Porin-independent accumulation in Pseudomonas enables antibiotic discovery

Abstract

Gram-negative antibiotic development has been hindered by a poor understanding of the types of compounds that can accumulate within these bacteria^1,2. The presence of efflux pumps and substrate-specific outer-membrane porins in Pseudomonas aeruginosa renders this pathogen particularly challenging³. As a result, there are few antibiotic options for P. aeruginosa infections⁴ and its many porins have made the prospect of discovering general accumulation guidelines seem unlikely⁵. Here we assess the whole-cell accumulation of 345 diverse compounds in P. aeruginosa and Escherichia coli. Although certain positively charged compounds permeate both bacterial species, P. aeruginosa is more restrictive compared to E. coli. Computational analysis identified distinct physicochemical properties of small molecules that specifically correlate with P. aeruginosa accumulation, such as formal charge, positive polar surface area and hydrogen bond donor surface area. Mode of uptake studies revealed that most small molecules permeate P. aeruginosa using a porin-independent pathway, thus enabling discovery of general P. aeruginosa accumulation trends with important implications for future antibiotic development. Retrospective antibiotic examples confirmed these trends and these discoveries were then applied to expand the spectrum of activity of a gram-positive-only antibiotic, fusidic acid, into a version that demonstrates a dramatic improvement in antibacterial activity against P. aeruginosa. We anticipate that these discoveries will facilitate the design and development of high-permeating antipseudomonals.

Extended Data Fig. 1.. Confocal fluorescent images of an intrinsically fluorescent compound, Bisindolylmaleimide X (BIM X).

a) The structure of BIM X along with accumulation values. The LC-MS/MS assay reveals BIM X as a poor accumulator in E. coli MG1655, while it is a good accumulator in P. aeruginosa PAO1. Accumulation units are in nmol/10¹² CFU and the error is reported as the s.e.m. b) The standard accumulation assay was performed in P. aeruginosa (PAO1) and E. coli (MG1655) with either BIM X (50 μM) or DMSO until just after the oil removal step. Cells were fixed in 3.7 % formaldehyde in PBS, and fluorescence images were taken with a Zeiss 710 multiphoton confocal microscope through a 63x/1.4 oil objective. All samples were excited at 488 nm with an argon laser, and fluorescence emission was recorded from 599–689 nm. Images were acquired using Zen Black (Zen 2.3). DMSO controls for both cell types tested indicate no autofluorescence. Images are representative of n = 3 biologically independent samples.

Extended Data Fig. 2.. Comparison of species-specific accumulation trends.

a) In the expanded set of primary amines, many compounds that fit the eNTRy rules do not accumulate in P. aeruginosa PAO1, and many compounds that do not fit the eNTRy rules do accumulate in P. aeruginosa PAO1. Low globularity (glob) and low rotatable bonds (RB) are predictive for ~80% of compounds tested in E. coli MG1655, but only 41% of compounds in P. aeruginosa PAO1. Compounds with poor amine steric accessibility, low amphiphilic moment, and multiple charges were removed from this analysis; 154 compounds total are included in the plots, see Compound Master Table for compounds. b) Compounds that accumulate in E. coli, but not in P. aeruginosa, can often be grouped according to structural class, but no additional trends were identified. c) Compounds that accumulate in P. aeruginosa, but not E. coli, are primarily compounds that have high rotatable bonds, high globularity, or both. Accumulation units are reported in nmol/10¹² CFUs. n=3 biologically independent samples. The s.e.m. is reported for accumulation values.

Extended Data Fig. 3.. Accumulation trends, matched molecular pairs, and comparison of P. aeruginosa and E. coli accumulation.

a) Amphiphilic moment (vsurf_A) positively correlates with accumulation in both P. aeruginosa and E. coli. b) Amine steric accessibility is important for accumulation in both P. aeruginosa and E. coli. c) Similarly, compounds with primary amines on secondary carbons tend to accumulate higher than compounds with primary amines on tertiary carbons. d) Matched molecular pairs show a correlation between amine pK_a and accumulation in P. aeruginosa. For structures, see Supporting Table 8. The pKa estimation was calculated using the software MoKa (v3.2.2) from Molecular Discovery suite. e) Distribution of accumulation values in P. aeruginosa vs. E. coli for compounds that accumulate in both bacterial strains (131 compounds plotted, see Compound Master Table for structures). Accumulation levels were lower on average in P. aeruginosa PAO1 relative to E. coli MG1655. Accumulation units are reported in nmol/10¹² CFUs. n=3 biologically independent samples. The s.e.m. is reported for accumulation values. Strains used: E. coli MG1655, P. aeruginosa PAO1.

Extended Data Fig. 4.. Random forest prediction modeling.

a) Random forest prediction model results on data set of all 240 primary amines, structures reported in Supplementary Table 2. ROC plot with 10 repeated cross-validations in the training classification models. b) Relative importance of top 15 descriptors for all 240 primary amines. c) Random forest prediction model results on data set of 50 highest primary amine accumulators and 50 lowest primary amine accumulators (100 amines total; compounds 2.1–2.50; 2.191–2.240 in Supplementary Table 2). d) Relative importance of top 15 descriptors for 100 primary amines. e) Random forest prediction model results on data set of 30 highest primary amine accumulators and 30 lowest primary amine accumulators (60 amines total; compounds 2.1–2.30; 2.211–2.240 in Supplementary Table 2). f) Relative importance of top 15 descriptors for 60 primary amines. Formal charge (h_pavgQ) and hydrogen bond donor surface area (vsa_don) are boxed in red. Early iterations of the model with the incomplete compound library always identified these properties within the top 15 most important.

Extended Data Fig. 5.. Influence of magnesium on accumulation, evaluation of its binding by NMR, and influence of magnesium and PMBN on compound accumulation.

a) Confocal fluorescent images of an intrinsically fluorescent compound, Bisindolylmaleimide X (BIM X) in P. aeruginosa with or without MgCl₂. The standard accumulation assay was performed in P. aeruginosa (PAO1) with either DMSO, BIM X (50 μM), or BIM X (50 μM) + MgCl₂ (1 mM), until just after the oil removal step. Cells were fixed in 3.7 % formaldehyde in PBS, and fluorescence images were taken with a Zeiss 710 multiphoton confocal microscope through a 63x/1.4 oil objective. All samples were excited at 488 nm with an argon laser, and fluorescence emission was recorded from 599–689 nm. Images were acquired using Zen Black (Zen 2.3). The images for P. aeruginosa + DMSO and P. aeruginosa + BIM X are the same as in Extended Data Fig. 1. DMSO controls indicate no autofluorescence. Images are representative of n = 3 biologically independent samples. b) Evaluation of accumulation of compounds in E. coli MG1655 upon co-treatment with MgCl₂ (1 mM). c) Determination of Mg²⁺ interactions with polyamines. Ethylenediaminetetraacetic acid (EDTA), a compound known to chelate to Mg²⁺ in solution, clearly shows a marked chemical shift change in the NMR as well as changes in coupling when comparing EDTA alone to EDTA plus Mg²⁺. When this same experiment was performed with norspermine, there were no observable changes in coupling or chemical shift in the presence of MgCl₂, suggesting a lack of perturbation of any electronic environment on the molecule, thus, a lack of interaction between Mg²⁺ and norspermine. Compounds were evaluated at a final concentration of 1 mM, and MgCl₂ was at a final concentration of 20 mM to maintain the same Mg²⁺-to-compound ratio as in the accumulation experiments. The pD of all solutions was adjusted to 7.2 prior to analysis. d) The same set of compounds as in Extended Data Fig. 5b showed a statistically significant increase in accumulation in P. aeruginosa PAO1 upon co-treatment with the permeabilizer PMBN (8 μg/mL). All structures and accumulation values are listed in Supplementary Table 4b. For samples with additives in Extended Data Fig. 5b & d, compounds 23 and 35 did not meet the mass spec standards and are thus excluded from this analysis. n=3 biologically independent samples. The average and s.e.m are reported for accumulation values. Statistical significance was determined using a two-sample Welch’s t-test (one-tailed test, assuming unequal variance). Statistically significant accumulation differences for compounds in P. aeruginosa PA14 versus P. aeruginosa PA14 with PMBN treatment or E. coli MG1655 versus E. coli MG1655 with MgCl₂ treatment are indicated with asterisks (n.s. not significant, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001).

Extended Data Fig. 6.. Multiple amines and alternative positive charges often aid in accumulation in P. aeruginosa PAO1.

a) Diamines accumulate to significantly higher levels intracellularly in P. aeruginosa relative to their monoamine comparators. b) Diamines containing two primary amines consistently accumulate to a significant extent. c) Diamines containing one primary amine and one secondary or tertiary amine have more variable accumulation levels in P. aeruginosa, depending on hydrogen bond donor ability. d) Accumulation summary of 16 amine, guanidinium, and pyridinium containing compounds (48 compounds total, structures in Supplementary Table 5) in P. aeruginosa PAO1. Compounds are classified as accumulators or non-accumulators based on statistical significance relative to the negative antibiotic controls. e) Examples of side-by-side amine (A), guanidinium (G), and pyridinium (P) comparators and their relative accumulation values in P. aeruginosa PAO1. Amine and guanidinium comparators tend to accumulate to a very similar extent, while pyridiniums often do not accumulate to a significant extent. f) Accumulation of antibiotic controls in three P. aeruginosa strains. Accumulation is consistent with antibacterial activity reported in Extended Data Table 1c. g) Accumulation of representative non-antibiotics in three P. aeruginosa strains. While there is some variance in accumulation levels between strains, high concordance of accumulation classification was observed. Compounds are classified as accumulators or non-accumulators based on statistical significance relative to the negative antibiotic controls. Structures and accumulation values are reported in Supplementary Table 6. Accumulation units are reported in nmol/10¹² CFUs. n=3 biologically independent samples. The average and s.e.m. are reported for accumulation values. Accumulation units are reported in nmol/10¹² CFUs. All compounds were tested in biological triplicate. The average and s.e.m. are reported for accumulation values. Formal charge (FCH) was calculated using MOE.

Extended Data Fig. 7.. Accumulation and activity of FA and various derivatives, and resistance generation in E. coli.

a) Introducing a hydrolyzable amidoxime linker onto FA provides a strategy to increase gram-negative activity and accumulation. Increasing the number of amines on the linker results in improved antibacterial activity and accumulation in two gram-negative species, E. coli MG1655 and P. aeruginosa PAO1, with the 4-amine linker-containing FA derivative (FA prodrug) demonstrating the most potent activity and highest absolute accumulation values. Accumulation values are reported in nmol/10¹² CFUs and represent the concentration of free FA in the cell. n=3 biologically independent samples. The average and s.e.m. are reported for accumulation values. b) E. coli MG1655 mutants resistant to FA prodrug were generated using a serial passage method and exhibit amino acid mutations mapping back to the FA binding pocket of EF-G. Bacteria (1 × 10⁸ CFU/mL) were first inoculated in a standard MIC experiment against both sub- and supra-MIC antibiotic concentrations. The well containing the highest concentration of FA prodrug where bacterial growth was still observed was then isolated and re-subjected to this experiment. c) Acetylating both alcohols of FA greatly disrupts target engagement of FA with EF-G as inferred from MIC values against S. aureus. The diacetylated version of FA prodrug (FA prodrug Ac₂O) loses 4–16x activity against both gram-positive and gram-negative bacterial strains, suggesting that inhibition of EF-G contributes to the observed antibacterial activity of FA prodrug. MICs were performed in MH or LB broth per Clinical and Laboratory Standards Institute (CLSI) guidelines. Accumulation values are reported in nmol/10¹² CFUs and represent the concentration of free FA in the cell. n=3 biologically independent samples. The average and s.e.m. are reported for accumulation values. * Indicates compound solubility limit.

Extended Data Fig. 8.. Mode of uptake and membrane interactions of FA prodrug.

a) (RIGHT) In PBS at 37°C, FA prodrug (10 μg/mL) hydrolyzes to fusidic acid (FA) over a period of 48 hours, as monitored via LCMS. TIC LCMS traces showing the disappearance of FA prodrug and the appearance of FA. Traces are all normalized to 2E6 ion counts. (LEFT) Plasma stability, microsomal stability, and 72-hour IC₅₀ values for FA and FA prodrug. Average percentage errors are reported as s.e.m. IC₅₀ errors reported as s.d. n=3 biologically independent samples. b) Co-treatment with magnesium ions leads to a 32x increase in MIC for gentamicin and FA prodrug, while FA shows no change. Treatment with 80 mM NaCl shows minimal change when compared to the MgCl₂ treated samples. MICs performed in P. aeruginosa PAO1 according to CLSI guidelines, and values are reported in μg/mL. n=3 biologically independent samples c) FA prodrug, gentamicin, and colistin all permeabilize the outer membrane of P. aeruginosa PAO1 to the membrane impermeable fluorophore NPN at a 10-minute time point, while treatment with FA shows no effect. Error bars represent the standard deviation from the average of RFUs. n=3 biologically independent samples d) Treatment with FA prodrug leads to dose-dependent inner membrane depolarization in P. aeruginosa PAO1, quantified using the potentiometric dye DiSC₃ (5), while treatment with FA shows no effect. Concentrations of FA and FA prodrug are listed in μg/mL. 1% Triton X was used as the positive control, while 2% DMSO was used as the negative control. n=3 biologically independent samples.

Fig. 1.. Assessment of antibiotic controls in P. aeruginosa accumulation assay and evaluation of eNTRy rules predictability in P. aeruginosa.

a) Inactive antibiotics show low accumulation in P. aeruginosa PAO1, while active antibiotics are high accumulators. Statistically significant accumulation over the average of the low-accumulating controls is indicated with asterisks (***P<0.001; tetracycline (P=7.6E-5), ciprofloxacin (P=3.1E-5), tigecycline (P=1.6E-8).). b) Low-accumulating antibiotics show an increase in accumulation with treatment of polymyxin B nonapeptide (PMBN, 8 μg/mL). Statistically significant accumulation differences for low accumulating compounds in permeabilized and non-permeabilized PAO1 are indicated with asterisks (**P < 0.01, ****P< 0.0001; fusidic acid (P=5.8E-5), valnemulin (P=1.8E-3), novobiocin (P=3.0E-3)). c) Efflux substrates show increased accumulation in the efflux pump knockout strain, P. aeruginosa PAΔ6, whereas non-substrate vancomycin shows no significant (P=1.9E-2) increase. Statistically significant accumulation differences for low accumulating compounds in wild-type P. aeruginosa PAO1 and efflux deficient P. aeruginosa are indicated with asterisks (*P<0.05, **P<0.01, ***P<0.001, ****P<0.0001; chloramphenicol (P=7.6E-4), valnemulin (P=4.5E-3), nalidixic acid (P=9E-6), trimethoprim (P=2E-6), and tedizolid (P = 5.3E-4)). d) The influence of amines on accumulation in P. aeruginosa PAO1 for three different series of compounds. pK_a values calculated using Chemaxon. e) The influence of globularity and rotatable bonds on accumulation in P. aeruginosa PAO1 versus E. coli MG1655 for 40 primary amines. Low globularity and low rotatable bonds are predictive for ~80% of compounds tested in E. coli, but only ~50% for P. aeruginosa. Structures of all compounds are in Supplementary Table 1 and Compound Master Table, and data for E. coli is taken from Richter and co. For all figure panels, the average and s.e.m. are reported for accumulation values (nmol/10¹² CFUs). n=3 biologically independent samples. Statistical significance was determined using a two-sample Welch’s t-test (one-tailed test, assuming unequal variance).

Fig. 2.. Importance of ClogD_7.4, Hydrogen Bond Donor Surface Area, and positive charge descriptors for accumulation in P. aeruginosa PAO1.

a) A set of 345 compounds, including 240 primary amines, was evaluated for accumulation in P. aeruginosa PAO1. All accumulating compounds have a positive charge. Structures, properties, and accumulation are reported in Supplementary Tables 2 and 3 and includes all 67 compounds from Supplementary Table 1. b) Analysis of 240 primary amines, correlation of Formal Charge or Positive Polar Surface Area and HBD Surface Area with compound accumulation in P. aeruginosa PAO1. In this analysis, compounds with HBD Surface Area ≥23 and either Positive Polar Surface Area ≥ 80 or Formal Charge ≥ 0.98 were most likely to accumulate. >80% of compounds that met these criteria were accumulators, shown in the green box. 113 compounds met the criteria, and 92 of them were accumulators, while 21 were non-accumulators. 127 compounds did not meet the criteria, and 55 of them were accumulators and 72 were non-accumulators. c) Increasing HBD Surface Area leads to an increase in accumulation in P. aeruginosa PAO1. d) Increasing the Positive Polar Surface Area positively correlates with accumulation in P. aeruginosa PAO1. e) Increasing the Formal Charge of a molecule through pK_a modulation of amines or other ionizable atoms increases accumulation in P. aeruginosa PAO1. Calculated pK_a values for basic functionalities are shown in blue, and calculated pK_a values for acidic functionalities are shown in red. Accumulation units are reported in nmol/10¹² CFUs. n=3 biologically independent samples. The average and s.e.m. are reported for accumulation values. ClogD_7.4 was calculated using the online compound property calculation software FAFdrugs. Formal charge (FCH), HBD Surface Area (vsa_don in MOE), and Positive Polar Surface Area (Q_vsa_PPos in MOE) were calculated in MOE. pK_a values were calculated using Chemaxon.

Fig. 2.. Importance of ClogD_7.4, Hydrogen Bond Donor Surface Area, and positive charge descriptors for accumulation in P. aeruginosa PAO1.

a) A set of 345 compounds, including 240 primary amines, was evaluated for accumulation in P. aeruginosa PAO1. All accumulating compounds have a positive charge. Structures, properties, and accumulation are reported in Supplementary Tables 2 and 3 and includes all 67 compounds from Supplementary Table 1. b) Analysis of 240 primary amines, correlation of Formal Charge or Positive Polar Surface Area and HBD Surface Area with compound accumulation in P. aeruginosa PAO1. In this analysis, compounds with HBD Surface Area ≥23 and either Positive Polar Surface Area ≥ 80 or Formal Charge ≥ 0.98 were most likely to accumulate. >80% of compounds that met these criteria were accumulators, shown in the green box. 113 compounds met the criteria, and 92 of them were accumulators, while 21 were non-accumulators. 127 compounds did not meet the criteria, and 55 of them were accumulators and 72 were non-accumulators. c) Increasing HBD Surface Area leads to an increase in accumulation in P. aeruginosa PAO1. d) Increasing the Positive Polar Surface Area positively correlates with accumulation in P. aeruginosa PAO1. e) Increasing the Formal Charge of a molecule through pK_a modulation of amines or other ionizable atoms increases accumulation in P. aeruginosa PAO1. Calculated pK_a values for basic functionalities are shown in blue, and calculated pK_a values for acidic functionalities are shown in red. Accumulation units are reported in nmol/10¹² CFUs. n=3 biologically independent samples. The average and s.e.m. are reported for accumulation values. ClogD_7.4 was calculated using the online compound property calculation software FAFdrugs. Formal charge (FCH), HBD Surface Area (vsa_don in MOE), and Positive Polar Surface Area (Q_vsa_PPos in MOE) were calculated in MOE. pK_a values were calculated using Chemaxon.

Fig. 2.. Importance of ClogD_7.4, Hydrogen Bond Donor Surface Area, and positive charge descriptors for accumulation in P. aeruginosa PAO1.

a) A set of 345 compounds, including 240 primary amines, was evaluated for accumulation in P. aeruginosa PAO1. All accumulating compounds have a positive charge. Structures, properties, and accumulation are reported in Supplementary Tables 2 and 3 and includes all 67 compounds from Supplementary Table 1. b) Analysis of 240 primary amines, correlation of Formal Charge or Positive Polar Surface Area and HBD Surface Area with compound accumulation in P. aeruginosa PAO1. In this analysis, compounds with HBD Surface Area ≥23 and either Positive Polar Surface Area ≥ 80 or Formal Charge ≥ 0.98 were most likely to accumulate. >80% of compounds that met these criteria were accumulators, shown in the green box. 113 compounds met the criteria, and 92 of them were accumulators, while 21 were non-accumulators. 127 compounds did not meet the criteria, and 55 of them were accumulators and 72 were non-accumulators. c) Increasing HBD Surface Area leads to an increase in accumulation in P. aeruginosa PAO1. d) Increasing the Positive Polar Surface Area positively correlates with accumulation in P. aeruginosa PAO1. e) Increasing the Formal Charge of a molecule through pK_a modulation of amines or other ionizable atoms increases accumulation in P. aeruginosa PAO1. Calculated pK_a values for basic functionalities are shown in blue, and calculated pK_a values for acidic functionalities are shown in red. Accumulation units are reported in nmol/10¹² CFUs. n=3 biologically independent samples. The average and s.e.m. are reported for accumulation values. ClogD_7.4 was calculated using the online compound property calculation software FAFdrugs. Formal charge (FCH), HBD Surface Area (vsa_don in MOE), and Positive Polar Surface Area (Q_vsa_PPos in MOE) were calculated in MOE. pK_a values were calculated using Chemaxon.

Fig. 3.. Evaluation of accumulation in a porin deficient strain and in the presence of magnesium.

a) Compounds tested in P. aeruginosa PA14 with all 40 putative porins knocked out (PA14 Δ40) show minimal accumulation differences relative to the parental strain PA14, suggesting a porin-independent mode of uptake. b) The same set of compounds shows a significant decrease in accumulation upon co-treatment with MgCl₂ (1 mM), suggesting self-promoted uptake as the primary mode of entry for these compounds. The same PA14 data is used in Fig. 3a and 3b. All structures and accumulation values are listed in Supplementary Table 4a. n=3 biologically independent samples. The average and s.e.m are reported for accumulation values. Statistical significance was determined using a two-sample Welch’s t-test (one-tailed test, assuming unequal variance). Statistically significant accumulation differences for compounds in P. aeruginosa PA14 versus P. aeruginosa PA14 with MgCl₂ treatment or P. aeruginosa PA14 Δ40 are indicated with asterisks (n.s. not significant, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001).

Fig. 4.. Six retrospective examples where an antibiotic derivative is more active (≥4-fold) against P. aeruginosa than the parent.

Analysis shows that the derivatives with improved antibacterial activity meet the HBD surface area and charge requirements for accumulation in P. aeruginosa (as shown by the green box). Target engagement (inferred from MIC values against efflux-deficient strains) is similar for most of the compound pairs (for structures of each antibiotic, see Extended Data Table 2), suggesting that the improved antibiotic activity against P. aeruginosa is due to an increase in accumulation; this has been explicitly shown tetracycline/tigecycline pair (Fig. 1a).

Fig. 5.. Development of PA-active fusidic acid (FA) derivative.

a) FA has potent activity against gram-positive bacteria, but no activity against P. aeruginosa PAO1. However, when co-administering the membrane permeabilizer PMBN (8 μg/mL), FA has good antibacterial activity, indicating that the target (EF-G) can be exploited, and if FA could accumulate, it would be active against wild-type P. aeruginosa. To improve accumulation using the predictive guidelines for PA, while maintaining the necessary acid for FA activity, an amidoxime prodrug moiety was generated with a polyamine linker. The prodrug is cleaved through hydrolysis to release FA inside the cell, leading to an MIC value of 8 μg/mL, a 128-fold improvement in activity against wild-type P. aeruginosa. b) FA accumulation in P. aeruginosa PAO1 is enhanced in the presence of PMBN (8 μg/mL). FA prodrug shows >20x higher accumulation levels that FA. As the prodrug hydrolyzes under assay conditions, the accumulation of FA is reported for FA prodrug. c) FA does not meet the predictive guidelines for accumulation in P. aeruginosa, while FA prodrug fits the described physicochemical properties, highlighted in the green box. d) FA prodrug possesses 64–256x improved activity relative to FA against a panel of 75 clinical isolates of P. aeruginosa. MICs were performed in LB Lennox broth according to the CLSI guidelines in biological triplicate. Accumulation units are reported in nmol/10¹² CFUs. n=3 biologically independent samples. The average and s.e.m are reported for accumulation values. Statistical significance was determined using a two-sample Welch’s t-test (one-tailed test, assuming unequal variance). Statistically significant accumulation differences for fusidic acid in the presence of PBMN or with the prodrug linker are indicated with asterisks (**P < 0.01, ****P < 0.0001)