Molecular Probes for the Determination of Subcellular Compound

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Molecular probes for the determination of sub-cellular compound exposure profiles in Gram-negative bacteria Benjamin Spangler, Dustin Dovala, William S Sawyer, Katherine V Thompson, David A Six, Folkert Reck, and Brian Y Feng ACS Infect. Dis., Just Accepted Manuscript • DOI: 10.1021/acsinfecdis.8b00093 • Publication Date (Web): 30 May 2018 Downloaded from http://pubs.acs.org on June 1, 2018

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ACS Infectious Diseases

Molecular probes for the determination of sub-cellular compound exposure profiles in Gram-negative bacteria. Benjamin Spangler1, Dustin Dovala1, William S. Sawyer 1, Katherine V. Thompson 1, David A. Six 1, Folkert Reck1, and Brian Y. Feng1* 1

Novartis Institutes for BioMedical Research; 5300 Chiron Way, Emeryville, CA. 94608; USA.

The Gram-negative cell envelope presents a formidable barrier to xenobiotics, and achieving sufficient compound exposure inside the cell is a key challenge for the discovery of new antibiotics. To provide insight on the molecular determinants governing compound exposure in Gram-negative bacteria, we developed a methodology leveraging a cyclooctyne-based bioorthogonal probe to assess compartment-specific compound exposure. This probe can be selectively localized to the periplasmic or cytoplasmic compartments of Gram-negative bacteria. Once localized, the probe is used to test azide-containing compounds for exposure within each compartment by quantifying the formation of click-reaction products by mass spectrometry. We demonstrate this approach is an accurate and sensitive method of determining compartmentspecific compound exposure profiles. We then apply this technology to study the compartmentspecific exposure profiles of a small panel of azide-bearing compounds with known permeability characteristics in Gram-negative bacteria, demonstrating the utility of the system and the insight it is able to provide regarding compound exposure within intact bacteria. Keywords: Gram-negative permeability, bioorthogonal probes, click chemistry, compartmentspecific exposure.

* Correspondence: [email protected]

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The Gram-negative cell envelope represents a major obstacle to antibacterial drug discovery.1–5 Gram-negative bacteria have two membranes, an inner membrane (IM) composed of a phospholipid bilayer similar to that found in Gram-positive bacteria, and a distinctive asymmetrical outer membrane (OM). While the inner leaflet of the OM is also composed of phospholipids, the outer leaflet is composed of lipopolysaccharide (LPS) which consists of a lipid core appended with long chains of polar sugars. Many compounds are thought to pass through the OM via hydrophilic porin channels;6,7 however, the majority of antibacterial targets reside within the cytoplasmic compartment.8 For compounds to achieve on-target efficacy in this compartment they must also be able to permeate the hydrophobic IM or otherwise be transported across this barrier. The orthogonal permeability characteristics of the OM and IM are consequently thought to limit efficient permeation of most compounds into the cytoplasm.1 In addition to these formidable barriers, many bacteria possess efflux pumps with broad substrate specificity which further limit the concentrations of xenobiotics within Gram-negative bacteria.5 To achieve therapeutic concentrations in the target compartment, compounds must thus possess physicochemical properties that balance OM permeability, IM permeability and efflux pump recognition. Few methods currently exist which provide the resolution necessary to understand how changes to the physicochemical properties of a molecule independently impact each of these factors.1,7 Classically, the ability of a compound to gain exposure within Gram-negative bacteria was inferred from the presence or absence of antibacterial activity. While these activity-based analyses have provided important insight into some of the factors which affect exposure within bacteria,2,3,9 these methods cannot be used to study inactive or weakly-active compounds, and there are few tools capable of providing activity-independent assessments of compound exposure in Gram-negative bacteria. Compounds with intrinsic spectroscopic features can be studied via various methods including spectroscopy, microscopy, and flow cytometry which can

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provide spatial and temporal resolution. Unfortunately, these measures are limited to the small subset of compounds with useful spectroscopic properties.10–14 In contrast, mass spectrometry (MS) can be used to analyze a broad range of chemical matter in an activity-independent fashion. While a number of such methodologies have been developed and successfully applied to provide greater understanding of compound exposure in bacteria, these approaches have thus far lacked either the resolution15–17 necessary to discriminate between exposure in the periplasmic and cytoplasmic compartments, or the throughput18 needed to explore large panels of chemical matter. This lack of tools has impeded the optimization of novel chemical matter for improved permeability; consequently, the development of new Gram-negative antibiotics has in large part been limited to known scaffolds with good intrinsic permeability.1 To address this gap, we have developed a cyclooctyne-based probe for measuring compound exposure with sub-cellular resolution. This technology is built upon the well-established bioorthogonal, strain-promoted, alkyne-azide cycloaddition (SPAAC)19,20 “click” reaction between bicyclo[6.1.0]nonyne (BCN)21 and azide-bearing compounds. We first localize BCNbearing compounds within the compartments of interest, and then use these compounds as probes for the exposure of azide-bearing molecules by monitoring the production of clickproducts (Figure 1). As a prototypical example of this strategy we describe here a Biotin-BCN conjugate which is selectively localized to the periplasmic or cytoplasmic compartments of Gram-negative bacteria using directed localization of heterologously-expressed streptavidin.22 Once localized, this probe serves as a sensitive and accurate tool to measure compartmentspecific compound exposure. Using a panel of azide-bearing molecules with well-studied OM and IM permeability properties, we demonstrate how this measurement can be used to quantify the relative exposure of compounds in each compartment. We also detail important control experiments required to accurately compare permeability properties between compounds and strains of E. coli. This approach combines the benefits of MS-based methodologies to enable



interrogation of diverse chemical matter with the subcellular resolution needed to study the differential permeability properties of the outer and inner membranes of Gram-negative bacteria in situ.

Results: Cyclooctyne probes enable sensitive detection of small-molecule azides in vitro In order to use cyclooctyne probes to provide subcellular resolution of compound exposure, they must be specifically localized to the compartments of interest (Figure 1). We reasoned we could utilize streptavidin expression systems paired with a biotin-cyclooctyne conjugate to achieve this based on previous literature precedent.22

Figure 1: Bio-orthogonal probes enable determination of sub-cellular compound exposure profiles within Gram-negative bacteria. Biotin-cyclooctyne conjugate probes are selectively localized to the


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periplasmic or cytoplasmic compartments using compartment-specific streptavidin expression. The exposure of azide-bearing molecules can then be assessed by measuring the formation of click-products by MS analysis after lysis and protein denaturation. Electron micrograph credit: Rocky Mountain Laboratories, NIAID, NIH (https://www.niaid.nih.gov/sites/default/files/E.coli.jpg).

To enable this approach, we constructed a Biotin-BCN conjugate from BCN alcohol (1) (Figure 2a). A portion of this material was further exposed to benzyl azide to give the authentic clickproduct 3, confirming the conjugate retained the ability to participate in 1,3-dipolar cycloadditions (Figure 2a). These compounds were further characterized by liquid chromatography-mass spectrometry (LCMS) to optimize chromatography conditions and determine the limits of detection. Both the Biotin-BCN probe (2) and the click-product (3) had linear ranges of detection from 50 pM-200 nM in E. coli lysate (Figure 2b). MS/MS analysis revealed the compounds shared common fragmentation ions (Figure S1), a feature we later exploited to identify click-products for which authentic synthetic samples were not available. Next, we measured the linear range of detection for a model azide under conditions representative of those within the bacteria. E. coli lysate containing 20 µM of compound 2 was thus treated with varied concentrations of benzyl azide for 3 h at 37 °C, and then analyzed for the presence of click-product (Figure 2c). Under these conditions, click-product was detected from treatment with as little as 1 nM benzyl azide. These findings suggested compound 2 could be utilized as a sensitive probe for intracellular azide exposure if efficiently and specifically localized to the desired compartments. Biotin-cyclooctyne probes can be localized to specific compartments in E. coli To enable the compartment-specific incorporation of probe 2 in E. coli, we constructed isogenic strains from a wild-type (WT) E. coli K12 (BW25113) background in which heterologouslyexpressed T7-tagged streptavidin23 was either directed to the periplasmic or cytoplasmic compartments (Figure 2d). To produce the periplasmic strain we induced secretion of the



streptavidin construct into the periplasm by leveraging the well-studied OmpA signal peptide sequence.22,24 The complementary cytoplasmic strain was created simply by omitting the signal peptide. We then optimized growth conditions for these strains to provide robust expression of streptavidin and achieve optimal incorporation of probe 2 (Figure S1). Under these conditions, bacteria were grown in M9 minimal media to exponential growth phase and streptavidin expression was induced with L-rhamnose 10 minutes prior to the addition of 2 to the growth medium (20 µM). The bacteria were exposed to probe 2 for 16 h, and then thoroughly washed to prevent the subsequent formation of click-products not arising from compartment-specific azide exposure.

Figure 2: Cyclooctyne probes detect nM concentrations of azides in vitro and can be differentially localized to the compartments of E. coli. (a) synthesis of probe 2 and subsequent click-products; (i) 4nitrophenyl chloroformate, pyridine, DCM, 0° C - rt, 1 h, 66%; (ii) Biotin-PEG2-NH2, TEA, DMF, rt, 3 h,


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59%. Subsequent exposure of 2 to azide bearing compounds results in formation of triazole ‘clickproducts’. (b) Linear limits of detection for compounds 2 and 3 in E. coli lysate as determined by + integrated EIC for the respective ions ([M+Na] ) normalized to an internal control (100 nM tetracycline). (c) The detection limit (dotted line) of benzyl azide (BnN3) as determined by the formation of click-product (3) after a 3 h exposure to 20 µM 2 in E. coli lysate at 37 °C with data collected as in (b). The lower limits of detection (LLoD) for each species were determined from vehicle controls (3*SD). MS data are shown as mean values from experiments conducted in triplicate. Error bars represent SD (n = 3). (d) Plasmids constructed for cytoplasmic and periplasmic localization of streptavidin in E. coli. (e) Representative fluorescence microscopy images of E. coli expressing the respective plasmids following incorporation of 2 and click reaction with 5R110-N3 (green). Bacterial membranes were visualized with FM4-64FX dye (red) and DNA was visualized with Hoechst 34580 nuclear stain (blue). Scale bars denote 2 µm.

Induction of streptavidin expression had a modest impact on the growth rate of the E. coli strains, likely as a function of the additional energy required to highly express this exogenous protein (Figure S2). As the streptavidin expression strains showed no significant changes in sensitivity to a panel of known antibiotics, including several excluded from the cell by the Gramnegative cell envelope and/or efflux pumps we anticipate that the permeability barrier of the bacteria is not significantly altered in these strains (Table S1). Furthermore, under these conditions, treatment with probe 2 did not impair growth (Figure S2). These findings indicate that the conditions used in the assay do not appear to significantly affect cell viability, permeability, or efflux. Using this general protocol for probe incorporation, we exposed bacteria bearing probe 2 to a fluorescent azide (5R110-N3) which had previously been found to achieve some exposure in E. coli,25 and used fluorescence microscopy to test whether 2 was appropriately localized in the cytoplasmic and periplasmic streptavidin expression strains. We found that bacteria expressing cytoplasmic streptavidin exhibited fluorescence that strongly co-localized with nucleic acid staining, indicative of cytoplasmic localization (Figure 2e). Bacteria expressing periplasmic streptavidin instead showed staining that co-localized with a membrane dye, consistent with periplasmic localization. Comparatively, bacteria lacking a streptavidin expression vector showed no significant fluorescence under these conditions. These findings not only confirmed



the desired localization of 2 within each of the strains, but also indicated that once localized, the cyclooctyne remains reactive with small molecule azides. The lack of fluorescence in the absence of heterologous streptavidin expression further indicates that significant incorporation and retention of 2 requires streptavidin expression. Having established the feasibility of localizing probe 2 to either the cytoplasm or periplasm, we next sought to leverage MS-based quantitation of 2 and click-products to measure probe incorporation and reactivity with bioactive control compounds. As a positive control for these assays we utilized azidothymidine (AZT), a known azide-bearing nucleoside analog with antibacterial activity in E. coli 26 (Figure 3a, Table S1). AZT is known to be a substrate of at least two nucleoside active transport systems27–29 and exerts antibiotic activity by inhibiting DNA synthesis30; this makes it a convenient positive control for cytoplasmic exposure. Consistent with our fluorescence experiments, treatment of E. coli bearing an empty expression vector with probe 2 and AZT did not yield detectable levels of probe 2 or AZT click-products, again indicating that heterologous streptavidin expression is required for probe retention and localization (Figure 3b). In contrast, strains expressing either cytoplasmic or periplasmic streptavidin were both loaded with significant amounts of probe 2. Interestingly, significantly more probe incorporation was observed in the periplasmic strain, suggesting probe 2 may be able to preferentially access this compartment. Importantly, subsequent treatment with AZT led to click-product formation in both strains, confirming that localized probe 2 is reactive and can be used to detect azide exposure by MS.


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Figure 3: MS analysis demonstrates the incorporation of probe 2 and its ability to detect azidebearing compound exposure in E. coli expressing localized streptavidin. (a) Scheme for reaction of probe 2 with AZT to form click-products. (b) Levels of probe 2 and click-products observed in the cytoplasmic and periplasmic streptavidin expression strains derived from WT E. coli (Efflux +) after probe incorporation and click reaction with 20 µM AZT as compared to signal observed in bacteria bearing the empty vector treated identically. (c) Levels of probe 2 and click-products observed in the cytoplasmic and periplasmic streptavidin expression strains derived from E. coli ∆tolC (Efflux -) as in (a). See Figure S3 for related information. ‘Normalized EIC’ values represent the integrated extracted ion chromatograms for the indicated analytes normalized to that of the internal standard (50 nM 3) from the same sample.

To explore the effects of efflux on compound exposure profiles, we also constructed strains expressing cytoplasmic or periplasmic streptavidin in an E. coli-∆tolC background. We found >100-fold more incorporation of probe 2 in the compartments of strains originating from E. coli-∆tolC (Figure 3c). As streptavidin expression was not significantly different in these strains (Figure S3), this result suggests efflux of 2 limits the exposure of the probe in WT E. coli. Consistent with this observation, we also measured low, but detectible, levels of probe 2 in E.



coli-∆tolC cells bearing the empty vector (64 µg/mL), whereas AZT susceptibility was similar (0.002 - 0.008 µg/mL, Table S1). While PMA clickproduct was also observable in the cytoplasm of E. coli-∆tolC, AZT click-product was observed at approximately 300-fold higher levels indicating additional factors limit the cytoplasmic exposure of PMA (i.e. IM permeability). Overall, these findings indicate that this method is able to quantify the differences between known permeable and impermeable compounds, and furthermore, that these differences can be assessed within intact bacteria across a dynamic range spanning at least 3 orders of magnitude.



Figure 5: Click-product formation within each compartment is dependent on the concentration of azide present. The concentration dependence of click-product formation from 3 h of AZT or PMA exposure was then explored in the cytoplasmic (a, c) and periplasmic (b, d) strains derived from WT (efflux +, a-b) and ∆tolC (efflux -, c-d) E. coli. The lower limits of detection (LLoD) for each species were determined from vehicle controls (3*SD). All data are shown as mean values from experiments conducted in triplicate. Error bars represent SD (n = 3). ‘Normalized EIC’ values represent the integrated extracted ion chromatograms for the indicated analytes normalized to that of the internal standard (50 nM 3) from the same sample.

Probes provide compartment-specific analysis of perturbations to bacterial permeability To further explore the limited exposure of PMA, we interrogated how membrane integrity affected signal for PMA exposure in this assay. As seen above, in untreated cells PMA exposure was below the limit of detection in the cytoplasm of WT E. coli. However, bacteria pretreated with polymyxin B nonapeptide (PMBN)33,34, colistin16,35, or EDTA36, accumulated substantially more PMA click-product, consistent with the known mechanisms of membrane perturbation for each of these agents (Figure 6a). Bacteria pretreated with cyanide mchlorophenylhydrazone (CCCP)6, a known de-coupler of the proton-motive force (PMF) and inhibitor of efflux pump function (amongst other processes), also resulted in a similar increase in 14 ACS Paragon Plus Environment

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signal for cytoplasmic PMA exposure. These same treatments had little to no impact on the cytoplasmic levels of AZT. (Figure 6a and Figure S5).

Figure 6: The impact of permeabilizing treatments on PMA exposure in the compartments of E. coli. (a) Probe-loaded bacteria from the WT (efflux +) cytoplasmic strain were pretreated with PMBN (200 µg/mL), colistin (5 µM), EDTA (1 mM in Tris-HCl pH 8), CCCP (100 µM), or vehicle (0.1% DMSO) for 20 min at 37 °C prior to azide addition (10 µM for 3 h) then measured by MS for differences in click-product formation between conditions. The LLoD (3*SD of bacteria not treated with PMA) for PMA click-product is shown by the dotted line. (b) Comparison of changes in PMA exposure between the cytoplasm and periplasm of WT bacteria treated as described in (a), data is shown as fold change from bacteria pretreated with vehicle. All data are shown as mean values from experiments conducted in triplicate. Error bars represent SD (n = 3). *: P < 0.05, ****: P < 0.0001. See Figure S5 and Table S2 for related information. ‘Normalized EIC’ values represent the integrated extracted ion chromatograms for the indicated analytes normalized to that of the internal standard (50 nM 3) from the same sample.

In the periplasmic compartment a less uniform response was observed from the same treatments. While EDTA and CCCP still produced significant increases in PMA exposure, PMBN and colistin had no effect (Figure 6b, Table S2). While PMBN and colistin are thought to interact directly with the membranes, EDTA and CCCP may have more pleiotropic effects on the permeability barrier. EDTA has been observed to impact both OM integrity36–38 and efflux39, 15 ACS Paragon Plus Environment


while CCCP treatment will deactivate any processes energized by the PMF including efflux pumps and many transporters. These findings thus suggest that periplasmic PMA exposure may be limited by efflux to a greater extent than OM integrity. CCCP treatment also caused an increase in periplasmic AZT exposure (Figure S5) which suggests that inactivation of PMFdependent nucleoside transporters27–29 may cause a build-up of the compound in the periplasm. Taken together, these results further validate our methodology and highlight its utility towards studying the factors which impact a compound’s exposure in bacteria with sub-cellular resolution. Compartment-specific analysis reveals differential compound exposure profiles We next sought to apply this technology to study differences in compartmental exposure profiles across a small panel of azide-bearing compounds whose disposition in terms of periplasmic and cytoplasmic accumulation were previously studied (Figure 7a). However, in order to make comparisons between compounds and across compartments, several potentially confounding factors had to be accounted for. Differences in probe incorporation between strains will affect the rates of product formation within each compartment. To account for this we normalized exposure data within a given strain to a compound such as AZT which exhibits robust exposure in both compartments (Figure S6). Additionally, because structurally-diverse azides have intrinsic differences in reactivity and MS detection efficiency, these properties must also be accounted for before rigorous comparisons can be made between compounds. To control for these variables we ran cell-free in vitro click reactions in E. coli lysate for each azide under conditions identical to those used in bacteria. Each azide reacted in a concentration-dependent fashion to yield click-products which were identified and quantified by MS analysis (Figure 7b, Figure S7). We used the slopes of the best-fit lines for these data to correct for differences in the inherent reactivities of the azides with probe 2 and the efficiencies of MS detection for the resulting products (Figure S6). 16 ACS Paragon Plus Environment

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To study the exposure properties of each molecule in the panel we thus measured the production of click-products in each strain by relative MS quantitation and normalized these values with the in vitro click reaction data. These values were then further normalized to the observed AZT click-product in each compartment to provide comparable relative exposures between azides within each strain and genetic background (Figure 7c-d; Table S3). Consistent with our previous experiments, we found PMA exhibited negligible exposure in the cytoplasm of efflux- competent bacteria and limited, but detectible exposure in the periplasm (2% of AZT). As a point of comparison we also tested the exposure of a related molecule, ethidium bromide monoazide (EtBrN3). EtBrN3 has been used similarly to PMA for live/dead discrimination of bacteria but is known to be less efficiently excluded from living bacteria.31 Consistent with these observations, we found that EtBrN3 exposure was limited in efflux-competent bacteria compared to AZT, but greater than that of PMA, with ~12% of AZT exposure in both compartments (Table S4). To study the exposure profile of chemical matter thought to accumulate in the periplasmic compartment we utilized the known β-lactam, azidocillin. Azidocillin bears an azide functionality and retains on-target activity within bacteria.40 β-lactam antibiotics represent one of the few classes of antibiotics with periplasmic targets; as such they can be optimized for periplasmic exposure without the need to retain permeability across the IM. As a result β-lactams are often highly polar and charged at physiological pH. In comparison to AZT, azidocillin gained roughly equivalent periplasmic exposure (70% of AZT) but had significantly less cytoplasmic exposure (32% of AZT) in efflux-competent bacteria (Figure 7c-d). It is important to note that β-lactams are irreversibly modified by penicillin-binding proteins (PBPs) in the periplasm of bacteria and are likely unavailable for reaction with the probe. Our methodology may thus underestimate exposure in that compartment for this class of compounds. MIC assays showed that, unlike AZT, azidocillin is subject to efflux with a 16-fold shift in MIC between the WT and ∆tolC strains 17 ACS Paragon Plus Environment


(Table S1). Consistent with this observation we found azidocillin had significantly increased periplasmic exposure in E. coli-∆tolC cells (~145% of AZT). The same increase was not evident in the cytoplasmic compartment, consistent with the hypothesis that the IM limits the cytoplasmic exposure of compounds that carry a charge at physiological pH. To supplement the bioactive azides in our panel, we also measured the accumulation of previously-studied azide-bearing fluorophores. The rhodamine fluorophore 5R110-N3 showed significant accumulation in both compartments, but at levels lower than AZT (51-57% of AZT). In comparison, TAMRA-N3, the tetramethyl analog of 5R110-N3, had similar exposure to AZT in the cytoplasm (89% of AZT) and increased exposure in the periplasm (165% of AZT). In contrast to these rhodamine-based fluorophores, 7-azido-3-hydroxycoumarin (7N3HC) registered substantially less exposure than AZT in both compartments (33-42% of AZT). This finding is consistent with the known propensity of coumarin scaffolds to be efflux substrates.41 Indeed, in cells lacking TolC-dependent efflux, 7N3HC achieved equivalent exposure to AZT in both compartments (Figure 7d). As a point of comparison to our MS-based measurements of these fluorophores, we also studied bacteria treated with these molecules by flow cytometry. We found that the fluorescence data broadly correlated with the un-normalized MS data (Figure S8); however, dim fluorophores such as 7N3HC were significantly under-represented. As the fluorescence data could not readily be normalized to correct for differences in azide reactivities or fluorophore brightness, this approach is of limited utility in comparing exposures between compounds and illustrates the benefits of our MS-based detection strategy.


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Figure 7: Compartment-specific analysis of exposure reveals differential exposure profiles between compounds. (a) Chemical structures of the azides used in these studies. (b) In vitro clickproduct formation for the panel of azides shown in (a) as a function of azide concentration. Linear regression were fit and displayed as solid lines. (c) Differences in azide exposure profiles relative to AZT in WT (efflux +) E. coli. OD600 and internal control normalized EIC for each compound were further normalized to in vitro click-reactions (b) and AZT exposure in the same strain to provide ‘Relative Exposure’ values. (d) Differences in azide exposure profiles relative to AZT in ∆tolC (efflux -) E. coli. Data were treated as described in (c). (e) Comparison of Exposure (cytoplasmic + periplasmic exposure) and Distribution (cytoplasmic/periplasmic exposure) across the panel of azides in WT and ∆tolC backgrounds. Data were normalized to AZT for each parameter to enable comparison across the set in each genetic



background. (f) Exposure, Distribution, and Efflux (∆tolC/WT) parameters for each azide normalized as in (e) shown in heat map format. All data are shown as mean values from experiments conducted in triplicate. Error bars represent SD (n = 3). See Figures S6-8 and Tables S1, S3, and S4 for related information.

To provide an intuitive visualization of compound exposure profiles we used the measured compartment-specific exposure data to compute several parameters describing overall exposure, cellular distribution, and efflux potential for given compounds. The ‘Exposure’ index was defined as the sum of cytoplasmic and periplasmic exposures within a given genetic background (i.e. WT or ∆tolC), whereas, the ‘Distribution’ index was defined as the ratio of cytoplasmic and periplasmic exposure (cytoplasmic/periplasmic). Finally, the ‘Efflux’ index was computed as the ratio of exposure in ∆tolC and WT backgrounds (∆tolC/WT) within a given compartment. We found these parameters to be useful for visualizing differences in exposure profiles across compounds. Plots of Exposure vs Distribution in WT and ∆tolC backgrounds facilitate the analysis discussed above and provide a means to track how changes in physicochemical properties impact exposure in bacteria (Figure 7e). Compounds in the lower left quadrant (red) see limited overall exposure that is largely restricted to the periplasmic compartment whereas compounds in the upper right quadrant (green) achieve good exposure in both compartments. While compounds in the upper left quadrant (blue) see good exposure in the periplasm, they have comparably limited cytoplasmic exposure suggesting the IM is a barrier to improved exposure. In contrast, compounds in the lower right quadrant (orange) appear to be most limited by the OM (or efflux); while total exposure is limited, what does get in partitions evenly across the compartments. Similarly, heat maps for each parameter can be used to provide an exposure fingerprint for each compound which is helpful in illustrating which (if any) aspects of exposure are limiting (Figure 7f). For example, while TAMRA-N3 exhibits similar overall exposure to AZT and limited efflux potential, it has poor distribution, suggesting the IM is a limiting barrier to increased exposure for this compound. In comparison, EtBrN3 had significantly less overall exposure but better 20 ACS Paragon Plus Environment

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distribution into the cytoplasm suggesting OM permeability was instead a primary barrier for this compound. 7N3HC also showed good distribution and was able to achieve high exposure in the ∆tolC strain, indicating that OM permeability is not limiting, however it was highly subject to efflux. These analyses should thus prove useful as larger data sets are compiled to provide insight into how physicochemical properties impact a compounds interaction with each of these barriers.

Discussion: While previous studies of compound exposure in Gram-negative bacteria have provided important insights into Gram-negative permeability, broadly applicable rules governing compound exposure have thus far remained elusive. Others have suggested that that further insight will require activity-independent and compartment-specific compound exposure data for large sets of compounds.1 We believe the technology presented here can help address this need by enabling the interrogation of diverse chemical matter in an activity-independent fashion with the resolution necessary to discriminate between intracellular compartments in Gramnegative bacteria. To achieve this level of resolution, we utilized a previously-described method for compartmentspecific streptavidin localization,22 in conjunction with a biotin-cyclooctyne conjugate to produce a sensitive, compartment-specific measure of azide-bearing compound exposure. In addition to the increased resolution provided by our technique, this methodology has several practical benefits over other activity-independent methods of measuring bacterial compound exposure. Previous MS-based methods for measuring compound exposure require wash steps to eliminate extracellular compound; however, once compound-bearing media has been removed, intracellular compound may diffuse out of the bacteria during wash steps, thus potentially biasing quantitation of compound exposure. In our method, the observed species are only



formed if compounds of interest see exposure to streptavidin-bound cyclooctyne probe within a given compartment. Bacteria can thus be washed rigorously without concern for the loss of analyte. The resulting click-products also contain conserved structural features which assist with MS analysis and enable the study of compounds which would not otherwise be readily observable by MS (i.e. benzyl azide due to low molecular weight). The broad spectrum of chemical matter which can be assayed via this methodology thus represents an additional benefit of the approach. While the use of in situ click chemistry confers a number of benefits, care must be taken to account for differences in click-product detection arising from factors unrelated to changes in azide exposure. Differences in azide-specific reaction kinetics and the detection efficiencies of the resulting click-products must thus be controlled for with in vitro click reactions. Similarly, as the effective concentrations of localized probe 2 differ between strains, comparisons between compartments and genetic backgrounds are only possible after normalizing data to an internal reference compound such as AZT. Nonetheless, once these factors are taken into account, our method enables quantitative assessment of the relationships between chemical structure and compartmental exposure. While AZT provides a convenient positive control for compound accumulation in this series of experiments, any compound which accumulates to robust levels could be used for this purpose. Future applications of this method may benefit from a different choice of reference molecules. Reliance on the in situ click-reaction of azides with probe 2 for the generation of signal also imparts notable constraints on the applications of this technology. The cyclooctyne probe must first be localized and retained within the compartment of interest to enable the detection of azide-bearing compounds. The use of biotin-cyclooctyne conjugates for this purpose allows us to leverage active-transport systems in E. coli42 to achieve exposure to the compartmentally localized streptavidin22 for the localization and retention of our probes. Growth conditions or 22 ACS Paragon Plus Environment

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genetic backgrounds which prevent efficient probe localization will thus limit analysis of exposure by this method. Furthermore, the rates of compound permeation in bacteria are generally thought to be on the minute time-scale,12,43,44 whereas the click reactions described here require hours to produce robust signal; this methodology is thus not a viable means of studying the kinetics of compound permeation. However, this difference in rates also suggests that the click reaction should not compete with influx or efflux to bias the analysis of exposure. Thus, the exposure measurements derived from our method are not an instantaneous measure of azide in the cell, but rather a relative measure of click-product produced in the compartment over the course of the experiment. In this aspect, they resemble AUC-based measurements of bioavailability, which are routinely used during optimization of the in vivo exposure of drug candidates. A final constraint is that this approach is not a label-free technology, thus its application is limited to azide-bearing compounds. This was a primary consideration in the selection of the BCN-azide bioorthogonal pair for the technology. While other bioorthogonal pairs are available which could afford significantly faster kinetics (i.e. the tetrazine ligation),19,45 they require larger chemical handles which are less readily available. Comparatively, the azide group represents a minimal mark (3-atoms) which is present on thousands of commercially available compounds and readily installed in a single step from common functional groups such as amino groups46, alcohols47,48, or alkyl halides49. Recent advances in direct azidation of complex molecules50,51 and the high-throughput synthesis of azide libraries52,53 further facilitate the generation of azidederivatized chemical matter. Thus, despite being limited to azide azide-bearing compounds, we believe a diverse range of chemical matter should be readily available for study in this assay. To provide proof-of-concept for our assay we studied the exposure of a panel of widelyavailable azides with known periplasmic or cytoplasmic dispositions. Within this set of compounds, we observed diverse exposure profiles which agreed with the known permeability 23 ACS Paragon Plus Environment


properties of these molecules. AZT, which has a cytoplasmic target, achieved good exposure in both compartments. In contrast, compounds with periplasmic targets such as azidocillin preferentially accumulated in the periplasm and negative control compounds such as PMA exhibited poor exposure in both compartments, consistent with previous studies31. Known chemical and genetic perturbations of membrane integrity and efflux were also found to affect these exposure profiles in the expected fashion. Chemical perturbations known to impact the integrity of the Gram-negative envelop were shown to increase the observed exposure of the otherwise largely impermeable PMA in a compartment-specific manner. The same treatments had little effect on the observed exposure of AZT with the exception of CCCP which caused a modest increase in periplasmic exposure but had no impact on cytoplasmic exposure. Though this might result from disruption of PMF-driven uptake, the lack of a concomitant decrease in cytoplasmic exposure suggests that cytoplasmic AZT uptake may also involve passive permeation or PMF-independent transporters. Comparison of exposure measurements from WT and efflux-deficient (E. coli-∆tolC) strains were consistent with the shifts in MIC’s observed between these strains for the subset of the compounds explored here which have intrinsic antibacterial activity. For the compounds studied here which lacked intrinsic antibacterial activity we also observed exposure profiles consistent with previous studies. 7N3HC was significantly impacted by efflux in our assay, consistent with previous findings that coumarin scaffolds are efflux substrates in E. coli.41 Likewise, 5R110-N3 was previously shown achieve exposure in at least the periplasm of E. coli25 and we were able to recapitulate these results via microscopy, flow cytometry, and MS analysis, to demonstrate that it achieves exposure not only in the periplasm, but also in the cytoplasm of E. coli. In comparison, the structurally-related TAMRA-N3 was biased towards periplasmic exposure in our assay, suggesting this method is amenable to assessing differences in exposure between closely related compounds. Taken together, these studies thus demonstrate that this technology can


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provide an accurate and sensitive means of quantifying relative differences in compartmentspecific compound exposure profiles in Gram-negative bacteria. As interrogations of additional chemical matter progress we anticipate the resolution afforded by this methodology will enable new insight into the factors governing compartmental exposure in Gram-negative bacteria. This assay is currently suitable to be run in 96-well plates with liquid handling automation, and thus should readily support the study of hundreds to thousands of azide-bearing compounds. Looking beyond E. coli, these studies represent a proof-of-principle for the use of similar bioorthogonal pairs as the basis of molecular probes for compound exposure within other contexts. Expanded applications of this approach within eukaryotic cells are thus particularly attractive given the high degree of compartmentalization and resolution needed to study exposure within the organelles of intact cells.

Conclusions: We have developed a novel technology to enable the study of compound exposure profiles with sub-cellular resolution. This methodology provides a sensitive and accurate measure of compartment-specific compound exposure and has the potential to be of significant utility in the interrogation of the factors governing compound exposure within each compartment of Gramnegative bacteria. The ability to quantitatively assess the relative impact of changes to physicochemical properties on compartment specific exposures within a series of compounds may also be a valuable tool in the optimization of drug candidates for Gram-negative antibacterial activity. We thus anticipate that further applications of this technology will benefit the challenging field of antibacterial drug discovery. More broadly, the methods used here should be applicable in a wide variety of multi-compartmental systems to enable the sub-cellular study of compound exposure. Such applications could provide valuable insight into the



differences in permeability barriers between organisms and the corresponding determinants of compound exposure in these contexts.


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Methods and Materials: Graphing and data analysis were done with Microsoft Excel 2010 and GraphPad Prism 7 software. Figures were prepared with Adobe Illustrator CS6 and Fiji (ImageJ) software. Reagents: Bicyclo[6.1.0]nonyne (BCN, 1) was purchased from Synaffix (90%). 4nitrophenylchloroformate was purchased from TCI America (98%). (+)-Biotin-(PEO)3-amine (97%) was purchased from Chem-Impex Int’l. Propidium monoazide (PMA, 20 mM in H2O) was purchased from Biotium. Copper(II) Sulfate pentahydrate (98%), trifluoromethanesulfonic anhydride (98%), sodium azide (99%), and 2-azidoethanol (10% solution in ethanol) were purchased from Oakwood Products, Inc. 3’-azido-3’-deoxythymidin (AZT, 98%), colistin (>15,000 U/mg), polymyxin B nonapeptide hydrochloride, Carbonyl cyanide 3chlorophenylhydrazone (CCCP, >97%), ethidium bromide monoazide (EtBrN3, 95%), ampicillin (>96%), L-Rhamnose monohydrate (>99%), and D-biotin (99%) were purchased from SigmaAldrich. 7-azido-3-hydroxycoumarin (7N3HC, 95%) was purchased from AK Scientific, Inc. . 5carboxyrhodamine 110 azide (5R110-N3) was purchased from BaseClick, GMBH. 5carboxytetramethylrhodamine azide (TAMRA-N3, 95%) was purchased from Lumiprobe. All other solvents and reagents were obtained from Sigma-Aldrich. Statistics: Error bars in all figures represent standard deviation from the mean (SD). Mean values were compared via two-way ANOVA tests using Dunnett’s multiple comparisons tests to determine statistical significance which is indicated as follows: *:P ≤ 0.05, **:P ≤ 0.01, ***:P ≤ 0.001, ****:P ≤ 0.0001. Strain generation: The coding sequence for streptavidin was cloned into the pRham (Lucigen) vector using Gibson assembly (NEB 2x Gibson Assembly master mix). The vector was further modified to include an N-terminal OmpA signal sequence (for the periplasmic construct only), followed by a T7 tag. The C-terminus was modified to include a GSG linker followed by a FLAG



tag. All modifications were made by PCR and ligation via the Q5 site-directed mutagenesis kit (NEB). Sequence-verified plasmid was then used to transform either wild-type (WT, E. coli K-12 (BW25113, Coli Genetic Stock Center, Yale)) or isogenic tolC knock out (∆tolC, E. coli K-12 ∆tolC732::kan (JW5503-1, Coli Genetic Stock Center, Yale)) by electroporation. Electroporationcompetent cells were produced from mid-log-phase cultures with five washes with ice cold 10% (v/v) glycerol, and final resuspension in 1% of the original volume of ice cold 10% (v/v) glycerol. Probe incorporation and lysate preparation: All bacterial cultures were inoculated from frozen glycerol stocks (made from overnight M9 cultures to 20% glycerol) and grown overnight in M9 minimal medium supplemented with 0.2% glycerol and kanamycin (50 µg/mL). The next day the cultures were diluted back to OD600 0.05 and grown to mid log phase. The cultures were then diluted back to OD600 0.05 and grown again to mid log phase to ensure even growth before streptavidin expression was induced by adding L-rhamnose (0.2% w/v). At 10 min post induction the cultures were treated with 2 (20 µM) and then grown in the presence of inducer and 2 for 16 h at 37 °C. The next day the bacteria were diluted to OD600 2.0 in 1-mL aliquots for each sample condition, then pelleted (3220 ×g, 10 min, 20 °C), and washed three times with M9 minimal media. The cells were then re-suspended in 100 µL of M9 medium (0.2% maltose with 0.2% Lrhamnose and kanamycin (50 µg/mL)) and transferred to a 96-well plate (100 µL/well), which was incubated at 37 °C for 20 min prior to compound treatments. At the described endpoints the resulting cultures were pelleted (3220 ×g, 10 min, 20 °C) and washed twice with 250 µL of M9 medium and once with Tris-HCl, pH 8. Each pellet was re-suspended in 50 µL of Tris-HCl pH 8, and 5 µL was transferred to a clear bottom 96-well plate and diluted up to 100 µL for OD600 determination. The remaining bacteria were lysed by the addition of 50 µL of acetonitrile (MeCN) and frozen at -80 °C for >16 h. The lysates were thawed at 37 °C for ca. 20 min, and 100 µL of dimethyl formamide (DMF) was added to each well to complete protein denaturation 54

and release the biotin-conjugates. The lysates were again frozen at -80 °C and thawed prior


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to clarification via centrifugation (3220 ×g, 15 min, 20 °C). The supernatant was transferred to a preconditioned SPE plate (Oasis HLB 96-well µElution plate, 30µm) and diluted with 500 µL of HPLC grade water (+ 0.1% formic acid) to enable cartridge loading. The samples were washed with an additional 250 µL of water then eluted with 60 µL of 50% methanol in water (+ 0.1% formic acid with 50 nM 3 as an internal standard), followed by 60 µL of methanol (+ 0.1% formic acid). The resulting samples were then analyzed by LCMS for the presence of 2 and clickproducts. Mass spectrometry analysis: Samples prepared as described above were analyzed for probe incorporation and click-product formation on an Agilent 1290 UPLC coupled to an Agilent 6550 ESI-QTOF in positive ionization mode for HRMS analysis. Samples were separated over 7 min using reversed-phase liquid chromatography on a Phenomenex Luna C8 column (5 µm particle, 100 Å pore size, 2 x 50 mm) with an Agilent Zorbax SB-C8, 5 µm particle, 2.1 x 12.5 mm guard column (Agilent Part # 821125-915) using gradient elution from 0-99% methanol in water with 0.1% formic acid. We found during the course of our experiments that the use of methanol for the mobile phase during separations was important to minimize sample carry-over as 2 and click-products were found to be much less soluble in acetonitrile. Expected click-product masses were calculated using ChemBioDraw Ultra software. The predicted m/z for each click product (+/- 5 ppm) was then extracted from MS data and peaks with appropriate retention times were integrated to provide intensities. Peak areas were then normalized to internal standards (50 nM 3) and sample OD600 values to correct for sample to sample variability in loading thus providing “Normalized EIC” values. The lower limit of detection for a given species was designated as 3x the standard deviation of signal for the same ion in vehicle controls. For experiments comparing different azides these values were further normalized to the in vitro control experiments and control compounds as described below and in the text.



In vitro click reactions: Four point, 5-fold dilution series of each azide were constructed in triplicate in clarified E. coli lysate at 2× concentration. 50 µL of each of these solutions were then transferred to a 96-well plate containing 50 µL solutions of 400 nM Biotin-BCN in clarified E. coli lysate to initiate the click reactions. The plate was sealed and incubated at 37 °C with shaking for 3 h. The reactions were then quenched with 100 µL of 10 mM 2-azidoethanol in DMF (from 10% solution in ethanol), then stored at -80 °C overnight. The next day samples were thawed at 37 °C for 20 min then spun down at 3220 ×g for 10 min at 20 °C. The samples were passed over SPE plates eluting with methanol as done with bacterial samples and the eluents were analyzed by LCMS for click product formation. These samples were further analyzed by MS/MS to confirm the identified fragment ions corresponded to the expected clickproducts (Figure S7). Fluorescence Microscopy: After click labelling with 5R110-N3 (3 h, 37 °C) bacteria were washed three times with M9 minimal media (0.2% maltose) and once with phosphate buffered saline pH = 7.4 (PBS). The samples were then re-suspended in PBS with FM4-64 membrane dye (5 µg/mL) and Hoechst 34580 nuclear stain (1 µg/mL) and incubated at rt for 30 minutes in the dark. Bacteria were again washed and re-suspended in PBS then 5 µL aliquots of the fluorescently-labeled live E. coli samples were deposited onto thin, 1.2% agar pads prepared on glass microscope slides. The cells were imaged using a Nikon Eclipse Ti inverted microscope with a Nikon halogen illuminator (D-LH/LC), a Sola light engine from Lumencor, and a Clara Interline CCD camera from Andor. A Nikon CFI Plan Apo Lambda DM ×100 Oil objective lens (1.45 NA) was used for phase contrast and fluorescent imaging. 5R110-N3 labelling was imaged in the GFP channel using the FITC-5050A-NTE-ZERO filter set (Semrock), membrane staining was imaged in the TRITC channel using the TRITCB-NTE-NEZO filter set (Semrock), and nucleic acid staining was imaged in the DAPI channel using the BFP-A-Basic-NTE filter set (Semrock). Images were captured by using Nikon Elements software, and exported for figure 30 ACS Paragon Plus Environment

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preparation in ImageJ. Exposure settings for each channel were constant between samples to enable comparison of labelling between strains.

Western blot analysis: OD-normalized cells were directly lysed by boiling in 5 x SDS load buffer and run on a 4–12% Bis-Tris Plus Bolt SDS–PAGE gel (Invitrogen) at 200 V for 30 min – after which the protein was transferred to a nitrocellulose membrane using the iBlot system (Life Technologies). The membrane was blocked for 1 h with 3% bovine serum albumin (BSA)/PBS and then probed with anti-FLAG antibody (1:5000, Agilent Catalog # 200472) while incubating for 1 h at room temperature. The membranes were then washed five times in PBS with 0.1% Tween 20 (PBS-T) for five min. The membrane was then probed with goat-anti-mouse 680 (1:10,000, LI-COR Catalog # 68020) or donkey-anti-mouse 800 (1:10,000, LI-COR Catalog # 32212) secondary antibody. The membranes were then washed five times with PBS-T for five minutes, followed by a fifteen minute wash in PBS. The membranes were scanned on a LI-COR infrared scanner at both 700 and 800 nm wavelengths. Flow Cytometry: The samples taken from MS experiments for OD600 normalization were further diluted 20-fold to provide samples for flow cytometry analysis. Analysis was done on an Attune NxT flow cytometer in the appropriate channels for each fluorophore. Voltages for each channel were tuned to provide the optimal signal-to-noise ratio for each fluorophore prior to analysis. Minimal Inhibitory Concentration (MIC) assay: Susceptibility testing was performed using a standard broth microdilution assay according to CLSI recommendations55 with the following specification: 0.2% L-Rhamnose was added to the test medium to induce streptavidinexpression in the bacterial strains.

Acknowledgments:



The authors would like to thank Dr. Laura McDowell, Dr. Jennifer Campbell, Dr. Jennifer Leeds and Dr. Thomas Krucker for helpful input in the preparation of this manuscript. They would also like to thank Dr. Shengtian Yang for his assistance in the NMR characterization of the synthesized azidocillin.

Funding: B.S. is supported by the Novartis Post-doctoral program.

Author Contributions: Conceptualization, B.S., D.A.S., and B.Y.F.; Methodology, B.S.; Investigation, B.S. and K.V.T.; Resources, B.S., D.D., and W.S.S.; Writing – Original Draft, B.S.; Writing – Review & Editing, B.S., D.A.S., B.Y.F., and F.R.; Visualization, B.S. and D.D.; Supervision, B.Y.F. and F.R.

Declaration of Interests: The authors are all current or former employees of Novartis.

Supporting Information: The Supporting Information is free of charge on the ACS publications website. It contains: optimization of strain growth and probe incorporation conditions (Supplementary Figures 1-2), impact of competition with biotin treatment on probe incorporation (Supplementary Figure 3), the presence of probe 2 over time in bacteria treated with AZT (Supplementary Figure 4), the impact of permeabilizing treatments on AZT exposure (Supplementary Figure 5), the normalizations used to provide Relative Exposure metrics (Supplementary Figure 6), MS/MS spectra confirming the identified click-reaction products (Supplementary Figure 7), comparisons in exposure measurements by MS analysis and flow cytometry for fluorescent azides (Supplementary Figure 8), a table of MIC measurements for the compounds used in these studies (Supplementary Table 1), tables of the statistical measurements preformed during data 32 ACS Paragon Plus Environment

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analysis (Supplementary Tables 2-4), synthetic protocols for the production of 2, 3, and azidocillin.



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