Abstract
Gram-negative antibiotic development has been hindered by a poor understanding of the types of compounds that can accumulate within these bacteria1,2. 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.
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Data availability
All data supporting the findings of this study are available in the paper and the Supplementary Information. Source data are provided with this paper.
Code availability
Source code for data analysis and model training can be found at https://github.com/HergenrotherLab/GramNegAccum.
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Acknowledgements
We thank the NIH (AI136773), the University of Illinois and Roche for support of this work. M.K.G. is a member of the NIH Chemistry-Biology Interface Training Grant (T32-GM136629). We thank L. Li (Metabolomics Center, Roy J. Carver Biotechnology Center, UIUC and Duke University School of Medicine Proteomics and Metabolomics Core Facility) for all LC–MS/MS analysis. We thank D. Olson, L. Zhu and N. Duay at the School of Chemical Sciences NMR Laboratory at UIUC for NMR services. We thank A. Cyphersmith and the Core Facilities at the Carl Woese Institute for Genomic Biology for assistance with confocal imaging. We are grateful to all past Hergenrother laboratory members who have contributed compounds to the complexity-to-diversity collection and to B. Drown, who wrote the code used for the random forest analysis. We thank H. Zgurskaya for the generous donation of the P. aeruginosa PA01 Δ6 and PA01 Δ6-pore strains and D. Bumann for the generous donation of the P. aeruginosa PA14 and PA14 Δ40 strain. We are further grateful to collaborators at Roche, including C. Kramer who helped establish this collaboration early on and G. M. Daniel for his guidance of the collaboration as alliance manager.
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P.J.H. and E.J.G. conceived the study. E.J.G. performed accumulation analyses, computational analyses and mode of uptake studies with assistance of M.K.G. E.J.G., M.R.L., M.K.G. and S.J.P. synthesized compounds in the test set. M.G.C., A.G. and M.K.G. synthesized FA derivatives. E.J.G., A.G., M.G.C. and M.K.G. performed MICs. C.B. and L.G. provided compounds and assisted with analysis of the data. E.J.G. and P.J.H. wrote this manuscript and it was approved by all authors. P.J.H. supervised this research.
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The University of Illinois has filed patents on some of the compounds described herein on which P.J.H. and M.G.C. are inventors.
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Extended data figures and tables
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 pKa and accumulation in P. aeruginosa. For structures, see Supplementary 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 modelling.
a) Random forest prediction model results on dataset 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 dataset 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 dataset 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 cotreatment 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 cotreatment 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) (LEFT) In PBS at 37 °C, FA prodrug (10 µg/ml) hydrolyses to FA (FA) over a period of 48 h, as monitored via LC–MS. TIC LC–MS traces showing the disappearance of FA prodrug and the appearance of FA. Traces are all normalized to 2E6 ion counts. (RIGHT) 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) Cotreatment 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.
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Synthetic methods and NMR spectra for reported compounds.
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Supplementary Tables 1–8 and the Compound Master Table.
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Geddes, E.J., Gugger, M.K., Garcia, A. et al. Porin-independent accumulation in Pseudomonas enables antibiotic discovery. Nature 624, 145–153 (2023). https://doi.org/10.1038/s41586-023-06760-8
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DOI: https://doi.org/10.1038/s41586-023-06760-8
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