Fidaxomicin (Fdx) is widely used to treat Clostridioides difficile (Cdiff) infections, but the molecular basis of its narrow-spectrum activity in the human gut microbiome remains unknown. Cdiff infections are a leading cause of nosocomial deaths1. Fidaxomicin, which inhibits RNA polymerase, targets Cdiff with minimal effects on gut commensals, reducing recurrence of Cdiff infection2,3. Here we present the cryo-electron microscopy structure of Cdiff RNA polymerase in complex with fidaxomicin and identify a crucial fidaxomicin-binding determinant of Cdiff RNA polymerase that is absent in most gut microbiota such as Proteobacteria and Bacteroidetes. By combining structural, biochemical, genetic and bioinformatic analyses, we establish that a single residue in Cdiff RNA polymerase is a sensitizing element for fidaxomicin narrow-spectrum activity. Our results provide a blueprint for targeted drug design against an important human pathogen.
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Cryo-EM maps and atomic models generated in this paper have been deposited in the Electron Microscopy Data Bank (accession codes EMD-23210) and the Protein Data Bank (accession codes 7L7B). The atomic models used in this paper were obtained from the Protein Data Bank under accession codes 5VI5, 6BZO and 6FLQ. Source data are provided with this paper.
CDC. Antibiotic Resistance Threats in the United States, 2019 (U.S. Department of Health and Human Services, CDC 2019); https://www.cdc.gov/drugresistance/pdf/threats-report/2019-ar-threats-report-508.pdf
Louie, T. J. et al. Fidaxomicin versus vancomycin for Clostridium difficile infection. N. Engl. J. Med. 364, 422–431 (2011).
Crawford, T., Huesgen, E. & Danziger, L. Fidaxomicin: a novel macrocyclic antibiotic for the treatment of Clostridium difficile infection. Am. J. Health Syst. Pharm. 69, 933–943 (2012).
Louie, T. J., Emery, J., Krulicki, W., Byrne, B. & Mah, M. OPT-80 eliminates Clostridium difficile and is sparing of bacteroides species during treatment of C. difficile infection. Antimicrob. Agents Chemother. 53, 261–263 (2009).
Lee, Y. J. et al. Protective factors in the intestinal microbiome against Clostridium difficile infection in recipients of allogeneic hematopoietic stem cell transplantation. J. Infect. Dis. 215, 1117–1123 (2017).
Vincent, C. & Manges, A. R. Antimicrobial use, human gut microbiota and Clostridium difficile colonization and infection. Antibiotics 4, 230–253 (2015).
Boyaci, H. et al. Fidaxomicin jams Mycobacterium tuberculosis RNA polymerase motions needed for initiation via RbpA contacts. eLife 7, e34823 (2018).
Lin, W. et al. Structural basis of transcription inhibition by fidaxomicin (lipiarmycin A3). Mol. Cell 70, 60–71.e15 (2018).
Morichaud, Z., Chaloin, L. & Brodolin, K. Regions 1.2 and 3.2 of the RNA polymerase σ subunit promote DNA melting and attenuate action of the antibiotic lipiarmycin. J. Mol. Biol. 428, 463–476 (2016).
Tupin, A., Gualtieri, M., Leonetti, J. P. & Brodolin, K. The transcription inhibitor lipiarmycin blocks DNA fitting into the RNA polymerase catalytic site. EMBO J. 29, 2527–2537 (2010).
Boyaci, H., Chen, J., Jansen, R., Darst, S. A. & Campbell, E. A. Structures of an RNA polymerase promoter melting intermediate elucidate DNA unwinding. Nature 565, 382–385 (2019).
Chen, J., Boyaci, H. & Campbell, E. A. Diverse and unified mechanisms of transcription initiation in bacteria. Nat. Rev. Microbiol. 19, 95–109 (2021).
Lane, W. J. & Darst, S. A. Molecular evolution of multisubunit RNA polymerases: sequence analysis. J. Mol. Biol. 395, 671–685 (2010).
Mani, N., Dupuy, B. & Sonenshein, A. L. Isolation of RNA polymerase from Clostridium difficile and characterization of glutamate dehydrogenase and rRNA gene promoters in vitro and in vivo. J. Bacteriol. 188, 96–102 (2006).
Cardone, G., Heymann, J. B. & Steven, A. C. One number does not fit all: mapping local variations in resolution in cryo-EM reconstructions. J. Struct. Biol. 184, 226–236 (2013).
Bae, B. et al. Phage T7 Gp2 inhibition of Escherichia coli RNA polymerase involves misappropriation of σ70 domain 1.1. Proc. Natl Acad. Sci. USA 110, 19772–19777 (2013).
Pei, H. H. et al. The δ subunit and NTPase HelD institute a two-pronged mechanism for RNA polymerase recycling. Nat. Commun. 11, 6418 (2020).
Fang, C. et al. The bacterial multidrug resistance regulator BmrR distorts promoter DNA to activate transcription. Nat. Commun. 11, 6284 (2020).
Campbell, E. A. et al. Structure of the bacterial RNA polymerase promoter specificity σ subunit. Mol. Cell 9, 527–539 (2002).
Hubin, E. A. et al. Structure and function of the mycobacterial transcription initiation complex with the essential regulator RbpA. eLife 6, e22520 (2017).
Chen, J. et al. 6S RNA mimics B-form DNA to regulate Escherichia coli RNA polymerase. Mol. Cell 68, 388–397.e386 (2017).
Feklistov, A. et al. RNA polymerase motions during promoter melting. Science 356, 863–866 (2017).
Babakhani, F., Seddon, J. & Sears, P. Comparative microbiological studies of transcription inhibitors fidaxomicin and the rifamycins in Clostridium difficile. Antimicrob. Agents Chemother. 58, 2934–2937 (2014).
Kuehne, S. A. et al. Characterization of the impact of rpoB mutations on the in vitro and in vivo competitive fitness of Clostridium difficile and susceptibility to fidaxomicin. J. Antimicrob. Chemother. 73, 973–980 (2018).
Goldstein, E. J., Babakhani, F. & Citron, D. M. Antimicrobial activities of fidaxomicin. Clin. Infect. Dis. 55, S143–S148 (2012).
Kurabachew, M. et al. Lipiarmycin targets RNA polymerase and has good activity against multidrug-resistant strains of Mycobacterium tuberculosis. J. Antimicrob. Chemother. 62, 713–719 (2008).
Srivastava, A. et al. New target for inhibition of bacterial RNA polymerase: ‘switch region’. Curr. Opin. Microbiol. 14, 532–543 (2011).
Forster, S. C. et al. A human gut bacterial genome and culture collection for improved metagenomic analyses. Nat. Biotechnol. 37, 186–192 (2019).
Qin, J. et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 59–65 (2010).
Wexler, A. G. & Goodman, A. L. An insider’s perspective: Bacteroides as a window into the microbiome. Nat. Microbiol 2, 17026 (2017).
King, C. H. et al. Baseline human gut microbiota profile in healthy people and standard reporting template. PLoS ONE 14, e0206484 (2019).
Corbett, D. et al. Potentiation of antibiotic activity by a novel cationic peptide: potency and spectrum of activity of SPR741. Antimicrob. Agents Chemother. 61, e00200–17 (2017).
Vaara, M. et al. A novel polymyxin derivative that lacks the fatty acid tail and carries only three positive charges has strong synergism with agents excluded by the intact outer membrane. Antimicrob. Agents Chemother. 54, 3341–3346 (2010).
Welch, M. et al. Design parameters to control synthetic gene expression in Escherichia coli. PLoS ONE 4, e7002 (2009).
Salis, H. M., Mirsky, E. A. & Voigt, C. A. Automated design of synthetic ribosome binding sites to control protein expression. Nat. Biotechnol. 27, 946–950 (2009).
Czyz, A., Mooney, R. A., Iaconi, A. & Landick, R. Mycobacterial RNA polymerase requires a U-tract at intrinsic terminators and is aided by NusG at suboptimal terminators. Mbio 5, e00931 (2014).
Yang, X. & Lewis, P. J. Overproduction and purification of recombinant Bacillus subtilis RNA polymerase. Protein Expr. Purif. 59, 86–93 (2008).
Davis, E., Chen, J., Leon, K., Darst, S. A. & Campbell, E. A. Mycobacterial RNA polymerase forms unstable open promoter complexes that are stabilized by CarD. Nucleic Acids Res. 43, 433–445 (2015).
Morin, A. et al. Collaboration gets the most out of software. eLife 2, e01456 (2013).
Suloway, C. et al. Automated molecular microscopy: the new Leginon system. J. Struct. Biol. 151, 41–60 (2005).
Zheng, S. Q. et al. MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat. Methods 14, 331–332 (2017).
Punjani, A., Rubinstein, J. L., Fleet, D. J. & Brubaker, M. A. cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nat. Methods 14, 290–296 (2017).
Zivanov, J. et al. New tools for automated high-resolution cryo-EM structure determination in RELION-3. eLife 7, e42166 (2018).
Punjani, A., Zhang, H. & Fleet, D. J. Non-uniform refinement: adaptive regularization improves single-particle cryo-EM reconstruction. Nat. Methods 17, 1214–1221 (2020).
Heymann, J. B. & Belnap, D. M. Bsoft: image processing and molecular modeling for electron microscopy. J. Struct. Biol. 157, 3–18 (2007).
Waterhouse, A. et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 46, W296–W303 (2018).
Guo, X. et al. Structural basis for NusA stabilized transcriptional pausing. Mol. Cell 69, 816–827.e814 (2018).
Pettersen, E. F. et al. UCSF Chimera—a visualization system for exploratory research and analysis. J. Comput. Chem. 25, 1605–1612 (2004).
Afonine, P. V. et al. Real-space refinement in PHENIX for cryo-EM and crystallography. Acta Crystallogr. D 74, 531–544 (2018).
Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. Features and development of Coot. Acta Crystallogr. D 66, 486–501 (2010).
Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).
Afonine, P. V. et al. New tools for the analysis and validation of cryo-EM maps and atomic models. Acta Crystallogr. D 74, 814–840 (2018).
Toulokhonov, I., Zhang, J., Palangat, M. & Landick, R. A central role of the RNA polymerase trigger loop in active-site rearrangement during transcriptional pausing. Mol. Cell 27, 406–419 (2007).
Weilbaecher, R., Hebron, C., Feng, G. & Landick, R. Termination-altering amino acid substitutions in the β′ subunit of Escherichia coli RNA polymerase identify regions involved in RNA chain elongation. Genes Dev. 8, 2913–2927 (1994).
Burby, P. E. & Simmons, L. A. CRISPR/Cas9 editing of the Bacillus subtilis genome. Bio. Protoc. 7, e2272 (2017).
Hockett, K. L. & Baltrus, D. A. Use of the soft-agar overlay technique to screen for bacterially produced inhibitory compounds. J. Vis. Exp. 119, 55064 (2017).
Wallace, A. C., Laskowski, R. A. & Thornton, J. M. LIGPLOT: a program to generate schematic diagrams of protein-ligand interactions. Protein Eng. 8, 127–134 (1995).
Stamatakis, A. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 22, 2688–2690 (2006).
Letunic, I. & Bork, P. Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucl. Acids Res. 47 (W1), W256–W259 (2019).
We thank S. Darst for helpful discussions during this study; R. Mooney for providing σ70 protein for transcription assays; J. Wang for providing plasmid pJW557; M. Young and J. Yang for guidance in B. subtilis genetics; M. Ebrahim, J. Sotiris and Honkit Ng at The Rockefeller University Evelyn Gruss Lipper Cryo-electron Microscopy Resource Center; and E. Eng and K. Maruthi for collecting cryo-EM data. Some of this work was performed at the Simons Electron Microscopy Center and National Resource for Automated Molecular Microscopy located at the New York Structural Biology Center, supported by grants from the Simons Foundation (SF349247), NYSTAR, the Agouron Institute (F00316), and the NIH (GM103310, OD019994). This research was supported by grants from the NIH to R.L. (GM38660) and E.A.C. (GM114450) and funding from the Revson Foundation to H.B. (CEN5650030).
The authors declare no competing interests.
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Extended data figures and tables
a, pXC026, overexpression plasmid for the Cdiff rpoA, rpoZ, rpoB, and rpoC genes (encoding the α, ω, β, and β′ subunits of Cdiff RNAP, respectively). The β and β′ subunits were fused with an inter-subunit 10-amino-acid (aa) linker (LARHVGGSGA) and a C-terminal Rhinovirus 3C protease-cleavable His10 tag. b, (Top) Size-exclusion chromatography profile for the assembled Cdiff RNAP EσA. (Bottom) Coomassie-stained SDS-PAGE of individual fractions from major peaks. RNAP subunits are labeled on the right of the gel. The yield for Cdiff RNAP EσA from pooled fractions of the second peak was sufficient from single purification and used for biochemistry and structural biology experiments. c, Abortive transcription assay with Cdiff core and EσA using the Cdiff rrnC promoter as DNA template. The transcriptional activity of Cdiff EσA was inhibited with increasing concentrations of Fdx. The transcription assays were repeated three times independently with similar results (n = 3). The result is shown from one representative experiment. The result is shown from one representative experiment. Lane 1, Cdiff RNAP core; lane 2, Cdiff EσA; lane 3, Cdiff EσA with 0.2 µM Fdx added; lane 4, Cdiff EσA with 2 µM Fdx added.
Flow chart showing the image-processing pipeline for the cryo-EM data of Cdiff EσA/Fdx complexes, starting with 6,930 dose-fractionated movies collected on a 300-keV Titan Krios (FEI) equipped with a K3 Summit direct electron detector (Gatan). Movies were frame-aligned and summed using MotionCor241. CTF estimation for each micrograph was calculated with cryoSPARC242. A representative micrograph is shown following processing by MotionCor241. Particles were auto-picked from each micrograph with cryoSPARC242 Blob Picker and then sorted by 2D classification using cryoSPARC2 to assess quality. The selected classes from the 2D classification are shown. After picking and cleaning by 2D classification, the dataset contained 2,415,902 particles. A subset of particles was used to generate an ab initio templates in cryoSPARC2 and 3D heterogeneous refinement was performed with these templates using cryoSPARC242. One major, high-resolution class emerged, which was polished using RELION43 and further cleaned with two more 3D heterogenous refinements. The final 182,390 particles were refined using cryoSPARC Non-Uniform refinement44.
a, Top left, the 3.26 Å-resolution cryo-EM density map of Cdiff EσA/Fdx. Top right, a cross-section of the structure, showing the Fdx. Bottom, same views as above, but colored by local resolution, The boxed region is magnified and displayed as an inset. Density for Fdx is outlined in red15. b, Gold-standard FSC plots of the Cdiff EσA/Fdx complex from cryoSPARC42. The dotted line represents the gold-standard 0.143 FSC cutoff which indicates a nominal resolution of 3.26 Å. c, Angular distribution calculated in cryoSPARC for Cdiff EσA /Fdx particle projections. Heat map shows number of particles for each viewing angle (less = blue, more = red)42. d, Cross-validation FSC plots for map-to-model fitting were calculated between the refined structure of Cdiff EσA/Fdx and the half-map used for refinement (work, red), the other half-map (free, blue), and the full map (black). The dotted black line represents the 0.5 FSC cutoff determined for the full map52.
The lineage-specific β inserts are shown for Cdiff RNAP in dark blue, E. coli RNAP in red16 (PDB ID:4LK1), Bsub RNAP in green17 (PDB ID:6ZCA). The Fdx is shown in green spheres, and the active site Mg2+ is shown as a yellow sphere. Superimposition of the RNAPs from each organism was performed in PyMOL. Only the Cdiff EσA is shown.
Extended Data Fig. 5 Differences in σA–Fdx contacts between Cdiff and Mtb and σA sequence alignment.
a, Conserved regions of Cdiff σA compared to Mtb σA and E. coli σ70. Mtb σA has a much shorter σA NCR than E. coli σ70, but the residues in the short Mtb NCR that contact RbpA are not present in either Cdiff or E. coli20. Mtb RbpA contacts Fdx whereas Cdiff σA makes more contacts to Fdx than does Mtb σA. Black arrows indicate RpbA- σA contacts whereas colored arrows indicate Fdx contacts to σA and RpbA, which includes one shared contact between Mtb and Cdiff σA (red arrow). b, Amino acid-sequence alignment of σA for diverse representatives of bacteria species. Identical residues are highlighted in yellow. Gaps are indicated by dashed lines. Conserved σ regions are labeled underneath the alignment. Colored boxes indicate contacts to Fdx: blue, unique to Cdiff; red, shared between Cdiff and Mtb. The three letter species code is as follows: Cdf, Clostridioides difficile; Bsu, Bacillus subtilis; Bun, Bacteroides uniformis; Eco, E. coli; Mtb, Mycobacterium tuberculosis.
a, Ligplot57 was used to determine contacts between Fdx and Mtb RbpA-EσA (left) and Cdiff EσA (right). Cyan sphere, H2O; green dashed line, hydrogen bond or salt bridge; red arc, van der Waals interactions; red dashed line, cation-π interactions. Note that in ligplot of the Cdiff EσA/Fdx interactions, V1143 (discussed in the text as one of the residues when mutated cause Fdx-resistance) did not make the distance cutoff (4.5 Å) as it was located 4.7 Å away from Fdx. The RNAP β, β' and σA residues are in cyan, pink, and orange respectively. The two Mtb RbpA residues (E17, R10) that interact with Fdx are colored in purple and indicated in the text. The Fdx-interacting residues that do not have corresponding interactions between Cdiff and Mtb are highlighted in red circles. b, The cryo-EM density map of residues interacting with Fdx. Coloring of the residues is consistent with RNAP subunits coloring in Fig. 3, the stick model and cryo-EM densities are color-coded as follows: Pink: β-subunit, cyan: β′- subunit, and orange: σA. Water molecules are shown as red spheres. The residues that form hydrogen bonds (black dotted line) with Fdx are labeled.
Extended Data Fig. 7 In vitro abortive transcription assays used to determine Fdx IC50 of Cdiff and Mtb EσAand EcoEσ70 related to Fig. 2d.
Abortive 32P-RNA products (GpUpG) synthesized on Cdiff rrnC promoter were quantified in the presence of increasing concentrations of Fdx. For each EσA (or Eσ70), three independent experiments were performed and analyzed on the same gel.
Extended Data Fig. 8 Comparative sequence alignment of key structural components of RNAPs that interact with Fdx between Fdx-resistant and sensitive bacteria.
The Fdx interacting regions are labeled on the top of sequence alignment. Locations of residues contacting Fdx in both Cdiff and Mtb are labeled by triangles underneath sequences. For gram-positive bacteria that are sensitive to Fdx, the corresponding residue at Cdiff β′K84 is either K or R, which is highlighted in pink background. For gram-negative bacteria that are resistant to Fdx, the residue at β′K84 is neutral Q, L, or negative E, which is highlighted in blue background. Conserved residues are shown as white letters on a red background, and similar residues are shown as red letters in blue boxes. Cdf, Clostridioides difficile; Mtb, Mycobacterium tuberculosis; Bsu, Bacillus subtilis; Bce, Bacillus cereus, Sab, Staphylococcus aureus; Lcb, Lactobacillus casei; Pmg, Peptococcus magna; Efc, Enterococcus faecium; Eco, Escherichia coli; Hpy, Helicobacter pylori; Pae, Pseudomonas aeruginosa; Bun, Bacteroides uniformis; Boa, Bacteroides ovatus; Pdi, Parabacteroides distasonis; Stm, Salmonella Choleraesuis; Nmc, Neisseria meningitidis.
Extended Data Fig. 9 Phylogenetic tree demonstrating the clade-specific distribution of the identity of the Fdx-sensitizer.
The tree displays the identity of the amino acid corresponding to position β′K84 of Cdiff in the most common species from human gut microbiota. Bacterial species were largely picked from28 and29. The tree was built from 66 small subunit ribosomal RNA sequences by using RaxML58 and iTol59. Species with experimentally confirmed resistance (MIC > 32 µg/mL) and sensitivity (MIC < 0.125 µg/mL) to Fdx are marked with solid and open orange circle respectively25. The amino acid sequence at β′K84 position for corresponding bacteria phyla is denoted by capital letters. The detailed bacterial species are listed in Supplementary Table 4.
a, Transcription assays for Cdiff WT, β′K94E and β′K84Q EσAs are related to Fig. 4b. The Cdiff rrnC promoter (Fig. 2c) was used as a template. b, Transcription assays for Eco WT and β’Q94K Eσ70s related to Fig. 4c. The same Cdiff rrnC promoter was used. For each RNAP, three independent experiments were performed and analyzed on the same gel. c, In vivo assays on agar plates for E. coli WT and Q94K mutant strains. Temperature-sensitive strain RL602 was transformed with control plasmid pRL662 encoding no rpoC, WT rpoC and mutant rpoC-Q94K. Strains were grown overnight at 40 °C. Bacteria containing plasmids expressing rpoC WT and Q94K grew well while the empty plasmid does not cell support growth. d. Antibiotic inhibition assays using E. coli rpoC WT and mutant strains from panel (c). Antibiotics in 3 µL DMSO (Fdx, SPR741, and rifampicin (Rif)) or water (kanamycin (Kan))were pipetted onto overlay soft agar containing the bacteria (see Methods). SPR741 did not inhibit cell growth but increased the potency of Rif and Fdx, suggesting that it increased antibiotic diffusion into the cells. Rif, an antibiotic that targets a region of RNAP distinct from Fdx (± SPR741), and Kan, an antibiotic that targets the ribosome and is not affected by SPR741, equally inhibited the WT and mutant Q94K strains. In contrast, Fdx potently inhibited only the mutant strain, establishing that the Q94E mutation conferred specific sensitivity to Fdx.
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Cao, X., Boyaci, H., Chen, J. et al. Basis of narrow-spectrum activity of fidaxomicin on Clostridioides difficile. Nature 604, 541–545 (2022). https://doi.org/10.1038/s41586-022-04545-z