equipment would be necessary to perform this resistance test. The readout is directly based on the classical profile spectra which are acquired in the same mode as spectra for species identification. The combination of MALDI-TOF MS identification and MS- RESIST testing as described here might enable identification and resistance testing in a single day on the same equipment.in contrast to the MSBL assay (mass spectrometric ß- lactamase assay) (7 9), this approach could be applied to different antibiotics additionally to ß-lactam antibiotics and might be able to detect all known resistance mechanisms (16, 17). Preliminary results have already demonstrated that this technique can also be applied to investigate Meropenem resistance in Klebsiella pneumoniae and Pseudomonas aeruginosa and aminoglycoside resistance in Pseudomonas aeruginosa (data not shown, Jung et. al, manuscript in preparation). In principle, the MS-RESIST assay might be generally applicable to different species, also including fungi, and to other antibiotics. Optimal incubation conditions like time, adaptation of the culture medium and antibiotic concentration will have to be tested for the respective approach. Different alternative evaluation procedures might be necessary for optimal results of different species and antibiotic combinations.

17 Transparency declaration Katrin Sparbier, Christoph Lange, and Markus Kostrzewa are employed at the mass spectrometry company Bruker Daltonik GmbH, Bremen, Germany Literature 1. Leone M, Martin C How to break the vicious circle of antibiotic resistances? Curr Opin Crit Care 14: Bou G Minimum inhibitory concentration (MIC) analysis and susceptibility testing of MRSA. Methods Mol. Biol. 391: Woodford N, Eastaway AT, Ford M, Leanord A, Keane C, Quayle RM, Steer JA, Zhang J, Livermore DM Comparison of BD Phoenix, Vitek 2, and MicroScan automated systems for detection and inference of mechanisms responsible for carbapenem resistance in Enterobacteriaceae. J. Clin. Microbiol. 48: Mellmann A, Bimet F, Bizet C, Borovskaya AD, Drake RR, Eigner U, Fahr AM, He Y, Ilina EN, Kostrzewa M, Maier T, Mancinelli L, Moussaoui W, Prévost G, Putignani L, Seachord CL, Tang YW, Harmsen D High interlaboratory reproducibility of matrix-assisted laser desorption ionization-time of flight mass spectrometry-based species identification of nonfermenting bacteria. J. Clin. Microbiol. 47: Sauer S, Kliem M Mass spectrometry tools for the classification and identification of bacteria. Nat. Rev. Microbiol. 8: Seng P, Rolain J-M, Fournier PE, La Scola B, Drancourt M, Raoult D MALDI- TOF-mass spectrometry applications in clinical microbiology. Future Microbiol 5: Sparbier K, Schubert S, Weller U, Boogen C, Kostrzewa M Matrix-assisted laser desorption ionization-time of flight mass spectrometry-based functional assay for rapid detection of resistance against β-lactam antibiotics. J. Clin. Microbiol. 50: Hrabák J, Walková R, Studentová V, Chudácková E, Bergerová T Carbapenemase activity detection by matrix-assisted laser desorption ionization-time of flight mass spectrometry. J. Clin. Microbiol. 49: Burckhardt I, Zimmermann S Using matrix-assisted laser desorption ionizationtime of flight mass spectrometry to detect carbapenem resistance within 1 to 2.5 hours. J. Clin. Microbiol. 49: Sauer S, Freiwald A, Maier T, Kube M, Reinhardt R, Kostrzewa M, Geider K Classification and identification of bacteria by mass spectrometry and computational analysis. PLoS ONE 3:e R: A language and environment for statistical computing. Vienna, Austria. 12. Gibb S, Strimmer K MALDIquant: a versatile R package for the analysis of mass spectrometry data. Bioinformatics 28: Demirev PA, Hagan NS, Antoine MD, Lin JS, Feldman AB Establishing Drug Resistance in Microorganisms by Mass Spectrometry. J. Am. Soc. Mass Spectrom. 14. Teramoto K, Sato H, Sun L, Torimura M, Tao H A simple intact protein analysis by MALDI-MS for characterization of ribosomal proteins of two genomesequenced lactic acid bacteria and verification of their amino acid sequences. J. Proteome Res. 6:

18 Teramoto K, Sato H, Sun L, Torimura M, Tao H, Yoshikawa H, Hotta Y, Hosoda A, Tamura H Phylogenetic classification of Pseudomonas putida strains by MALDI- MS using ribosomal subunit proteins as biomarkers. Anal. Chem. 79: Poole K Efflux pumps as antimicrobial resistance mechanisms. Ann. Med. 39: Tenover FC Mechanisms of antimicrobial resistance in bacteria. Am. J. Med. 119:S3 10; discussion S Downloaded from on April 21, 2018 by guest

19 449 Figure legends 450 Figure Zoom of MALDI-TOF MS spectra displayed in flexanalysis (A, B) and ClinProTools (C, D) in the mass range between 6200 and 7200 Da of a susceptible Staphylococcus aureus strain (A, C) and a resistant Staphylococcus aureus strain (B, D) after incubation with normal lysine ( normal ), with heavy lysine ( heavy ), and with heavy lysine and Oxacillin ( heavy + Oxa ), respectively. Peaks corresponding to normal proteins are highlighted in light grey (A, B). Peaks corresponding to heavy proteins are indicated by the boxes (A, B). Y-axes give the number s of multiple measurements (C, D). Figure 2 Zoom of MALDI-TOF MS spectra displayed in flexanalysis (A, B) and ClinProTools (C, D) in the mass range between 6200 and 7200 Da of a susceptible Staphylococcus aureus strain (A, C) and a resistant Staphylococcus aureus strain (B, D) after incubation with normal lysine ( normal ), with heavy lysine ( heavy ), and with heavy lysine and Oxacillin ( heavy + FOX ), respectively. Peaks corresponding to normal proteins are highlighted in light grey (A, B). Peaks corresponding to heavy proteins are indicated by the boxes (A, B). Y-axes give the number s of multiple measurements (C, D). 470 Figure Correlation analysis: Correlation matrix of normal versus heavy + Oxa versus heavy of a susceptible strain (A) and a resistant strain (B). Red means strong similarity and blue means low similarity. Values similar or below 0.6 for the correlation normal versus heavy + Oxa were considered as resistant.

20 Figure Reproducibility of the MS-RESIST assay in combination with the different automated data evaluation strategies shown for four different Staphylococcus aureus strains (22318, 55158, 55279, and 56838) and Oxacillin Downloaded from on April 21, 2018 by guest

21 _N 0:C2 MS, Smoothed, BaselineSubtracted Intens. [a.u.] Intens. [a a.u.] Intens. [a.u.] x x x A normal _H_60 0:C10 MS, Smoothed, BaselineSubtracted heavy + Oa Oxa _H 0:C5 MS, Smoothed, BaselineSubtracted heavy Intens. [a.u.] Intens. [a a.u.] Intens. [a.u.] x x x B _N 0:E2 MS, Smoothed, BaselineSubtracted normal _H 0:E7 MS, Smoothed, BaselineSubtracted heavy + Oa Oxa _H_60 0:E9 MS, Smoothed, BaselineSubtracted heavy C normal D normal heavy + Oxa heavy + Oxa heavy heavy Figure 1: Zoom of MALDI-TOF MS spectra displayed in flexanalysis (A, B) and ClinProTools (C, D) in the mass range between 6200 and 7200 Da of a susceptible Staphylococcus aureus strain (A, C) and a resistant Staphylococcus aureus strain (B, D) after incubation with normal lysine ( normal ), with heavy lysine ( heavy ), and with heavy lysine and Oxacillin ( heavy + Oxa ), respectively. Peaks corresponding to normal proteins are highlighted in light grey (A, B). Peaks corresponding to heavy proteins are indicated by the boxes (A, B). Y-axes give the number s of multiple measurements (C, D).

22 449_N 0:H1 MS, Smoothed, BaselineSubtracted Intens. [a.u.] Intens. [a.u.] Intens. [a.u.] x x x A normal 449_H_60 0:H6 MS, Smoothed, BaselineSubtracted heavy + FOX 449_H 0:H3 MS, Smoothed, BaselineSubtracted heavy Intens. [a.u.] Intens. [a.u.] Intens. [a.u.] x x x B 330_N 0:E2 MS, Smoothed, BaselineSubtracted normal 330_H_60 0:E6 MS, Smoothed, BaselineSubtracted heavy + FOX 330_H 0:E3 MS, Smoothed, BaselineSubtracted heavy C normal D normal heavy + FOX heavy + FOX heavy heavy Figure 2: Zoom of MALDI-TOF MS spectra displayed in flexanalysis (A, B) and ClinProTools (C, D) in the mass range between 6200 and 7200 Da of a susceptible Staphylococcus aureus strain (A, C) and a resistant Staphylococcus aureus strain (B, D) after incubation with normal lysine ( normal ), with heavy lysine ( heavy ), and with heavy lysine and Oxacillin ( heavy + FOX ), respectively. Peaks corresponding to normal proteins are highlighted in light grey (A, B). Peaks corresponding to heavy proteins are indicated by the boxes (A, B). Y-axes give the number s of multiple measurements (C, D).

23 A susceptible strain 0,34 0,73 1,00 3: normal 0,72 1,00 0,73 2: heavy + Oxa 1,00 0,72 0,34 1: heavy Low similarity B resistant strain 0,34 0,40 1,00 3: normal 0,97 1,00 0,40 2: heavy + Oxa 1,00 0,97 0,34 1: heavy High similarity Downloaded from Figure 3 Correlation analysis: Correlation matrix of normal versus heavy + Oxa versus heavy of a susceptible strain (A) and a resistant strain (B). Red means strong similarity il it and blue means low similarity. il it Values similar il or below 0.6 for the correlation normal versus heavy + Oxa were considered as resistant. on April 21, 2018 by guest

24 A tion index Correla B Correlation analysis "heavy + Oxa" versus "normal" Incorporation analysis of "heavy + Oxa Day 1 Day 2 Day 3 C Normalize ed Difference Normalized Difference Day 1 Day 2 Day 3 Downloaded from f "heavy + OXA" Ratio (H/N) o Day 1 Day 2 Day 3 Figure 4 Reproducibility of the MS-RESIST assay in combination with the different automated data evaluation strategies shown for four different Staphylococcus aureus strains (22318, 55158, 55279, and 56838) and Oxacillin. on April 21, 2018 by guest

25 Table 1: Results of resistance testing by the standard routine method and the different bioinformatics approaches applied to the MS-RESIST spectra for the 28 routine isolates. Bold indicates resistance. Italic indicates dissent with other classification results. N/A: no spectra acquired. Correlation Incooperation Correlation Incooperation Normalized Normalized MIC [µg/ml] MIC [µg/ml] analysis "Heavy analysis analysis "Heavy Strain analysis "Heavy Difference Difference Oxacillin Cefoxitin +Oxa"/ "Heavy + + FOX"/ + Oxa" Oxa FOX "Normal" FOX" "Normal" >= 4 (R) >= 4 (R) >= 1 (R) <= 0.5 (R) <= 0.6 (R) >= 1 (R) <= 0.6 (R) <= 0.6 (R)

26 (4)

27 N/A N/A N/A

28 Number of resistant 14/28 14/28 14/28 15/28 14/28 13/27 14/27 16/27 strains of total strains Downloaded from on April 21, 2018 by guest