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Deep mutational scan of a drug efflux pump reveals its structure–function landscape

Abstract

Drug efflux is a common resistance mechanism found in bacteria and cancer cells, but studies providing comprehensive functional insights are scarce. In this study, we performed deep mutational scanning (DMS) on the bacterial ABC transporter EfrCD to determine the drug efflux activity profile of more than 1,430 single variants. These systematic measurements revealed that the introduction of negative charges at different locations within the large substrate binding pocket results in strongly increased efflux activity toward positively charged ethidium, whereas additional aromatic residues did not display the same effect. Data analysis in the context of an inward-facing cryogenic electron microscopy structure of EfrCD uncovered a high-affinity binding site, which releases bound drugs through a peristaltic transport mechanism as the transporter transits to its outward-facing conformation. Finally, we identified substitutions resulting in rapid Hoechst influx without affecting the efflux activity for ethidium and daunorubicin. Hence, single mutations can convert EfrCD into a drug-specific ABC importer.

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Fig. 1: Cryo-EM structure of EfrCD.
Fig. 2: DMS pipeline for drug efflux pump EfrCD.
Fig. 3: Sequence–function map of EfrCD.
Fig. 4: DMS analysis of EfrCD.
Fig. 5: Single clone analysis of depleted cluster variants.
Fig. 6: Sensitivity variants investigated at a single clone level.

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Data availability

The cryo-EM map and coordinates for the EfrCD structure have been deposited in the EM Data Bank with accession code EMD-12816 and the Protein Data Bank with accession code 7OCY. NGS datasets have been deposited in the National Center for Biotechnology Information’s Gene Expression Omnibus (GEO) and are accessible through GEO Series accession number GSE189399. Source data are provided with this paper.

Code availability

The code of the Python script used to analyze NGS data was deposited on https://github.com/giameier/DMS_ABC.

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Acknowledgements

We wish to thank all members of the Seeger and Barandun laboratories for scientific discussions. G.M. and M.A.S. thank the Functional Genomics Center Zurich (M. D. Moccia, L. Poveda and W. Qi) for their assistance with deep sequencing. We thank S. Štefanić of the Nanobody Service Facility, University of Zurich, for alpaca immunization. C. Perez is acknowledged for initial help with grid freezing of EfrCD. The electron microscopy data were collected at the Umeå Core Facility for Electron Microscopy, a node of the Cryo-EM Swedish National Facility, funded by the Knut and Alice Wallenberg Foundation, the Erling-Persson Family Foundation, the Kempe Foundation, SciLifeLab, Stockholm University and Umeå University. J.B. acknowledges funding from the Swedish Research Council (2019-02011), the SciLifeLab National Fellows program and Molecular Infection Medicine Sweden. This work was funded by a Swiss National Science Foundation Professorship (PP00P3_144823, to M.A.S.), a Swiss National Science Foundation Project Grant (310030_188817, to M.A.S.), a European Research Council (ERC) Consolidator Grant (MycoRailway, no. 772190, to M.A.S.) and an ERC Starting Grant (PolTube, no. 948655, to J.B.).

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Authors and Affiliations

Authors

Contributions

G.M. and M.A.S. conceived the project. G.M. generated the DMS libraries, established the selection protocol, programmed and validated the NGS data analysis pipeline and performed the ATPase activity assays. S.T. generated the great majority of the single clone variants and analyzed them in growth assays and fluorescence transport assays, together with G.M. Nanobodies were generated by G.M. and L.H. and analyzed by G.M. and S.T. Cryo-EM analyses were performed by K.E., under the supervision of J.B., with EfrCD protein purified by C.A.J.H. Cryo-EM data analysis and model building were performed by K.E. and J.B. L.H. generated preliminary mutational data on alanine variants within the TMDs and supervised G.M. Figures were made and edited by G.M., S.T., K.E., J.B. and M.A.S. All authors wrote the paper.

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Correspondence to Markus A. Seeger.

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Nature Chemical Biology thanks Parjit Kaur, Dirk Slotboom and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Characterization of nanobody Nb_EfrCD#1.

a, Cartoon representation of Nb_EfrCD#1 binding to the extracellular part of EfrCD. Complementary determining regions (CDRs) 1, 2 and 3 are colored in yellow, orange and red, respectively. b, Affinity determination of Nb_EfrCD#1 using grating-coupled interferometry (GCI). EfrCD was immobilized on a WAVEchip and Nb_EfrCD#1 was injected at 0.33, 1, 3, 9 and 27 nM. A 1:1 kinetic binding model was used for data fitting (black curve) and values for on-rate (ka), off-rate (kd) and dissociation constant (KD) are given in the graph. c, ATPase activity of detergent-solubilized EfrCD in the presence and absence of 1 µM Nb_EfrCD#1. Shown is the mean and standard deviation of technical triplicates.

Source data

Extended Data Fig. 2 Variant scores determined in the absence of drugs.

Control experiment in which the DMS libraries were grown in the absence of drugs under otherwise identical conditions as in the competitive growth experiments shown in Fig. 3 (that is, in the presence of inducer nisin). Enrich2 was used to calculate variant scores based on the data obtained from three biological replicates. Enriched variants are colored in red and depleted variants in blue. The same scaling as in Fig. 3 was applied. Diagonal lines in each square correspond to the standard error for the variant score and are scaled such that the entire diagonal corresponds to a standard error of 0.8. Squares with dots have the wild-type amino acid at that position. Gray squares denote variants for which no score was calculated due to high errors or sequencing biases. Randomized residues are indicated on the left of the heat map. NBD residues of the consensus nucleotide binding site are shaded in dark green and residues of the degenerate site in light green. Substituting amino acids are indicated on the top and are grouped into positively charged (+), negatively charged (−), polar-neutral (P), non-polar (NP), aromatic (A) and unique (U).

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Extended Data Fig. 3 Variant filtering.

a, Variant scores determined in the absence of drugs (see Extended Data Fig. 2) were ordered according to the score value. Annotated variants colored in blue deviate strongly from wild-type EfrCD (variant score = 0) and were excluded in the DMS analysis (gray squares in Fig. 3). b, c, d, Standard errors calculated by Enrich2 for all variants ordered according to their value for daunorubicin (b), Hoechst (c) and ethidium (d). Variants exhibiting suspiciously high standard errors are colored in blue and annotated. These variant scores were excluded in the DMS analysis (gray squares in Fig. 3).

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Extended Data Fig. 4 Correlation analysis of calculated versus measured growth rates.

Growth rates for 28 individual variants relative to wild-type EfrCD were determined in the presence of ethidium as two biological replicates. Each growth rate data point is the average of at least two technical replicates. Theoretical growth rates were calculated based on variant scores (see Methods). a, b, Pearson correlation analysis of measured versus calculated growth rates for the two biological replicates, respectively. c, List of analyzed variants and the corresponding calculated and measured growth rates.

Source data

Extended Data Fig. 5 Substitutions towards negatively charged residues enriched in the presence of ethidium.

Surface representation of EfrCD cut into two halves to visualize the substrate binding cavity. Residues with variant scores > 1 in the presence of ethidium when substituted to aspartate or glutamate are depicted in red.

Extended Data Fig. 6 Depleted cluster and Hoechst- sensitivity cluster in the structural context of outward- facing EfrCD.

Side-by-side representation of inward-facing EfrCD structure (a and d) and outward-facing EfrCD homology model (b, c, e and f) based on the coordinates of Sav1866 (PDB: 2HYD). The depleted cluster residues are colored in blue (a-c) and the Hoechst-sensitivity cluster residues in purple (d-f).

Extended Data Fig. 7 Single clone analysis of depleted cluster variants.

Growth of L. lactis NZ9000 ΔlmrCD ΔlmrA expressing the indicated depleted cluster variants in the presence of daunorubicin (red, 8 µM), ethidium (green, 16 µM) or Hoechst (blue, 1.5 µM) is shown as straight line. Cells expressing wild- type EfrCD (wtEfrCD, dashed line) or the inactive E512QEfrD variant (dotted line) were included as controls. The growth experiment was carried out on three separate days, resulting in three biological replicates.

Source data

Extended Data Fig. 8 Schematic drawing of Hoechst assays.

Hoechst accumulation assay in intact cells. Hoechst fluorescence increases due to intercalation of Hoechst into the chromosomal DNA and into the lipid bilayer. Active Hoechst efflux mediated by EfrCD results in a slower increase of fluorescence. b, Hoechst transport into inside-out vesicles (ISOVs). ATP is added from the outside to pump Hoechst into the vesicle lumen. ATP is also consumed by the F1F0-ATPase to pump protons into the ISOV lumen, thereby acidifying the intraluminal milieu. Hoechst fluorescence decreases as a result of protonation of Hoechst due to the lower pH inside the ISOV.

Extended Data Fig. 9 Growth analysis of Hoechst-sensitivity variants.

Growth of L. lactis NZ9000 ΔlmrCD ΔlmrA expressing the indicated Hoechst-sensitivity variants in the presence of daunorubicin (red, 8 µM), ethidium (green, 16 µM) or Hoechst (blue, 1.5 µM) is shown as straight line. Cells expressing wild- type EfrCD (wtEfrCD, dashed line) or the inactive E512QEfrD variant (dotted line) were included as controls. The growth experiment was carried out on three separate days, resulting in three biological replicates.

Source data

Extended Data Fig. 10 Single clone analysis of Hoechst-sensitivity variants.

a, Accumulation of fluorescent drugs Hoechst (upper row) or ethidium (lower row) in intact L. lactis NZ9000 ΔlmrCD ΔlmrA expressing Hoechst-sensitivity variants. Wild-type EfrCD and inactive E512QEfrD variant were included in all measurements. Per individual graph, the experiment performed on the same day is shown. All fluorescence experiments were carried out twice on the same day (technical duplicates) and were performed on two separate days with freshly prepared cells (biological replicates). Representative results from these four replicates are shown. b, Expression levels of variants based on GFP fluorescence of L. lactis NZ9000 ΔlmrCD ΔlmrA expressing transporter variants containing GFP fusion tags. Data are represented as mean + /- standard deviations of technical triplicates.

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Meier, G., Thavarasah, S., Ehrenbolger, K. et al. Deep mutational scan of a drug efflux pump reveals its structure–function landscape. Nat Chem Biol 19, 440–450 (2023). https://doi.org/10.1038/s41589-022-01205-1

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