Abstract Objectives Although meropenem is widely used to treat Burkholderia infections, the response of Burkholderia pathogens to this antibiotic is largely unexplored. Methods Burkholderia thailandensis, a model for Burkholderia spp., particularly Burkholderia mallei and Burkholderia pseudomallei, was challenged with a lethal level of meropenem and survivors were isolated. The genomes of two of the isolates were analysed to identify mutated genes and these genes were then specifically examined in more isolates to profile mutation diversity. Mutants were characterized to investigate the biological basis underlying survival against meropenem. Results One of two genes associated with tRNA metabolism [metG or trmD, encoding methionyl-tRNA synthetase or tRNA (guanine-N1)-methyltransferase, respectively] was found to be mutated in the two survivors. A single nucleotide substitution and a frameshift mutation were found in metG and trmD, respectively. Five different substitution mutations affecting methionine- or tRNA-binding sites were found in metG during further screening. The mutants exhibited slowed growth and increased tolerance not only to meropenem but also various other antibiotics. This tolerance required intact RelA, a key stringent response. Conclusions Specific mutations affecting the tRNA pool, particularly those in metG, play a pivotal role in the B. thailandensis response to meropenem challenge. This mechanism of antibiotic tolerance is important because it can reduce the effectiveness of meropenem and thereby facilitate chronic infection by Burkholderia pathogens. In addition, specific mutations found in MetG will prove useful in the effort to develop new drugs to completely inhibit this essential enzyme, while preventing stringent-response-mediated antibiotic tolerance in pathogens. Introduction Burkholderia pseudomallei is the aetiological agent of melioidosis, which is endemic to South-East Asia and north-eastern Australia.1,Burkholderia mallei, the cause of glanders, is a species derived from a clone of B. pseudomallei.2,Burkholderia thailandensis is closely related to these pathogens, but is generally considered avirulent in humans and therefore has been used as a model species for these other dangerous pathogens in laboratory research.3,4 In these Burkholderia species, a class A β-lactamase PenL (also previously called penA3–5) (BTH_II1450 from B. thailandensis strain E264) acts as a first-line defence against penicillin derivatives (including amoxicillin and ampicillin) and cephalosporins (including ceftazidime) through mutations that lead to substrate spectrum extension.3–6 PenL from B. thailandensis is highly conserved in pathogenic Burkholderia species including B. pseudomallei, B. mallei and Burkholderia cenocepacia.2,7,8 Ceftazidime and meropenem (used separately or in combination) constitute the major antibiotic regimens used to treat infections by Burkholderia pathogens.9,10 Whereas resistance to ceftazidime occurs through a mutation in penL, development of meropenem resistance is not as straightforward. Strains of B. pseudomallei and B. cenocepacia with decreased meropenem susceptibility have been reported recently.11,12 In B. cenocepacia strains, increased expression of the phenylacetic acid degradation pathway appeared to be involved.12 These reports suggest that the mechanisms underlying meropenem resistance in Burkholderia spp. need to be carefully explored. Carbapenem resistance is a serious threat in general, with an increasing incidence in recent years and few therapeutic options for treating infections caused by carbapenem-resistant bacteria, including strains of Enterobacteriaceae and Klebsiella pneumoniae.13 In this study, we demonstrate that mutations can develop in specific genes associated with tRNA metabolism in Burkholderia, increasing survival in the response to meropenem. We show that MetG with a specific amino acid substitution is one of the major routes leading to the stringent response, which confers antibiotic tolerance. This mechanism involving the stringent response is the first that has been observed to protect Burkholderia spp. from the clinically important antibiotic meropenem. Materials and methods Bacterial strains and cultures All Escherichia coli strains were grown in LB medium and all B. thailandensis strains were grown in LB or AB minimal media containing 0.25% glucose (ABG)14 at 37 °C. The antibiotic concentrations used for E. coli were: tetracycline, 10 mg/L; ampicillin, 100 mg/L. For B. thailandensis, the concentration of tetracycline used was 50 mg/L. Selection of meropenem-resistant mutants For the isolation of meropenem-resistant mutants, a single colony of WT B. thailandensis strain E264 was grown overnight in 2 mL of Mueller–Hinton broth at 37 °C with shaking at 250 rpm. The overnight culture was washed with fresh Mueller–Hinton and the cells were resuspended in 2 mL of fresh Mueller–Hinton broth to ∼109 cfu/mL. Cell suspensions of 100 μL were spread on Mueller–Hinton agar plates containing 4–6 mg/L meropenem (4–6 × MIC), which were subsequently incubated for 48 h at 37 °C until the meropenem-resistant mutants formed visible colonies. Determination of MIC values for meropenem-resistant mutants The MIC values of ceftazidime were determined using the agar dilution method as described by Wiegand et al.15 Briefly, a single colony of each strain grown on Mueller–Hinton agar was inoculated in 2 mL of Mueller–Hinton broth and incubated overnight with shaking at 250 rpm at 37 °C. Overnight cultures were diluted with fresh Mueller–Hinton such that the bacterial suspensions contained ∼107 cfu/mL. Using a multichannel micropipette, 1 μL of the diluted bacterial suspension was placed on individual Mueller–Hinton agar plates each containing a concentration of antibiotics over the appropriate range and incubated at 37 °C for 16 h. The MIC was recorded as the lowest concentration of antibiotic at which no visible bacterial growth was observed in the spots containing the bacterial inoculum. The number of cfu was determined by spreading 100 μL of the appropriately diluted bacterial suspensions on Mueller–Hinton agar plates, followed by incubation for 24 h at 37 °C and counting of viable colonies. The average values were calculated from triplicate experiments. Sequencing of meropenem-resistant mutants To map the mutations conferring meropenem resistance in B. thailandensis mutants, genomic DNA of the selected mutant was purified using a Wizard Genomic DNA Purification Kit (Promega, Madison, WI, USA) and whole-genome sequencing was carried out using HiSeq 2000 (Illumina, San Diego, CA, USA) services at Macrogen Inc. (Seoul, South Korea). A DNA library of genomic DNA fragments was prepared according to the Illumina protocols and was validated using an Agilent Bioanalyzer. The sequences were read using the 101 bp paired-end reading module. Sequence data were analysed using CLC genomics workbench software (CLC Bio, Redwood City, CA, USA). Briefly, raw sequence data were paired-trimmed and the resulting reads were mapped to the B. thailandensis E264 (accession numbers CM000438.1 and CM000439.1) reference genome followed by SNP and deletion/insertion polymorphism (DIP) detection analysis. Localization of mutations in metG and trmD To identify metG mutations (BTH_I0856 in the B. thailandensis E264 genome) in additional meropenem-resistant mutants, we PCR amplified and sequenced the coding region of the gene and the flanking regions. The genomic DNA of each mutant was purified using the Wizard Genomic DNA Purification Kit (Promega, Madison, WI, USA) and was used as the template for PCR amplification of metG and the flanking regions to obtain a 2853 bp amplicon (243 bp upstream from the start codon of the gene to 297 bp downstream of the stop codon). PCR reactions were carried out in a 50 μL reaction mixture containing 1 U of KOD FX Neo polymerase (Toyobo, Osaka, Japan), 20 pmol of the primers metG-F (5′-GAGCGGCGTAGTCTGTCTTT-3′) and metG-R (5′-TTTCGGGTATTCCAGTCTCG-3′), 10 ng of template DNA, 10 μL of dNTP mix (2 mM each) and 25 μL of KOD FX Neo buffer. Cycling conditions were as follows: a pre-denaturation step (94 °C for 2 min), a 35 cycle amplification step (35 cycles at 98 °C for 10 s, 59.6 °C for 30 s and 68 °C for 1.5 min) and a final extension step (72 °C for 10 min). The gel-purified PCR products were sequenced with a 3730XL DNA Analyzer (Applied Biosystems, Foster City, CA, USA) in both directions using primers metG-F, metG-R, metG-MF (5′-GATCTATCTCGCGTTGAAGGA-3′) and metG-MR (5′-GAGATGAACGGCGATGCT-3′). Construction of the relA null mutants The relA gene (BTH_I2597) was disrupted as follows. First, two fragments each containing upstream or downstream flanking regions and parts of the coding region of relA were PCR amplified as follows. The 556 bp fragment containing the first 25 codons of relA and its upstream region, relA_fragment 1, was amplified using the primer pairs relA_FG1_FSALI (5′-ATATATGTCGACCGCGTCATAATATGCGGTTC-3′), which contains a SalI recognition site (underlined), and relA_FG1_R (5′-CTCGCGCACGAACGCGA-3′). The second 507 bp fragment containing the last 10 codons of relA and some of the downstream region, relA_fragment 2, was amplified using the primer pairs relA_fg2_F (5′-GGGGTCGTTCGGGCGGC-3′) and relA_fg2_RSACI (5′-ATATATGAGCTCGTCAGGCAAGCGTATCGAA-3′), which contains a SacI recognition site (underlined). Then, the PCR products were digested with SalI and SacI, respectively, and ligated into SalI and SacI double-digested pUC19 along with a tetr cassette. The tetr cassette was previously amplified from pRK415K,16 using KOD FX Neo polymerase (Toyobo Co., Ltd., Osaka, Japan) and primers tetR-F (5′-ATATATCTCGAGGTGAGGCTTGGACGCTAGG-3′) and tetR-R (5′-ATATTTCTCGAGCTTGGATCAGACGCTGAGTG-3′), which contains an XhoI recognition site (underlined), and was phosphorylated at the 5′ hydroxyl termini with T4 polynucleotide kinase (NEB, Ipswich, MA, USA). The quadripartite ligation mixture, which was designed to generate a pUC19 construct containing relA_fragment 1 and 2 with an intervening tetr cassette, was used to transform E. coli DH5α and selected for the construct on LB agar plates containing 10 mg/L tetracycline and 100 mg/L ampicillin. The resultant pUC19 construct (1–2 μg) was used to transform B. thailandensis strains using a modified method of natural transformation described previously3 to obtain relA null mutants. The relA null mutants of B. thailandensis were verified by PCR using a primer pair relA_LF (5′-TCGATTACCTGACGTCGTTG-3′) and relA_LR (5′-CCTTGTATTTCTCGCCGATG-3′) that bind to genomic regions outside relA. 3D modelling of B. thailandensis MetG The structure of the B. thailandensis MetG was predicted using the solved X-ray structure of the MetG homologue from E. coli (PDBID: 1QQT)17 as a template (sequence identity, 54%) using Modeller.18 After generating the WT structure of B. thailandensis MetG, structures for five different mutants were generated using Chimera.19 Molecular dynamics simulations with explicit water molecules were performed on WT and the mutant MetGs using NAMD20 to remove the structural distortions caused by manual mutation with Chimera. Changes in the methionine binding pocket volume in the MetG mutants (Figure 1c) were measured and averaged for a 1 ns simulation after the simulations reached equilibrium. Figure 1. View largeDownload slide Mutations spontaneously occurred in B. thailandensis against meropenem. (a) Survivors of meropenem and their mutations. Point mutations in metG and a frameshift mutation in trmD found in survivors are shown along with their associated MICs (mg/L). (b) Structural model of B. thailandensis MetG with mutation sites. Methionine-binding cavity (in pink), ATP-binding site (in light blue) and tRNAMet-binding sites in two separate places (in yellow) are denoted. (c) Volume change in the methionine-binding cavity during molecular dynamics simulation; the WT MetG and five mutants are compared. The bars indicate range. Figure 1. View largeDownload slide Mutations spontaneously occurred in B. thailandensis against meropenem. (a) Survivors of meropenem and their mutations. Point mutations in metG and a frameshift mutation in trmD found in survivors are shown along with their associated MICs (mg/L). (b) Structural model of B. thailandensis MetG with mutation sites. Methionine-binding cavity (in pink), ATP-binding site (in light blue) and tRNAMet-binding sites in two separate places (in yellow) are denoted. (c) Volume change in the methionine-binding cavity during molecular dynamics simulation; the WT MetG and five mutants are compared. The bars indicate range. Growth analysis Overnight cultures were used to inoculate 100 mL of fresh LB broth at a ratio of 1:100 and new cultures were incubated at 37 °C with shaking at 250 rpm. OD600 was measured using a SpectraMax M2e microplate reader (Molecular Devices, CA, USA). The specific growth rate of each strain was calculated by obtaining the slope values from the linear region of the plots of the natural log of optical density (y-axis) versus time (x-axis). The Mann–Whitney test in SPSS was used to identify significant differences between the growth rates of the WT and the mutants. The growth curves were generated from triplicate experiments. Antibiotic tolerance assays Killing curves were generated in the presence of a lethal dose (512 mg/L) of ceftazidime and the minimal duration for killing 99% (MDK99) values for each strain (a measure of antibiotic tolerance21) was determined as described by Friedman et al.22 Briefly, single WT or mutant colonies were inoculated and grown overnight in 2 mL Mueller–Hinton broth at 37 °C with shaking at 250 rpm. The overnight culture was diluted 1:100 with fresh Mueller–Hinton broth and ceftazidime was added to the culture to the final concentration of 512 mg/L. The diluted culture was incubated at 37 °C with shaking at 250 rpm and 100 μL of the culture was removed at the indicated timepoints and serially diluted and plated on Mueller–Hinton agar plates. cfu were counted after 1–2 days of incubation at 37 °C. The timepoints corresponding to the intersections between the killing curves and the point of 99% killing were determined to be the MDK99 values for bacterial populations. Killing curves were generated from triplicate experiments. Phylogenetic analysis of MetG To obtain the phylogenetic relationship of Burkholderia MetGs relative to homologues from other bacteria, 499 reviewed MetG sequences were retrieved from the NCBI protein database (UniprotKB/Swiss-Prot) and the sequences were aligned with CLUSTALX.23 The phylogenetic tree was drawn based on the alignment information using iTOL software.24 Results and discussion B. thailandensis mutants that survived a lethal dose of meropenem To identify the genes associated with survival against meropenem, B. thailandensis was challenged with 4–6 mg/L meropenem (4–6 × MIC). The frequency of survivors was estimated to be 10−8–10−7. Genome sequencing analysis of two randomly selected isolates identified mutations in the metG and trmD genes, coding for methionyl-tRNA synthetase (BTH_I0856) and tRNA (guanine-N1)-methyltransferase (BTH_I1663), respectively, as the only mutations. MetG mediates the aminoacylation of tRNAMet, whereas TrmD is responsible for post-transcriptional modification of tRNAs.25 It is intriguing that both gene products are associated with tRNA metabolism and this suggests that an alteration in tRNA metabolism underlies the decreased susceptibility of B. thailandensis to meropenem. We selected more meropenem survivors and searched for more metG and trmD mutations. From the 29 isolates we obtained, we found 11 additional metG mutations, whereas no additional mutations were identified in trmD. This frequency of 12/29 indicates that metG was heavily over-selected for mutation from the 5712 genes in the B. thailandensis genome.26metG was also over-selected relative to the other 21 aminoacyl-tRNA synthetase (aaRS)-coding genes, where mutations could also have potential tRNA metabolism effects. All mutations in metG were single-nucleotide substitution mutations leading to five different amino acid substitutions (Pro27Ser, Leu216Pro, Phe316Ser, Arg424Pro and Phe501Leu) rather than disrupting the whole enzyme (Figure 1a). In contrast, the mutation in trmD was insertion of a nucleotide (G), causing a frameshift that disrupted the enzyme of 264 amino acids from position 178 (Figure 1a). These metG and trmD mutations were stable in the absence of antibiotic pressure, similar to other point mutations that conferred ceftazidime resistance.3 The mutants exhibited 5- to 10-fold increases in MICs of meropenem (Figure 1a). Amino acid substitutions in MetG are located at the binding sites for methionine or tRNAMet Unlike the frameshift mutation disrupting trmD, the position of which may not be particularly important as long as the enzyme is disrupted, the locations and the replacement amino acids play an important role in the substitution mutations in MetG because they retain the integrity of the enzyme while mainly affecting a specific function. To understand the affected function in B. thailandensis MetG, the structure of which has not been solved, we computationally predicted the structure using the E. coli MetG (PDB IDs: 1QQT, 1PG2),17,27 which has a high homology (54.7%) with the B. thailandensis MetG (Figure 1b). All five mutations were located at either the predicted methionine- or tRNAMet-binding sites (Figure 1b). Pro27Ser was mapped to the methionine-binding cavity, while four others were mapped to the tRNA-binding sites separated into two regions (Figure 1b). Specifically, two amino acid substitutions, Leu216Pro and Phe316Ser, were mapped to the tRNA-binding site in the catalytic pocket, which also includes the methionine- and ATP-binding sites (Figure 1b). The other two amino acid substitutions, Arg424Pro and Phe501Leu, were mapped to the anticodon-binding site separated from the catalytic pocket. This specific localization of the five amino acid changes might affect the binding of methionine (Pro27Ser) or tRNAMet (all others), increasing the uncharged tRNAMet pool in the cell. Intriguingly, all mutations at the tRNA-binding sites, particularly the two mutations in the anticodon-binding domain, Arg424Pro and Phe501Leu, increased the volume of the methionine-binding cavity during molecular dynamics simulation (Figure 1c). This finding suggests that Arg424Pro and Phe501Leu, which affect tRNAMet binding, may also affect the binding of methionine from separated positions. MetG mutants induce a stringent response, which confers antibiotic tolerance MetG mutants exhibited significantly reduced growth rates compared with the WT (P = 0.004; Figure 2a). The specific growth rate of the WT strain was 0.88 ± 0.04/h, whereas growth rates of the MetG mutants were 48%–60% of this value (P27S, 0.43 ± 0.05/h; F316S, 0.46 ± 0.01/h; R424P, 0.35 ± 0.03/h; F501L, 0.40 ± 0.07/h). Growth retardation is a main symptom of stringent response leading to antibiotic tolerance in bacteria.21 As predicted, in addition to meropenem, increased MICs were observed for various antibiotics with different modes of action, including ampicillin (a penicillin), ceftazidime (a third-generation cephalosporin), ciprofloxacin (a quinolone) and kanamycin (an aminoglycoside) with MetG mutants as well as the TrmD mutant (Figure 2b). This result strongly indicates that MetG and TrmD mutants confer antibiotic tolerance rather than resistance, which is generally specific to one class of antibiotics.3 Based on the clinically defined CLSI MIC breakpoints, MetG and TrmD mutants were classified as ‘intermediate’ for meropenem, which is an upgrade from ‘susceptible’, the classification of the WT strain. Among the antibiotics for which MICs were increased in strains with mutations (Figure 2b), the increase in ciprofloxacin was sufficient to necessitate an upgrade from ‘intermediate’ to ‘resistant’. Figure 2. View largeDownload slide Stringent response phenotypes. (a) Growth curves of four metG mutants compared with the WT. The OD600 and the log of OD600 (inset) values are plotted against time. (b) An MIC table of metG and trmD mutants for various antibiotics. Each cell of the table comprises the heat map reflecting the fold change in MIC values relative to those of the WT. Actual values of the MICs (mg/L) are also shown in each cell. MEM, meropenem; AMP, ampicillin; CAZ, ceftazidime; CTX, cefotaxime; KAN, kanamycin; TET, tetracycline; CIP, ciprofloxacin; ND, not determined. (c) Killing curves of the metG and penL mutants in the presence of ceftazidime. The green horizontal line indicates the point of 99% killing in each mutant population. Vertical arrows originating from the intersections between curves and the horizontal line designate the x-axis values, which correspond to the minimal duration for killing 99% (MDK99 in h) for each mutant population. Figure 2. View largeDownload slide Stringent response phenotypes. (a) Growth curves of four metG mutants compared with the WT. The OD600 and the log of OD600 (inset) values are plotted against time. (b) An MIC table of metG and trmD mutants for various antibiotics. Each cell of the table comprises the heat map reflecting the fold change in MIC values relative to those of the WT. Actual values of the MICs (mg/L) are also shown in each cell. MEM, meropenem; AMP, ampicillin; CAZ, ceftazidime; CTX, cefotaxime; KAN, kanamycin; TET, tetracycline; CIP, ciprofloxacin; ND, not determined. (c) Killing curves of the metG and penL mutants in the presence of ceftazidime. The green horizontal line indicates the point of 99% killing in each mutant population. Vertical arrows originating from the intersections between curves and the horizontal line designate the x-axis values, which correspond to the minimal duration for killing 99% (MDK99 in h) for each mutant population. Some mutations in aaRSs have been shown to trigger a stringent response when aminoacylation of tRNAs is severely disrupted, resulting in an increase in the uncharged tRNA pool in E. coli.28 The free tRNA occupying the A site of ribosomes can activate RelA, the synthetase of (p)ppGpp, which is the main mediator of the bacterial stringent response.29,Escherichia coli isolates with mutations in genes encoding aaRSs, including those encoding ArgS, AlaS, LeuS and IleS, exhibited decreased susceptibility to novobiocin.30 In another study, mutations in genes encoding aaRSs, including ArgS, AlaS, AspS, ThrS and GltX, showed decreased susceptibility to the β-lactam mecillinam.31 Mutations in metG also have been associated with activation of a stringent response, leading to increased tolerance to β-lactams and quinolones by increasing lag time in E. coli.21,22 Therefore, it is likely that a similar mechanism underlies antibiotic tolerance in the MetG mutants of B. thailandensis, although they exhibited an increased MIC of meropenem, which is typically suggestive of resistance rather than tolerance.21 The genome of B. thailandensis E264 contains a relA gene (BTH_I2597), a key stringent response component, which shares high homology (96% at the protein level) with relA of B. pseudomallei.32 Inactivation of relA in the metG mutants significantly lowered the MICs of various antibiotics (Figure 2b), supporting the supposition that stringent response is responsible for mutant phenotypes. In addition, the killing curves of metG mutants in the presence of ceftazidime compared with those of ceftazidime-resistant penL mutants clearly demonstrated that it is indeed antibiotic tolerance that is conferred by the metG mutants (Figure 2c). Two penL mutants (N136D, P174S) included in the comparison were previously obtained by selection in the presence of ceftazidime.3 Killing curves were generated in the presence of a lethal dose (512 mg/L) of ceftazidime and the MDK99 values of each strain, a measure used for antibiotic tolerance,21 were determined (Figure 2c). The MDK99 values for penL mutants (3.4 and 4.4 h for N136D and P174S penL mutants, respectively) were markedly shorter than those of metG mutants (P27S and F316S mutants with 6.2 and >8 h, respectively), although penL mutants had higher MIC values (Figure 2c). These results suggest that the duration of antibiotic treatment should be adjusted according to the underlying mechanism protecting the pathogens. MetGs in Proteobacteria are closely related To profile the diversity of MetGs, we downloaded 499 verified MetG sequences from the NCBI database and constructed a phylogenetic tree (Figure 3). These MetG sequences were largely grouped into three clusters, one of which was a distinct cluster with MetGs from Proteobacteria, including Burkholderia species and E. coli (Figure 3). The B. thailandensis MetG is nearly identical to those from highly pathogenic B. mallei and B. pseudomallei (92.84% identity). Because bacteria belonging to Proteobacteria have key stringent response components RelA and SpoT,33 and E. coli and B. thailandensis MetGs have a similar antibiotic tolerance mechanism, but share a lower level of protein identity than others in the Proteobacteria cluster (Figure 3), it seems reasonable that other MetGs in this cluster also act as a pathway to the stringent response, leading to antibiotic tolerance. Figure 3. View largeDownload slide Phylogenetic tree of MetGs. The phylogenetic relationship of 499 MetG orthologues organized in three clusters is shown. Each clade of the tree is colour-coded by phylum. The heat map in the outer circle shows the amino acid percentage identity of the enzymes corresponding to those of E. coli strains as the standard. A cluster composed of Proteobacteria, including Burkholderia spp. and E. coli, which have similar metG-mediated stringent responses that lead to tolerance to various antibiotics, is shown. Bt, B. thailandensis; Bp, B. pseudomallei; Bm, B. mallei; Bcc, Burkholderia cepacia complex. Figure 3. View largeDownload slide Phylogenetic tree of MetGs. The phylogenetic relationship of 499 MetG orthologues organized in three clusters is shown. Each clade of the tree is colour-coded by phylum. The heat map in the outer circle shows the amino acid percentage identity of the enzymes corresponding to those of E. coli strains as the standard. A cluster composed of Proteobacteria, including Burkholderia spp. and E. coli, which have similar metG-mediated stringent responses that lead to tolerance to various antibiotics, is shown. Bt, B. thailandensis; Bp, B. pseudomallei; Bm, B. mallei; Bcc, Burkholderia cepacia complex. Perspectives Resistance to carbapenems has primarily been attributed to carbapenemase, but also to overexpression of efflux pumps or porins, or alterations or down-regulation of targeted PBPs.13 The increased membrane permeability associated with the expression of a B. pseudomallei porin in E. coli correlated with antimicrobial susceptibility to carbapenems,34 implying that mutations in this porin increasing permeability may lead to meropenem resistance in Burkholderia pathogens. As meropenem resistance is a problem in chronic Burkholderia infections in patients with cystic fibrosis,35 and clinical isolates of B. pseudomallei with reduced meropenem susceptibility have been reported recently,11 it is significant that this study revealed a key defence mechanism against meropenem in Burkholderia spp., which is through stringent-response-mediated tolerance triggered by mutations in genes encoding MetG and TrmD that affect tRNA metabolism, particularly MetG as the major route. All metG mutations conferred a single amino acid substitution, which contrasts with the trmD mutation, which caused a frameshift disrupting the whole enzyme (Figure 1a). This suggests that unlike trmD, metG is indispensable. Consistent with this notion, inhibitors of MetGs are considered novel candidates for antibiotics or anti-parasitic drugs in various bacteria and protozoa, including E. coli,36,37 Gram-positive bacteria, Staphylococcus aureus38 and Streptococcus pneumoniae,39 and a parasitic protozoan, Trypanosoma brucei.40 These inhibitors block MetGs via competition with methionine41 or by interacting with bound ATP,40 while not significantly affecting human MetGs. However, mutations in genes encoding MetG conferring evasion by altering antibiotic targets on the enzymes have been found in several bacteria.42–45 Furthermore, as shown in this study, partial inhibition of MetGs may trigger a stringent response leading to antibiotic tolerance. The five specific amino acid substitution mutations identified in MetG that lead to a stringent response will be useful in efforts to develop new drugs that inhibit this essential enzyme without causing stringent-response-mediated antibiotic tolerance in pathogens. Funding This work was supported by grants NRF-2015R1A2A2A01004007 and 2015M3C9A4053393 from the National Research Foundation (NRF) of the Republic of Korea and grant K1620031 from Korea University Medical Center and Anam Hospital, Seoul, Republic of Korea. Additional support was provided by grant 2016R1A6A3A11935950 for research fellows from the NRF of the Republic of Korea to H. Y. Transparency declarations None to declare. References 1 Cheng AC, Currie BJ. Melioidosis: epidemiology, pathophysiology, and management. Clin Microbiol Rev 2005; 18: 383– 416. Google Scholar CrossRef Search ADS PubMed 2 Song H, Hwang J, Yi H et al. The early stage of bacterial genome-reductive evolution in the host. PLoS Pathog 2010; 6: e1000922. Google Scholar CrossRef Search ADS PubMed 3 Yi H, Cho K-H, Cho YS et al. Twelve positions in a β-lactamase that can expand its substrate spectrum with a single amino acid substitution. PLoS One 2012; 7: e37585. Google Scholar CrossRef Search ADS PubMed 4 Yi H, Kim K, Cho K-H et al. Substrate spectrum extension of PenA in Burkholderia thailandensis with a single amino acid deletion, Glu168del. Antimicrob Agents Chemother 2012; 56: 4005– 8. Google Scholar CrossRef Search ADS PubMed 5 Yi H, Song H, Hwang J et al. The tandem repeats enabling reversible switching between the two phases of β-lactamase substrate spectrum. PLoS Genet 2014; 10: e1004640. Google Scholar CrossRef Search ADS PubMed 6 Hwang J, Cho K-H, Song H et al. Deletion mutations conferring substrate spectrum extension in the class A β-lactamase. Antimicrob Agents Chemother 2014; 58: 6265– 9. Google Scholar CrossRef Search ADS PubMed 7 Tribuddharat C, Moore RA, Baker P et al. Burkholderia pseudomallei class a β-lactamase mutations that confer selective resistance against ceftazidime or clavulanic acid inhibition. Antimicrob Agents Chemother 2003; 47: 2082. Google Scholar CrossRef Search ADS PubMed 8 Poirel L, Rodriguez-Martinez J-M, Plésiat P et al. Naturally occurring class A β-lactamases from the Burkholderia cepacia complex. Antimicrob Agents Chemother 2009; 53: 876– 82. Google Scholar CrossRef Search ADS PubMed 9 Leitão JH, Sousa SA, Ferreira AS et al. Pathogenicity, virulence factors, and strategies to fight against Burkholderia cepacia complex pathogens and related species. Appl Microbiol Biotechnol 2010; 87: 31– 40. Google Scholar CrossRef Search ADS PubMed 10 Wuthiekanun V, Peacock SJ. Management of melioidosis. Expert Rev Anti Infect Ther 2006; 4: 445– 55. Google Scholar CrossRef Search ADS PubMed 11 Price EP, Smith ML, Paxinos EE et al. Whole-genome sequences of Burkholderia pseudomallei isolates exhibiting decreased meropenem susceptibility. Genome Announc 2017; 5: e00053-17. Google Scholar CrossRef Search ADS PubMed 12 Sass A, Marchbank A, Tullis E et al. Spontaneous and evolutionary changes in the antibiotic resistance of Burkholderia cenocepacia observed by global gene expression analysis. BMC Genomics 2011; 12: 373. Google Scholar CrossRef Search ADS PubMed 13 Meletis G. Carbapenem resistance: overview of the problem and future perspectives. Ther Adv Infect Dis 2015; 3: 15– 21. Google Scholar CrossRef Search ADS 14 Kim HS, Yi H, Myung J et al. Opine-based Agrobacterium competitiveness: dual expression control of the agrocinopine catabolism (acc) operon by agrocinopines and phosphate levels. J Bacteriol 2008; 190: 3700– 11. Google Scholar CrossRef Search ADS PubMed 15 Wiegand I, Hilpert K, Hancock REW. Agar and broth dilution methods to determine the minimal inhibitory concentration (MIC) of antimicrobial substances. Nat Protoc 2008; 3: 163– 75. Google Scholar CrossRef Search ADS PubMed 16 Keen NT, Tamaki S, Kobayashi D et al. Improved broad-host-range plasmids for DNA cloning in Gram-negative bacteria. Gene 1988; 70: 191– 7. Google Scholar CrossRef Search ADS PubMed 17 Mechulam Y, Schmitt E, Maveyraud L et al. Crystal structure of Escherichia coli methionyl-tRNA synthetase highlights species-specific features. J Mol Biol 1999; 294: 1287– 97. Google Scholar CrossRef Search ADS PubMed 18 Fiser A, Šali A. Modeller: generation and refinement of homology-based protein structure models. Methods Enzymol 2003; 374: 461– 91. Google Scholar CrossRef Search ADS PubMed 19 Pettersen EF, Goddard TD, Huang CC et al. UCSF Chimera—a visualization system for exploratory research and analysis. J Comput Chem 2004; 25: 1605– 12. Google Scholar CrossRef Search ADS PubMed 20 Phillips JC, Braun R, Wang W et al. Scalable molecular dynamics with NAMD. J Comput Chem 2005; 26: 1781– 802. Google Scholar CrossRef Search ADS PubMed 21 Brauner A, Fridman O, Gefen O et al. Distinguishing between resistance, tolerance and persistence to antibiotic treatment. Nat Rev Microbiol 2016; 14: 320– 30. Google Scholar CrossRef Search ADS PubMed 22 Fridman O, Goldberg A, Ronin I et al. Optimization of lag time underlies antibiotic tolerance in evolved bacterial populations. Nature 2014; 513: 418– 21. Google Scholar CrossRef Search ADS PubMed 23 Larkin MA, Blackshields G, Brown NP et al. Clustal W and Clustal X version 2.0. Bioinformatics 2007; 23: 2947– 8. Google Scholar CrossRef Search ADS PubMed 24 Letunic I, Bork P. Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res 2016; 44: W242– 5. Google Scholar CrossRef Search ADS PubMed 25 Byström AS, Björk GR. Chromosomal location and cloning of the gene (trmD) responsible for the synthesis of tRNA (m1G) methyltransferase in Escherichia coli K-12. Mol Gen Genet 1982; 188: 440– 6. Google Scholar CrossRef Search ADS PubMed 26 Kim HS, Schell MA, Yu Y et al. Bacterial genome adaptation to niches: divergence of the potential virulence genes in three Burkholderia species of different survival strategies. BMC Genomics 2005; 6: 174. Google Scholar CrossRef Search ADS PubMed 27 Crepin T, Schmitt E, Mechulam Y et al. Use of analogues of methionine and methionyl adenylate to sample conformational changes during catalysis in Escherichia coli methionyl-tRNA synthetase. J Mol Biol 2003; 332: 59– 72. Google Scholar CrossRef Search ADS PubMed 28 Vinella D, D’Ari R, Jaffe A et al. Penicillin binding protein 2 is dispensable in Escherichia coli when ppGpp synthesis is induced. EMBO J 1992; 11: 1493. Google Scholar PubMed 29 Potrykus K, Cashel M. (p)ppGpp: still magical? Annu Rev Microbiol 2008; 62: 35– 51. Google Scholar CrossRef Search ADS PubMed 30 Milija J, Lilic M, Janjusevic R et al. tRNA synthetase mutants of Escherichia coli K-12 are resistant to the gyrase inhibitor novobiocin. J Bacteriol 1999; 181: 2979– 83. Google Scholar PubMed 31 Thulin E, Sundqvist M, Andersson DI. Amdinocillin (mecillinam) resistance mutations in clinical isolates and laboratory-selected mutants of Escherichia coli. Antimicrob Agents Chemother 2015; 59: 1718– 27. Google Scholar CrossRef Search ADS PubMed 32 Müller CM, Conejero L, Spink N et al. Role of RelA and SpoT in Burkholderia pseudomallei virulence and immunity. Infect Immun 2012; 80: 3247– 55. Google Scholar CrossRef Search ADS PubMed 33 Atkinson GC, Tenson T, Hauryliuk V. The RelA/SpoT homolog (RSH) superfamily: distribution and functional evolution of ppGpp synthetases and hydrolases across the tree of life. PLoS One 2011; 6: e23479. Google Scholar CrossRef Search ADS PubMed 34 Aunkham A, Schulte A, Winterhalter M et al. Porin involvement in cephalosporin and carbapenem resistance of Burkholderia pseudomallei. PLoS One 2014; 9: e95918. Google Scholar CrossRef Search ADS PubMed 35 Dales L, Ferris W, Vandemheen K et al. Combination antibiotic susceptibility of biofilm-grown Burkholderia cepacia and Pseudomonas aeruginosa isolated from patients with pulmonary exacerbations of cystic fibrosis. Eur J Clin Microbiol Infect Dis 2009; 28: 1275– 9. Google Scholar CrossRef Search ADS PubMed 36 Lee J, Kang SU, Kim SY et al. Vanilloid and isovanilloid analogues as inhibitors of methionyl-tRNA and isoleucyl-tRNA synthetases. Bioorg Med Chem Lett 2001; 11: 965. Google Scholar CrossRef Search ADS PubMed 37 Lee J, Kang SU, Kang MK et al. Methionyl adenylate analogues as inhibitors of methionyl-tRNA synthetase. Bioorg Med Chem Lett 1999; 9: 1365– 70. Google Scholar CrossRef Search ADS PubMed 38 Green LS, Bullard JM, Ribble W et al. Inhibition of methionyl-tRNA synthetase by REP8839 and effects of resistance mutations on enzyme activity. Antimicrob Agents Chemother 2009; 53: 86– 94. Google Scholar CrossRef Search ADS PubMed 39 Gentry DR, Ingraham KA, Stanhope MJ et al. Variable sensitivity to bacterial methionyl-tRNA synthetase inhibitors reveals subpopulations of Streptococcus pneumoniae with two distinct methionyl-tRNA synthetase genes. Antimicrob Agents Chemother 2003; 47: 1784– 9. Google Scholar CrossRef Search ADS PubMed 40 Koh CY, Kim JE, Wetzel AB et al. Structures of Trypanosoma brucei methionyl-tRNA synthetase with urea-based inhibitors provide guidance for drug design against sleeping sickness. PLoS Negl Trop Dis 2014; 8: e2775. Google Scholar CrossRef Search ADS PubMed 41 Hurdle JG, O'Neill AJ, Chopra I. Prospects for aminoacyl-tRNA synthetase inhibitors as new antimicrobial agents. Antimicrob Agents Chemother 2005; 49: 4821– 33. Google Scholar CrossRef Search ADS PubMed 42 Hughes J, Mellows G. Interaction of pseudomonic acid A with Escherichia coli B isoleucyl-tRNA synthetase. Biochem J 1980; 191: 209– 19. Google Scholar CrossRef Search ADS PubMed 43 Kim S, Lee SW, Choi E-C et al. Aminoacyl-tRNA synthetases and their inhibitors as a novel family of antibiotics. Appl Microbiol Biotechnol 2003; 61: 278– 88. Google Scholar CrossRef Search ADS PubMed 44 Fang P, Guo M. Evolutionary limitation and opportunities for developing tRNA synthetase inhibitors with 5-binding-mode classification. Life 2015; 5: 1703– 25. Google Scholar CrossRef Search ADS PubMed 45 Ochsner UA, Young CL, Stone KC et al. Mode of action and biochemical characterization of REP8839, a novel inhibitor of methionyl-tRNA synthetase. Antimicrob Agents Chemother 2005; 49: 4253– 62. Google Scholar CrossRef Search ADS PubMed © The Author 2017. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please email: firstname.lastname@example.org.
Journal of Antimicrobial Chemotherapy – Oxford University Press
Published: Feb 1, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.
All for just $49/month
Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.
Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.
It’s easy to organize your research with our built-in tools.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera