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Development and optimization of a higher throughput bacterial compound accumulation assay Marcella Widya, William Pasutti, Meena Sachdeva, Robert Simmons, Pramila Tamrakar, Thomas Krucker, and David A. Six ACS Infect. Dis., Just Accepted Manuscript • DOI: 10.1021/acsinfecdis.8b00299 • Publication Date (Web): 09 Jan 2019 Downloaded from http://pubs.acs.org on January 10, 2019

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ACS Infectious Diseases

Development and optimization of a higher throughput bacterial compound accumulation assay Authors: Marcella Widya, William D. Pasutti, Meena Sachdeva, Robert L. Simmons, Pramila Tamrakar, Thomas Krucker, David A. Six Address Infectious Diseases Area and Global Discovery Chemistry, Novartis Institutes for BioMedical Research, 5300 Chiron Way, Emeryville, CA 94608, USA The Gram-negative bacterial permeability barrier, coupled with efflux, raises formidable challenges to antibiotic drug discovery. The absence of efficient assays to determine compound penetration into the cell and impact of efflux makes the process resourceintensive, small-scale, and lacking much success. Here, we present BacPK: a label-free, solid phase extraction-mass spectrometry (SPE-MS)-based assay that measures total cellular compound accumulation in Escherichia coli. The BacPK assay is a 96-well accumulation assay that takes advantage of 9 second/sample SPE-MS throughput. This enables the analysis of each compound in a 4-point dose-response in isogenic strain pairs along with a no-cell control and 16-point external standard curve, all in triplicate. To validate the assay, differences in accumulation were examined for tetracycline (Tet) and two analogs, confirming close analogs can differ greatly in accumulation. Tet cellular accumulation was also compared for isogenic strains exhibiting Tet-resistance due to expression of an efflux pump (TetA) or ribosomal protection protein (TetM), confirming only TetA affected cellular Tet accumulation. Finally, using a diverse set of antibacterial compounds, we confirmed the assay’s ability to quantitate differences in accumulation for isogenic strain pairs with efflux or permeability alterations that are consistent with differences in susceptibility seen for the compounds. Keywords: Bacteria, antibiotic, accumulation, assay, efflux, permeability

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Clinical failure of established antibiotic therapy in recent years has been attributed mainly to the emergence of multi-drug resistant (MDR) strains of pathogenic bacteria. Key mechanisms of bacterial resistance to antibiotics are: alteration and modification of the target site; enzymatic degradation of the antibiotic; and increased efficiency of the membrane barrier or loss of permeability in concert with active efflux. Modifications of porin activity reduce compound transit across the outer membrane while overexpression of efflux pumps results in compound extrusion out of the cell. This in turn limits the intracellular concentration of the antibiotics.1-3 One of the biggest obstacles to overcome during discovery of new antibiotics for MDR Gram-negative pathogens is the requirement to penetrate the cell envelope. This is necessary in order to deliver the compound to its target, often located in the periplasm or, more commonly, in the cytoplasm. Gramnegative bacteria are intrinsically difficult to treat in part because of their outer membrane (OM). The OM serves as a permeability barrier, blocking or reducing the influx of many compounds, including large and/or hydrophobic antibacterials, into the cells. In addition, MDR Gram-negative pathogens possess efflux pumps. These can reduce the intracellular concentration of many compounds, again including many antibacterials. Although Hergenrother and colleagues have published a set of guidelines or rules for predicting compound permeation in E. coli,4, 5 the methodology used to derive these guidelines has several drawbacks. For example, minimal data for each compound is available due to low throughput,6 and perhaps as a result, there are many notable exceptions to these derived guidelines.7-9 It is clear that more robust data for a greater number and diversity of both compounds and bacterial strains will be necessary to generate testable structure-accumulation relationships. Accurate and efficient methods for quantifying compound concentration in bacteria are critical to establish a relationship between the cellular accumulation and physico-chemical properties. Several approaches have been used to quantify antibiotics in bacteria.6 Radiolabeled antibiotics have been utilized extensively for uptake studies in Pseudomonas aeruginosa 10, 11, Escherichia coli and Staphylococcus aureus 12. Taking advantage of the auto-fluorescence of some antibiotics, many investigators have used fluorescence assays to study intracellular concentrations of fluoroquinolones 13, 14 and tetracycline (Tet) 15-17 in bacteria. Though radiolabeled assays are sensitive, they are low throughput, cost-intensive, and not always feasible. There are also many disadvantages to using fluorescence assays, including the limited number of auto-fluorescent compounds available, low sensitivity, and difficulties with quantitation. More recently, low throughput liquid chromatography-mass spectrometry (LC-MS) based assays were published to monitor compound uptake in E. coli,4, 5, 18 in P. aeruginosa,18, 19 and in Mycobacterium.20, 21 The use of LC-MS circumvents problems encountered by radiolabeling and fluorescent assays. However, the reported analysis times were between 2.5 and 21 minutes/sample. This makes them less amenable to the screening of a large number of compounds or conditions.


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Here, we present BacPK: a label-free, solid-phase extraction-mass spectrometry (SPE-MS)-based assay that measures total cellular compound accumulation in E coli. The BacPK assay is a 96-well accumulation assay that takes advantage of 9 second/sample SPE-MS throughput. This enabled 80 sample injections for each compound tested, encompassing a 16-point external standard curve, along with a 4-point dose-response in an isogenic strain pair, and a no-cell control, all in triplicate. We validated the assay with a variety of compounds that have known or expected differences in cellular accumulation between isogenic strain pairs.



Figure 1. Summary of the sample preparation steps of the BacPK assay. Cells are incubated with compound in 96-well plates, allowing for increased throughput. The wash steps are aided by a vacuum manifold. By applying a vacuum, the cell pellets are held tightly to the filter plate, allowing the supernatant or wash buffer to be removed swiftly by inverting the vacuum manifold holding sample plate. After lysis, the samples are analyzed by high-throughput solid-phase extraction (SPE) – tandem mass spectrometry (MS/MS). Sample MS signal is normalized to both an external standard curve and the OD600 values of its respective sample well.

Results Effects of the incubation buffer when measuring efflux-sensitive compounds As a validation control for the BacPK assay, we compared Tet accumulation in isogenic strains with two different Tet resistance genes. The TetA efflux pump is a member of the Major Facilitator Superfamily (MFS) of efflux pumps. It effluxes Tet from the cytoplasm into the periplasm using the proton gradient across the inner membrane.16 In cells that are no longer actively metabolizing, the proton gradient across the inner membrane collapses, abrogating efflux across the inner membrane.22 The TetM ribosomal protection protein causes modification of the ribosome to prevent productive binding of Tet and various analogs to the ribosome target.23 TetM is not expected to alter the compound permeation or efflux, but would be expected to reduce the cytoplasmic Tet binding sites on the ribosome. The expression of Tet resistance proteins TetA (encoding a Tet-specific efflux pump) or TetM (encoding a ribosomal protection protein) both causes Tet MIC shifts of ≥32-fold compared to the vector alone, as described previously 16, 24, 25 (Fig. 2).

Figure 2. Chemical structures and MIC values of tetracycline and its analogs 2tetracyclinonitrile (CN-Tet) and 13-phenylmercapto-α-6-deoxy-tetracycline (PTT). E. coli strains tested: Control E. coli K-12 BW25113 containing vector control and two


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Tet-resistant strains: TetA (expressing the efflux-pump TetA), and TetM (expressing the ribosome protection protein TetM). When Tet was incubated with cells washed and resuspended in Tris-buffer, comparable Tet accumulation was detected in the vector control and TetA strain (Fig. 3A). However, there was a seven-fold reduction in cellular Tet in the TetA strain compared to the control strain when incubating the cells in LB (Fig. 3A). Tet accumulation in the control strain was also significantly lower when incubated in Tris compared to LB (P = 0.029, n=2), consistent with energy-dependent influx described for Tet.45 MHBII is used routinely in microbiological assays to determine the MIC of antibacterial compounds, so Tet accumulation in MHBII was tested. In MHBII there was once again lower Tet accumulation in the TetA containing strain (Fig. 3B, P = 0.0053, n=3), consistent with energized efflux. The requirement for energized efflux has been previously reported for sulfoadenosines, where the accumulation in phosphate-buffered saline was higher than growth medium and glucose-supplemented phosphate buffered saline.22 There was also a significant difference in Tet accumulation for the vector control strain between LB and MHBII (P 128

1

Erythromycin

>128

4*

64

2

Novobiocin Rifampicin Tetracycline Tiamulin

>64 32 2 >128

4 0.06 0.5 16*

>64 1 >128

2 0.5 0.5

* Denotes observed growth inhibition at sub-MIC concentrations.

For Tet and ciprofloxacin, no significant difference in measured accumulation was seen between the isogenic strain pairs (Fig. 7), consistent with their MIC values. All six



remaining compounds showed significantly higher level of accumulation in the OM permeable strain compared to the wild type strain at nearly all concentrations tested (Fig. 7). This was again consistent with their MIC values. While cellular compound accumulation was lower in the WT strain, it was detectable for five of six compounds tested at doses well below the MIC. The ability to detect compound accumulation substantially below the MIC for WT E. coli is a feature of the BacPK assay that reflects the large number of cells used in the assay, the minimal dilution factor during lysis/extraction, and the sensitivity of the SPE-MS. However, one of the tool compounds, dicloxacillin, was only detected in the OM permeable strain at the highest doses (16 and 64 µg/mL). The challenges in detecting beta-lactams have been previously reported 4, and could be due to multiple factors. In the BacPK assay, only masses specific to the intact parent compound were monitored by SPE-MS/MS. Any change in parent mass, and some changes in structure that impact fragmentation, would result in non-detection. Beta-lactams like dicloxacillin are known to react with and covalently bind to penicillin binding proteins.34 Once reacted, they would not be detected with the MS/MS transitions selected for the BacPK assay. In addition, E. coli K-12 has a chromosomal copy of the ampC gene coding for a beta-lactamase. While expression of AmpC in E. coli K-12 is low,35 any hydrolysis of dicloxacillin would reduce the signal of the parent ion. Another reason for low levels of this beta-lactam could be due to its localization to the periplasm (and exclusion from the cytoplasm).36 As porins are two-way channels, loss of periplasmic compound during washes is possible.


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Figure 7. BacPK assay compound accumulation measured in E. coli wild-type (WT) and the OM permeable mutant (lptD4213) for A) novobiocin (1 µg/mL: P = 0.0615; 4, 16 and 64 µg/mL: P ≤ 0.0124), B) erythromycin (all concentrations: P ≤ 0.0068), C) tiamulin (all concentrations: P ≤ 0.0251), D) rifampicin (all concentrations: P ≤ 0.0275), E) CoaD compound 8 (1, 16, and 64 µg/mL: P ≤ 0.0453, 4 µg/mL: P = 0.0543), F) ciprofloxacin (all concentrations P = 0.17 to 0.3), G) Tet (all concentrations P = 0.0573 to 0.1919), and H)



dicloxacillin (64 µg/mL: P = 0.039). Analysis was performed by SPE-MS/MS. Results are normalized to an external standard curve and again to the OD600 of respective sample. Accumulation is expressed as ng compound per OD600. All experiments were performed at least twice in triplicate. Representative results are displayed here. For ease of visualization the points are connected. The LLOD, ULOQ, and adjusted ULOQ values can be found in Table S2. Efflux-deficient mutant E. coli versus wild-type E. coli The BacPK assay was also applied to a second set of antibiotics possessing differential against wild-type E. coli K-12 and its isogenic efflux-deficient mutant ΔtolC. In E. coli, TolC is the only outer membrane channel in the RND class of tripartite efflux pumps,37 so this strain completely lacks efflux from over nine different TolC partners.38 Many antibiotics and other compounds are known substrates of TolC-dependent efflux, including erythromycin and novobiocin, and deletion of the efflux pump can increase susceptibility, while overexpression of the efflux pump can decrease susceptibility to these pump substrates.39, 40 Two control compounds, Tet and ciprofloxacin, show no significant difference in MIC for the isogenic strain pair (Table 1), suggesting that any contribution of efflux is minimal under the MIC conditions. In contrast seven tool compounds (actinonin, clindamycin, CoaD compound 8, dicloxacillin, erythromycin, novobiocin, and tiamulin) show large shifts in susceptibility between the isogenic strain pair. All seven have little measurable growth inhibitory activity against wild type E. coli (MIC: 64 to >128 µg/mL), but do display activity (MIC: ≤0.125 to 4 µg/mL) against an isogenic efflux-deficient mutant ΔtolC (Table 1). For ciprofloxacin, no significant difference in accumulation was detected in the two strains (Fig. 8). Overall, tetracycline accumulation in the ΔtolC strain was found to be somewhat higher than in the wild-type strain, but this difference was only significant at the 1 µg/mL dose. This is consistent with the reported TolC-mediated efflux of Tet.17 CoaD compound 8 only showed significant difference in accumulation at 64 µg/mL, despite the shift in MIC between the two strains. The other six compounds all showed a higher level of accumulation in ΔtolC strain compared to the wild type strain (Fig. 8), again consistent with their MIC values. Cellular compound accumulation was readily detectable for six of seven compounds tested in wild-type E. coli including doses well below the MIC. Dicloxacillin was clearly detected in the ΔtolC mutant above the LLOD at doses ≥4 µg/mL. However dicloxacillin was not detected in wild-type E. coli, with the exception of 2 out of 6 biological replicates at the 64 µg/mL dose (Fig. 8), which matched the findings from Fig. 7.


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Figure 8. BacPK assay accumulation in E. coli wild-type versus efflux-null. Analysis was performed by SPE-MS/MS. Results are normalized to an external standard curve and again to the OD600 of respective sample. Accumulation is expressed as ng compound per OD600. The accumulation was measured (n=3) in E. coli wild-type (Keio parent strain (BW25113)) and ΔtolC (Keio tolC732::kan) for A) actinonin (all concentrations, P≤0.0147), B) novobiocin (all concentrations, P 410.2. Quantitation of Tet was performed using calibration curves prepared in 50:50 10 mM Tris-HCl, pH 8:methanol, v:v, and analyzed in parallel. Accumulation of tetracycline analogs in an isogenic Tet-resistant strain panel The isogenic strains, composed of E. coli K-12 (BW25113) with plasmids containing tetA, tetM, or the vector control, were tested with various Tet analogs. All experiments were performed in biological triplicate, three times on separate days. As the assay was optimized for the comparison of only two strains in the same batch, these particular samples were prepared in separate batches. Each batch contained the control strain and either the tetM-containing strain, or tetA-containing strain. MS SRM transitions monitored were as follows: 445.2 > 410.2 (Tet), 427.2 > 257.1/153.1 (CN-Tet), and 537.1 > 123.1/520.2 (PTT). Accumulation in isogenic strain pairs evaluating efflux deficiency or OM permeability defect All samples were prepared as per BacPK methodology. All experiments (each containing a biological triplicate) were performed at least twice on separate days. MS SRM transitions monitored were as follows in m/z: 386.3 > 102.7/285.3 (actinonin), 332.1 > 288.1 (ciprofloxacin), 425.3 > 126.1/377.2 (clindamycin), 453.3 > 149.1/253.1 (CoaD compound 8), 470 > 160.2/311.0 (dicloxacillin), 734.5 > 576.3 (erythromycin), 613.2 > 189.1 (novobiocin), 823.4 > 791.5 (rifampicin), 445.2 > 410.2 (Tet), and 494.3 >192.1/119.5 (tiamulin). Statistical analysis All statistical analysis was performed using GraphPad Prism 7.04 for Windows (GraphPad Software, La Jolla, CA). Statistical difference between the slopes of the linear standard curves (Figure S1) was determined by using a two-tailed t-test. Statistical significance of accumulation measured was determined per separate dose concentration by using a two-tailed Welch’s t-test (unpaired, assuming unequal variance) relative to the control strains (Figures 3, 6, 7, and 8).

Associated Content Supporting Information Supplemental Results: Sample matrix effects on compound detection by MS Figure S1: Standard curves of 5 compounds with and without matched matrix Supplemental Methods: Matrix effects on MS and compound synthesis for Tet analogs Figure S2: Reaction scheme of PTT synthesis Figure S3: Reaction scheme of CN-Tet synthesis Supplemental Discussion: Expanding the BacPK assay to other species


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Table S1: MS settings used for all experiments Table S2: Detection limits for compounds from Fig. 7 Table S3: Detection limits for compounds from Fig. 8

Author Information Corresponding Author *E-mail: [email protected] ORCID David A. Six: 0000-0002-9013-1711 Present Addresses: M.W. & P.T.: BioMarin Pharmaceuticals, Inc., San Rafael, California. W.D.P.: Ribometrix, Inc., Durham, North Carolina. M.S.: Sanofi, Framingham, Massachusetts. D.A.S.: VenatoRx Pharmaceuticals, Inc., Malvern, Pennsylvania. Notes The authors declare the following competing interest(s): All authors were working at Novartis Institutes for BioMedical Research at the time this work was conducted. T.K. is a current Novartis employee and owns stock and/or stock options.

Acknowledgements We thank Cindy Li for confirming the MIC values and Matthew Spencer, Sovanda Som, Ali Akin, Alexey Ruzin, Xiaoyu Shen, Tsuyoshi Uehara, Charles Dean, Folkert Reck, Brian Feng, Laura McDowell, Jennifer Leeds, William Sawyer, and Christopher Rath for their support and helpful discussions. This work was fully funded by Novartis Institutes for BioMedical Research.

Abbreviations ACN, acetonitrile; BacPK, bacterial pharmacokinetics; CN-Tet, tetracyclinonitrile; LB, lysogeny broth; LC-MS, liquid chromatography-mass spectrometry; LLOD, lower limit of detection; MDR, multi-drug resistant; MDS, Major Facilitator Superfamily; MHBII, cation adjusted Mueller-Hinton broth; MIC, minimum inhibitory concentration; OD600, optical density at 600 nm; OM, outer membrane; PCR, polymerase chain reaction; PTT, 13phenylmercapto-α-6-deoxy-tetracycline; QQQ, triple quadrupole; RND, resistance, nodulation, differentiation; SIMS, secondary ion mass spectrometry; S/N, signal to noise; SPE-MS, solid phase extraction-mass spectrometry; SRM, selected reaction monitoring; Tet, tetracycline; Tris, tris(hydroxymethyl)-aminomethane; ULOQ, upper limit of quantitation; WT, wild-type



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