Abstract
Efflux pumps are a serious challenge for the development of antibacterial agents. Overcoming efflux requires an in-depth understanding of efflux pump functions, specificities and the development of inhibitors. However, the complexities of efflux networks have limited such studies. To address these challenges, we generated Efflux KnockOut-35 (EKO-35), a highly susceptible Escherichia coli strain lacking 35 efflux pumps. We demonstrate the use of this strain by constructing an efflux platform comprising EKO-35 strains individually producing efflux pumps forming tripartite complexes with TolC. This platform was profiled against a curated diverse compound collection, which enabled us to define physicochemical properties that contribute to transport. We also show the E. coli drug efflux network is conditionally essential for growth, and that the platform can be used to investigate efflux pump inhibitor specificities and efflux pump interplay. We believe EKO-35 and the efflux platform will have widespread application for the study of drug efflux.
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Data availability
All supporting data are included in this published article and the Supplementary information. Source data are provided with this paper. EKO-35 and EKO-35-Pore genomic raw sequence data were deposited in GenBank (BioProject ID PRJNA838981). The reference E. coli genome was obtained from NCBI (accession no. CP009273.1). Mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD033975. Source data are provided with this paper.
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Acknowledgements
This study was supported by a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery grant (no. RGPIN-2019-04996) and a Canada Foundation for Innovation (CFI) grant no. JELF 37730 awarded to G.C., a Postgraduate Scholarship (NSERC) awarded to L.K.T., an Ontario Graduate Scholarship awarded to S.Z. and a Canadian Graduate Scholarship awarded to J.A.G. This research was also supported by a Foundation grant from the Canadian Institutes of Health Research (grant no. FRN 143215), infrastructure funding from the CFI, a Research Excellence allocation from the Ontario Research Fund, and a Tier I Canada Research Chair award to E.D.B. We thank K. Klaus and H. Green-Glass for their assistance with aspects of efflux gene inactivation. We also thank T. Bhando for providing the E. coli Pore strain used for the generation of the EKO-35-Pore, H. Zgurskaya for donating the anti-AcrB antibody used in western blotting and C. Murphy and L. Carfrae for assistance with high-throughput susceptibility testing at the Center for Microbial Chemical Biology (CMCB), McMaster University. Last, we thank J. Krieger (Bioinformatics Solutions Inc.) for operating the mass spectrometer for the proteomics experiments and E. Roach (Advanced Analysis Center, University of Guelph) for technical assistance with generation of the scanning electron microscopy images.
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G.C. conceived the research. G.C. and E.D.B. guided the research. G.C., T.T., L.K.T. and C.R.M. designed the experiments. G.C., T.T., L.K.T., S.Z., S.E.G., C.R.M., N.M.K. and J.A.G. performed experiments. L.K.T. and S.Z. analyzed the genome sequence data. L.K.T. prepared the proteomic samples and analyzed the data with guidance from J.G.-M. The high-throughput susceptibility testing was performed by T.T., S.Z., N.M.K., C.R.M. and S.E.G. T.T. and S.Z. analyzed the data. G.C., T.T., L.K.T. and S.Z. wrote the manuscript and all authors commented on and approved the paper.
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Extended data
Extended Data Fig. 1 Plasmid-based complementation of genes harboring nonsynonymous mutations in EKO-35 is detrimental in EKO-35 and wild-type E. coli.
Growth profiling of EKO-35 with ASKA constructs expressing a, pitA b, rspA c, tufA d, yjfC e, wcaC f, gyrB in i, nutrient-rich Lysogeny broth and ii, M9 minimal glucose medium. Solid symbols represent empty vector controls while open symbols represent ASKA expressing constructs. Gene expression was induced with 0.1 mM IPTG and plasmid selection for EKO-35 was achieved using 1 µg/mL in M9 minimal glucose medium and 4 µg/mL in Lysogeny broth. Data points represent mean values of n = 3 biological replicates.
Extended Data Fig. 2 The growth of EKO-35 at acidic and alkaline pH is not restored through plasmid-based complementation of genes in EKO-35 harboring nonsynonymous genomic mutations.
EKO-35 growth is significantly reduced at a, pH 5.0 and is not restored through expression of rspA, pitA, tufa, gyrB, wcaC, and yjfC (P = 6.53 × 10−8, 5.34 × 10−7, 2.52 × 10−8, 3.16 × 10-7, 6.75 × 10−8, 4.80 × 10-8 respectively). Likewise, growth was not restored at b, pH 5.5 (P = 1.00 × 10−7, 1.03 × 10−7, 1.18 × 10−7, 1.45 × 10−6, 4.05 × 10−7, 4.02 × 10−4 respectively). EKO-35 expressing ASKA constructs did not grow at c, 8.5 and d, 9.0. Gene expression was induced with 0.1 mM IPTG and plasmid selection for EKO-35 was achieved using 1 µg/mL chloramphenicol. Data points represent mean values ± s.d. of n = 3 biological end-point readings after 18 h of growth. P-values were calculated by a two-tailed Student’s t-test (****P < 0.0001, ns = not significant) relative to EKO-35 pCA24N.
Extended Data Fig. 3 Plasmid-based complementation of genes in EKO-35 harboring genomic mutations alters biofilm formation in EKO-35 and wild-type E. coli.
Expression of rspA significantly increased biofilm formation in a, wild-type E. coli (P = 2.67 × 10−3) and b, EKO-35 (P = 3.35 × 10−2) in Lysogeny broth, whilst expression of pitA, tufA, gyrB, and yjfC significantly lowered biofilm formation in wild-type E. coli (P = 4.70 × 10−4, 2.98 × 10−5, 6.56 × 10−3, 1.09 × 10−3 respectively) and pitA, tufA, and yjfC in EKO-35 (P = 3.00 × 10−3, 1.65 × 10−1, 8.36 × 10−2, 3.09 × 10−3 respectively). Gene expression was induced using 0.1 mM IPTG and plasmid selection for EKO-35 was achieved using 1 µg/mL chloramphenicol in M9 minimal glucose medium and 4 µg/mL in Lysogeny broth. Data points represent mean values ± s.d. of n = 3 biological end-point readings after 24 h and 48 h of growth in nutrient-rich and -limited media, respectively. P-values were calculated by a two-tailed Student’s t-test (*P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, ns = not significant).
Extended Data Fig. 4
Plasmid-based complementation of genes harboring nonsynonymous mutations in EKO-35 is detrimental in EKO-35 and wild-type E. coli under low oxygen conditions. Growth profiling of EKO-35 in low oxygen environments with ASKA constructs expressing a, pitA b, rspA c, tufA d, yjfC e, wcaC f, gyrB in i, Lysogeny broth with 10 mM KNO3 (1% oxygen) and ii, M9 minimal glucose medium (5% oxygen). Solid symbols represent empty vector controls while open symbols represent ASKA expressing constructs. Gene expression was induced with 0.1 mM IPTG and plasmid maintenance for EKO-35 was achieved using 1 µg/mL chloramphenicol in M9 minimal glucose medium and 4 µg/mL chloramphenicol in Lysogeny broth. Data points represent mean values of n = 3 biological replicates. P-values were calculated by a two-tailed Student’s t-test (*P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, ns = not significant).
Extended Data Fig. 5 Assessing the susceptibility of EKO-35 harboring ASKA plasmids expressing rspA, tufA, pitA, wcaC, gyrB, and yjfC.
Strains were profiled against a, benzalkonium chloride, b, novobiocin, c, trimethoprim, d, synthetic 2, e, synthetic 14, f, synthetic 19. MICs were determined i, without and ii, with chloramphenicol to maintain ASKA plasmids. Gene expression was induced with 0.1 mM IPTG. 25 µg/mL and 4 µg/mL chloramphenicol were used to maintain ASKA plasmids in wild-type E. coli and EKO-35, respectively. Strains were assessed in technical duplicate.
Extended Data Fig. 6 Susceptibility and growth profiling of porinated wild-type (WT) K-12, ∆tolC, and EKO-35 strains in LB at 37 °C.
a, Measurement of growth kinetics revealed the pore marginally extended the lag phase of EKO-35-Pore (P = 0.013), and did not significantly impact the generation time of EKO-35-Pore (P = 0.29) compared to the non-porinated parental strains, which was assessed using n = 3 biological replicates. Statistical analysis was performed using a two-tailed Student’s t-test. b, Heatmap depicting vancomycin susceptibility of the porinated strains. Each strain was tested in technical duplicate and MIC values were normalized to 100%, where green represents the highest MIC value, and white represents the lowest value (see key). Susceptibility of the WT K-12, ∆tolC, and EKO-35 strains + /- the pore was assessed for 52 compounds. The physicochemical properties for each compound that resulted in a 4-fold or greater increase in susceptibility compared to the wild-type strain are presented as individual data points in the box plots. The line through the center of each box indicates the median, and whiskers the minimum and maximum values. Physicochemical properties were calculated using DataWarrior (Version 5.5.0): c, Molecular weight (MW); d, Lipophilicity (logP); e, Aqueous solubility (logS); and f, Polar Surface Area (PSA). n for each strain is defined as the number of active compounds that decreased the MIC value by ≥4-fold compared to the WT K-12 strain as listed in panel g. The bounds of the boxes represent 25% (Q1) to 75% (Q3) of the physicochemical substrate ranked ranges, which are also summarized in panel g. g, Summary of the physicochemical property ranges for each strain. Medians are indicated in parentheses.
Extended Data Fig. 7 Heat maps depicting susceptibility levels of strains expressing efflux pump-encoding genes.
Each strain was tested in technical duplicate and MIC values were normalized to 100% for each compound tested, where orange represents the highest MIC value, and white represents the lowest value (see key). Genes encoding a, AcrEF, b, AcrD, c, AcrB, d, MdtEF, e, MdtBC, f, MacAB, g, MacAB, and h, MexCD were chromosomally integrated into the wild-type strain, a single gene deletion mutant, and EKO-35. Susceptibility testing revealed no changes in the resistance levels of the wild-type or single gene deletion backgrounds, except for c, ΔacrB. EKO-35 was highly susceptible to all compounds tested, revealing susceptibility profiles similar to ΔtolC, and integration of efflux genes into this strain conferred resistance to the known substrates.
Extended Data Fig. 8 Heat maps depicting aminoglycoside susceptibility of the wild-type K-12 strain and an ΔacrD mutant expressing the chromosomally integrated acrD gene (araC::acrD).
Susceptibility testing was performed in both MHB and LB. a, Kanamycin in cation-adjusted Mueller Hinton II Broth (MHB II), b, Kanamycin in Lysogeny broth (LB), c, Gentamicin in MHB II, and d, Gentamicin in LB. The cell inoculum used was 104 cells/mL to replicate susceptibility testing conditions used in previous studies. Each strain was assessed using three technical replicates and MIC values were normalized to 100% for each compound tested, where orange represents the highest MIC value, and white represents the lowest value (see key).
Extended Data Fig. 9 EKO-35 and the efflux platform can be used to assess efflux pump inhibitor specificities.
Bar charts depicting fractional inhibitory concentration index (FICI) values of a, phenylalanine-arginine-β-naphthylamide (PAβN) in combination with fusidic acid and ciprofloxacin, in addition to FICI values of b, 1-(1-naphthylmethyl)-piperazine (NMP) in combination with fusidic acid and ciprofloxacin. The FICI represents the ΣFIC of each drug. The FIC for each drug was determined by dividing the MIC of each drug in combination, by the MIC of each drug alone. ΣFIC = FICA + FICB = (CA/MICA) + (CB/MICB). Synergy (FICI < 0.5), additive (FICI > 0.5–1.0), indifferent (FICI > 1.0–2.0), and antagonistic (FICI > 2.0), as highlighted on each bar chart. Related to Supplementary Datasets 3 and 4.
Extended Data Fig. 10 EKO-35 and the efflux platform can be used to assess efflux pump interplay.
Interplay was not observed for novobiocin in a, EKO-35 and b, EKO-35-Pore or for minocycline in c, EKO-35 and d, EKO-35-Pore. pGDP-2 harboring emrE is denoted as pEmrE. All integrated strains were transformed with the empty vector (pGDP-2). Genes encoding AcrB, AcrEF, AcrD, and MdtEF were integrated into the arabinose operon (araC) of EKO-35. Related to Fig. 5 and Supplementary Dataset 5. Data points represent mean MIC values for which the OD600nm value >0.100 ± s.d. of n = 3 biological replicates. P-values were calculated by a two-tailed Student’s t-test (ns = not significant).
Supplementary information
Supplementary Information
Supplementary Figs. 1–5 and Tables 1–13.
Supplementary Data 1
MICs of various compounds against the wild-type K-12, ΔtolC, EKO-35 and the efflux-integrated EKO-35 strains, which were used to calculate fold change.
Supplementary Data 2
MICs of various compounds against the wild-type (WT)-Pore, ΔtolC-Pore, EKO-35-Pore and the efflux-integrated EKO-35-Pore strains, which were used to calculate fold change.
Supplementary Data 3
The FICI for PAβN in combination with different antibiotics using EKO-35 and the efflux platform.
Supplementary Data 4
The FICI for NMP in combination with different antibiotics using EKO-35 and the efflux platform.
Supplementary Data 5
Assessing efflux pump interplay using EKO-35 and the efflux platform.
Supplementary Data 6
Strains and plasmids used in this study.
Supplementary Data 7
Primers and oligonucleotides used in this study.
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Teelucksingh, T., Thompson, L.K., Zhu, S. et al. A genetic platform to investigate the functions of bacterial drug efflux pumps. Nat Chem Biol 18, 1399–1409 (2022). https://doi.org/10.1038/s41589-022-01119-y
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DOI: https://doi.org/10.1038/s41589-022-01119-y
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