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. 2018 Aug 8;3(4):e00371-18.
doi: 10.1128/mSphereDirect.00371-18.

Mechanism of High-Level Daptomycin Resistance in Corynebacterium striatum

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Free PMC article

Mechanism of High-Level Daptomycin Resistance in Corynebacterium striatum

Nicholas K Goldner et al. mSphere. .
Free PMC article

Abstract

Daptomycin, a last-line-of-defense antibiotic for treating Gram-positive infections, is experiencing clinical failure against important infectious agents, including Corynebacterium striatum The recent transition of daptomycin to generic status is projected to dramatically increase availability, use, and clinical failure. Here we confirm the genetic mechanism of high-level daptomycin resistance (HLDR; MIC = >256 µg/ml) in C. striatum, which evolved within a patient during daptomycin therapy, a phenotype recapitulated in vitro In all 8 independent cases tested, loss-of-function mutations in phosphatidylglycerol synthase (pgsA2) were necessary and sufficient for high-level daptomycin resistance. Through lipidomic and biochemical analysis, we demonstrate that daptomycin's activity is dependent on the membrane phosphatidylglycerol (PG) concentration. Until now, the verification of PG as the in vivo target of daptomycin has proven difficult since tested cell model systems were not viable without membrane PG. C. striatum becomes daptomycin resistant at a high level by removing PG from the membrane and changing the membrane composition to maintain viability. This work demonstrates that loss-of-function mutation in pgsA2 and the loss of membrane PG are necessary and sufficient to produce high-level resistance to daptomycin in C. striatumIMPORTANCE Antimicrobial resistance threatens the efficacy of antimicrobial treatment options, including last-line-of-defense drugs. Understanding how this resistance develops can help direct antimicrobial stewardship efforts and is critical to designing the next generation of antimicrobial therapies. Here we determine how Corynebacterium striatum, a skin commensal and opportunistic pathogen, evolved high-level resistance to a drug of last resort, daptomycin. Through a single mutation, this pathogen was able to remove the daptomycin's target, phosphatidylglycerol (PG), from the membrane and evade daptomycin's bactericidal activity. We found that additional compensatory changes were not necessary to support the removal of PG and replacement with phosphatidylinositol (PI). The ease with which C. striatum evolved high-level resistance is cause for alarm and highlights the importance of screening new antimicrobials against a wide range of clinical pathogens which may harbor unique capacities for resistance evolution.

Keywords: Corynebacterium; antimicrobial resistance; artificial liposomes; daptomycin; genomics; lipidomics; phosphatidylglycerol; surface plasmon resonance; transcriptomics.

Figures

FIG 1
FIG 1
Available and tested C. striatum isolates. Isolate naming convention: W, WT; R, resistant; P, isolated from a patient; E, evolved from a patient isolate in culture under conditions of daptomycin selection; numbers, different isolate sources; a, b, and c suffixes, isolates collected from the same patient at different time points. All isolates’ genomes were sequenced. WP1a was used as the reference genome. All other genomes were mapped to that genome, and SNPs found in the resistant isolate and not the susceptible isolate from each pair were analyzed further. Transcriptomic analysis was performed on WPIa and RP1b. Lipidomics analysis was performed on the WT strain and the resistant matched pairs of: WP1a:RP1b, WP1c:RE1c, WP2:RE2, and WP5:RE5.
FIG 2
FIG 2
All HLDR isolates have predicted nonfunctional mutations in pgsA2. (A) Structure of PG synthase monomer, with mutations in conserved sites overlaid. (B) Mutation in CDP alcohol phosphatidyl (CDP-AP) transferase active site conserved across species. (C) Mutation in the dimer interface domain. (D) Mutation in substrate binding pocket. (E) Premature stop mutations predicted to produce truncated products.
FIG 3
FIG 3
Lipid metabolism pathway of phosphatidylglycerol and cardiolipin, observed SNPs, and relative abundance changes of key lipids and transcripts between WT and HLDR isolates. (A and B) The PG (A) and CL (B) lipid synthesis pathways were constructed with KEGG. A total of 8 WT and HLDR isolate paired genomes were compared and nonsynonymous single nucleotide polymorphisms identified. The names and structures of the metabolites are on the left, with key lipids colored in red and green. R1 represents the 16:0 carbon chain, and R2 represents the 18:1 carbon chain. The enzyme nomenclature for each enzymatic step and the corresponding genes are located next to the appropriate synthesis arrow. SNP mutations for each enzyme/gene unit are indicated at the far right with the number of mutations among the 8 HLDR isolates, unless no mutations were present in any of the isolates. Except for pgsA2, none of the lipid synthesis genes for PG have SNPs. On the left side, black bars indicate the functional completeness of the PG synthesis pathway. The WT strain proceeds through the entire synthesis pathway producing PG, while the HLDR strain ends at the production of CDP-DAG. The green coloring of the lipid CDP-DAG indicates a 543-fold to 5,946-fold buildup of that metabolite in the HLDR isolates compared to the WT. The red coloring of PG and cardiolipin indicates a reduction of that metabolite in the HLDR isolates compared to the WT with a 369- to 1,990-fold reduction in PG. (C) Expression levels of genes involved in lipid synthesis pathways were not significantly altered in HLDR isolates (P > 0.05). Expression levels of the housekeeping genes rpoA and gyrA were also not significantly altered (P > 0.05).
FIG 4
FIG 4
Lipidomic comparison of WT and resistant paired isolates across mutation types. (A to E) The y axis represents the relative abundance of the important phospholipid between the WT and HLDR isolates. WT-HLDR pairs are associated by color, with WT represented by solid block colors and HLDR represented by black-striped colors. The value corresponding to the lipid that is most abundant in the WT or HLDR isolate has been normalized to 100. Fold changes, where calculable, are listed above the WT and HLDR comparisons; fold change was calculated using (ba)/a, where “b” is the largest value and “a” is the smallest, to maintain a positive number. The structures of the lipid are directly to the right of the graph, where R1 represents the 16:0 carbon chain and R2 represents the 18:1 carbon chain. Statistical analysis was performed with 1-way ANOVA, and the data in every column represent comparisons of the means (*, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001; ****, P ≤ 0.0001).
FIG 5
FIG 5
Comparison of HLDR and WT lipid membranes and surface charge. (A) WP1a and RP1b isolates were imaged with transmission electron microscopy after 1 h with or without the addition of 10 µg/ml daptomycin. WP1a without daptomycin and RP1b with and without daptomycin showed no membrane irregularities, while WP1a with daptomycin showed membrane blebbing and disruption. EDL, electron-dense layer; ETL, electron-transparent layer. (B) All available WT and HLDR isolate pairs were checked for surface membrane charge changes. Charges were not indicative of HLDR, and the differences in the ranges of surface charge between the most and least negative WT and HLDR isolates were not significant, while there was significant variability in charge for both the WT and HLDR isolates compared within MIC group. Statistical analysis was performed with 1-way ANOVA and paired-means analysis (ns, P > 0.05; *, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001; ****, P ≤ 0.0001).
FIG 6
FIG 6
Daptomycin spent-medium growth curves. Growth curves of daptomycin-susceptible S. aureus ATCC 29213 grown in spent media are shown. Spent medium was obtained by growth of resistant isolates (RP1b, RE4, and RE6) or the control isolate (S. aureus [SA] 25923) and uninoculated media, with or without daptomycin (5 µg/ml), for 24 h. After filtration, in triplicate, susceptible S. aureus ATCC 29213 grew only in media that had never contained daptomycin. This indicates lack of daptomycin degradation by HLDR isolates. OD 600, optical density at 600 nm.
FIG 7
FIG 7
Daptomycin binding across concentrations and liposome content. (A to E) The y axis plots the normalized binding of daptomycin to liposomes at various concentration ratios. The x axis shows the types of liposomes tested, which include 1:1 equimolar ratios of PG, PA, or CL to PC and a control liposome made entirely of PC. The data in panel E demonstrate stepwise increases in daptomycin binding to PG. (F) Structures of our lipid of interest. Statistical analysis was performed with 1-way ANOVA, and the data in every column represent comparisons of the means (*, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001; ****, P ≤ 0.0001). All tests were performed in buffer containing 100 mM KCl, 10 mM HEPES (pH 7.0), and 2 nM Ca2+.
FIG 8
FIG 8
Daptomycin activity across concentrations and liposome content. (A to F) The y axis plots percent activity of various concentrations of daptomycin based on absolute fluorescence that is normalized to the fluorescence achieved by the addition of Triton X-100. In panels A to E, the x axis shows the types of liposomes tested, which include 1:1 equimolar ratios of PG, PA, or CL to PC and a control liposome made entirely of PC. (F) The x axis indicates the concentration of daptomycin added to the different liposome compositions. (G) Relation of percent activity of 35 µg/ml of daptomycin (Dap) based on absolute fluorescence that is normalized to the fluorescence achieved by the addition of Triton X-100 (y axis) to the percentage of PG content of the liposome tested with PC contributing the remainder of the required lipid to reach 100% composition (x axis). Daptomycin activity against liposomes is correlated with MIC values for WT and daptomycin-resistant bacterial isolates where the percentage of PG content is known. HDR, highly daptomycin resistant. Statistical analysis was performed with 1-way ANOVA, and the data in every column represent comparisons of the means (*, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001; ****, P ≤ 0.0001). All tests were performed in buffer containing 100 mM KCl, 10 mM HEPES (pH 7.0), and 2 nM Ca2+.

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