Center for Genomics and Bioinformatics, Karolinska Institutet, Berzelius väg 35, 171 77, Stockholm, Sweden
Received 9 March 2005; returned 12 April 2005; revised 13 April 2005; accepted 19 April 2005
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Abstract |
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Objective: To evaluate antimicrobial effectiveness from combinations of protein-specific drugs and mRNA-specific antisense inhibitors.
Methods: Interactions between conventional antimicrobial drugs and mRNA-specific translation inhibiting antisense peptide nucleic acids were assessed in Escherichia coli and Staphylococcus aureus cultures using pairwise combinations in a chequerboard arrangement. Fractional inhibitory concentration indices (FICIs) were calculated and grouped according to the functional relationship between the inhibitor targets. Antisense specificity controls included different antisense sequences targeting the same mRNA, as well as biochemical quantification of active protein expressed from the essential fabI gene and from the lacZ reporter gene after single and combined inhibitor treatment.
Results: FICIs were higher for inhibitor combinations with unrelated targets than for combinations with functionally related targets. Inhibitor combinations with shared genetic targets displayed the lowest FICIs, with several qualifying for the conservative definition of antimicrobial synergy (FICI 0.5). Furthermore, low FICIs arise as the hyperbolic doseresponse curves for each separate inhibitor are maintained in combination.
Conclusion: Interactions between mRNA- and protein-level inhibitors with the same genetic target can be synergistic and may provide a strategy to improve antimicrobial efficacy, facilitate drug mechanism of action studies and aid the search for new antimicrobials.
Keywords: antimicrobial treatment , antisense , chequerboard , inhibitor combinations , PNA
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Introduction |
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A strategy to improve therapy is to use drug combinations. By this means the likelihood that microbes would simultaneously develop resistance against more than one drug is reduced. Also, combined drug treatment can lead to positive combinatorial effects or even antimicrobial synergy.3 The combination of trimethoprim and sulphonamides (co-trimoxazole) is a well known example, involving mutual interference of two sequential steps in folate biosynthesis.4 Unfortunately, there are few examples of successful antimicrobial combinations, reflecting the limited profile of distinct drug classes and mechanisms.
Antimicrobial combination studies frequently involve pairwise titration of two conventional antimicrobials in chequerboard assays.3 Although typically applied to conventional drugs, the experimental design can be extended to assess pairs of protein and mRNA inhibitors. We have developed modified antisense peptide nucleic acids (PNAs) for gene inhibition studies in bacteria, where an attached peptide aids cell uptake.5 Such PNAs are effective against growth-essential genes in Escherichia coli and Staphylococcus aureus,6,7 and have the potential to greatly expand the scope of inhibitor studies. Here we designed antisense PNAs against a panel of well known antimicrobial drug targets and combined these mRNA inhibitors with a corresponding panel of conventional small molecule antimicrobials in a systematic mRNA- and protein-level inhibitor study.
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Materials and methods |
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E. coli K12 was acquired from the E. coli Genetic Stock Center (Yale University, USA), E. coli AS19 from S. Pedersen (University of Copenhagen, Denmark) and S. aureus strain RN4220 from Prof. Staffan Arvidson (Karolinska Institutet, Sweden). PNAs were purchased from Oswel Research Products Ltd. (Southampton, UK). All antimicrobial drugs were purchased from Sigma-Aldrich (Stockholm, Sweden) except for triclosan, which was a generous gift from Barbro Guse at Ciba Specialty Chemicals (Västra Frölunda, Sweden). Other chemicals were from Sigma-Aldrich unless otherwise stated.
Selection of antimicrobial drugs and design of antisense PNAs
Antimicrobial drugs used in this study were originally selected because of their known specificity for single protein targets. Other drugs with a broader target spectrum were also included. PNA target genes were chosen based on the availability of target-specific drugs. A few additional target genes were selected as controls. PNA sequences were selected following the antisense PNA design rules described before8 with the cell penetrating peptide KFFKFFKFFK attached for improved uptake.6
Determination of MICs
E. coli K12 and AS19 were pre-grown overnight in 2 mL MullerHinton broth (MHB) at 37°C with constant shaking at 225 rpm. Optical density (OD) was measured at 550 nm the following day and the cultures were diluted to 1.25 x 105 bacteria per mL in MHB. Aliquots (80 µL) corresponding to 104 cells were added to the wells of an ultra low attachment 96-well plate with lid (COSTAR®, Corning Inc., NY, USA). Dilutions of PNAs and drugs were added to make a total culture volume of 100 µL. The 96-well plates were incubated for 24 h in a VERSAmax spectrophotometer (Molecular Devices Corporation, CA, USA) at 37°C with shaking and OD measurements every 5 min. Shaking time was set to 5 s and optical density was measured at 550 nm to monitor growth. MICs were determined as the lowest concentration of an antimicrobial drug or PNA needed for growth inhibition after 24 h. MICs for S. aureus were determined in the same way as for the E. coli strains except that OD measurements were performed every 3 min and shaking time was set to 15 s.
Chequerboard assay and calculation of fractional inhibitory concentration indices (FICIs)
PNAs and drugs were tested in pairs using the chequerboard method3 in 96-well format under the same growth conditions as used for the MIC determinations. Inhibitors were titrated in perpendicular dimensions and FICs were calculated:
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Assay for enoyl-ACP reductase (EACPR) activity
The general procedure described by Bergler and co-workers10 was modified as follows: E. coli K12 cells were grown in 2 mL MHB at 37°C with constant shaking at 225 rpm until an OD550 of 5.0. The culture was diluted in MHB and aliquots of 200 µL were added to the wells of a 96-well plate together with 50 µL of either water or sub-growth-inhibitory concentrations of Ec107fabI and Ec246folA PNA, giving a final cell concentration of 106 cells per mL. The plate was incubated in a spectrophotometer at 37°C with shaking, and OD measurements were taken every 5 min until an increase in OD550 of
0.4 was reached. The content of 32 wells were pooled (three different samples could be prepared in parallel in one plate) and centrifuged for 10 min at 5000g and 4°C. The cells were re-suspended in 1 mL cold 0.1 M phosphate buffer (pH 7.5) and centrifuged for 10 min at 5000g and 4°C. After re-suspension in 205 µL cold phosphate buffer, 10 µL samples were diluted 100 times in phosphate buffer and the OD550 was determined. Equal numbers of cells were transferred to 2 mL tubes in 200 µL samples with phosphate buffer added to adjust the volumes where needed. Silica beads (400 mg of 0.1 mm diameter, www.biospec.com) were added and the bacteria were lysed in a Mini-Beadbeater 3110BX (www.biospec.com) at 4800 rpm for 2 min, chilled on ice. Seven hundred microlitres of cold phosphate buffer was added and the tubes were centrifuged at 12 000g for 1 min to spin down beads, large cell debris and whole cells. Supernatants (650 µL) were transferred to 1.5 mL polypropylene centrifuge tubes (Beckman Coulter AB, Bromma, Sweden) and the samples centrifuged at 48 000g for 1 h at 4°C. Supernatants (500 µL) were transferred to clean Eppendorf tubes. For assay reactions, 100 µL supernatant was mixed with 20 µL NAD+ (2 mM), 30 µL phosphate buffer and 20 µL triclosan (100 µM dissolved in 10% DMSO) or 20 µL 10% DMSO in the wells of a 96-well plate. The plate was incubated in the dark during constant shaking for 30 min before the addition of 20 µL NADH (1 mM) and 10 µL Crotonoyl-CoA (5 mM). The plate was placed in a plate spectrophotometer programmed for room temperature measurements of optical density at 340 nm every 30 s with pre-shaking for 5 s. Slopes of the conversion curves were used to determine reaction rates for NADH consumption and the activity of the EACPR enzyme.
Inhibition and quantification of ß-galactosidase
ß-Galactosidase was measured as described.11 A culture of E. coli K12 was diluted in MHB and 200 µL samples were added to the wells of a 96-well plate prepared with 50 µL IPTG solution and varying concentrations of Ec274lacZ PNA, giving a final concentration of 106 cells/mL in 100 µM IPTG. The plate was incubated in a spectrophotometer at 37°C with shaking and absorbance measurements each 5 min until an increase in OD550 of 0.2 was reached. Cultures with equal PNA concentrations were pooled (eight wells/concentration), and the samples washed twice in PBS before being dissolved in 1 mL PBS. Cell concentrations were equalized with PBS and five 30 µL samples from each culture pool were mixed with 30 µL lysis buffer (piercenet.com prod. no. 78990). After 1 h incubation on a shaking table, 40 µL aliquots were transferred to a 96-well plate containing variable concentrations of the competitive ß-galactosidase inhibitor D-galactal (Sigma) dissolved in PBS. Finally, 160 µL Z-buffer (60 mM Na2HPO4, 40 mM NaH2PO4, 10 mM KCl, 1 mM MgSO4 and 50 mM ß-mercaptoethanol adjusted to pH 7.0) and 20 µL ONPG solution (ONPG 4 mg/mL in 100 mM HEPES, pH 7.2) were added and the ß-galactosidase-induced cleavage of ONPG was monitored spectrophotometrically at 420 nm with shaking and absorbance measurements every 30 s at 28°C. Slopes of colour conversion curves were used to determine the relative activities of ß-galactosidase in each sample.
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Results and discussion |
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To establish a set of antisense inhibitors, we designed PNAs complementary to unique sequences within the start codon region of mRNAs encoded by essential genes including drug targets in E. coli and S. aureus.12 The carrier peptide KFFKFFKFFK was attached to each PNA to improve cell uptake.6,13 Inhibitory drug and PNA concentrations were determined in E. coli wild type (K12) and permeable (AS19) strains and S. aureus (RN4220) (Table 1). As expected, the permeable strain was most susceptible to both drugs and PNAs and the thick-walled S. aureus was generally less susceptible.5 Inhibitory concentrations also varied between target genes, possibly due to differences in uptake, binding kinetics and gene product requirement. As a control, the cell penetrating peptide KFFKFFKFFK was tested at a 20 µM concentration in S. aureus without showing any effect upon bacterial growth. The set of antisense PNAs and drugs provide titratable inhibitors of growth-essential genes.
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To analyse the level of interaction between mRNA and protein level inhibitors, PNAs and drugs were used in pairwise combinations in E. coli and S. aureus cultures. Interactions were assessed using the chequerboard assay, and FICIs were calculated (see Materials and methods). For comparison, drug/drug combinations with functionally related and unrelated targets were included. As expected, co-trimoxazole displayed synergy in both K12 (Figure 1a, c8) and AS19 (c20) whereas drug/drug combinations with unrelated targets showed no interaction (c9c12). A total of 14 PNA/drug combinations were tested in E. coli; six with unrelated targets, four with targets in the same biosynthetic pathway and four sharing genetic targets. A pattern was observed where inhibitor combinations with unrelated targets resulted in the highest FICIs (Figure 1a, c3, c4, c6, c13, c16 and c19), and combinations with targets in the same pathway generally showed a lower FICI (c5, c7, c15 and c17). The four combinations with shared genetic targets gave the lowest FICIs (c1, c2, c14 and c18), and three of these could be defined as synergistic. In S. aureus, 19 antisense PNA/drug combinations were tested; 15 with unrelated targets, one with functionally related targets and three sharing genetic targets. Again, combinations with unrelated targets displayed no interaction with relatively high FICIs (Figure 1b, cII-cIV, cVI-cX, cXII, cXIII and cXV-cXIX), whereas combinations with shared genetic targets gave much lower values (cV, cXI), and in one case displayed antimicrobial synergy (cXIV). Therefore, the synergistic or more than additive interactions for antisense/drug combinations sharing genetic targets suggest a new strategy to improve antimicrobial efficiency in practice. Moreover, as protein- and mRNA-level inhibitors are chemically distinct and inhibit sequential steps in gene expression, combined treatment could help limit drug resistance. Although gene-selective mRNA inhibitors for antimicrobial applications are still far from the clinic, there are possibilities to develop mRNA sequence6,7,13 and structure14 targeting antimicrobials, which could follow the progress of antisense agents in viral and cancer treatment.15
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Antisense PNA inhibition is mRNA specific
When assessing antisense inhibition, sequence specificity of the PNA is an important issue. In bacteria, sequence alterations in both the PNA and the target sequence lower PNA efficiency.6,7 Here, target specificity is indicated by the low FICI observed for each PNA/drug combination with a shared genetic target relative to other combinations. Moreover, antisense/drug combinations maintain similar FICIs when the antisense target is shifted within the translation start region of the mRNA (Figure 1, cf. c1 with c2 and cXI with cXIV; see also Table 1 for PNA target sites). Although the data probably reflect mRNA-specific effects, we aimed to evaluate specificity more thoroughly.
To test whether the positive inhibitor interactions hold true at the biochemical level, the activity of the essential EACPR enzyme (fabI gene product) was determined in E. coli K12 cultures pre-treated with Ec107fabI PNA and a control PNA (Ec246folA) in the presence or absence of the EACPR-specific inhibitor triclosan. The results demonstrate a dose-dependent inhibition of EACPR with Ec107fabI, whereas high doses of the unrelated Ec246folA did not affect the level of enzyme activity (Figure 2, cf. bar 24 with bar 12 and 13). Moreover, combined Ec107fabI and triclosan treatment showed more potent inhibition than either inhibitor used alone (cf. bar 79 with bar 24). Also, enzyme activity in samples treated with both Ec246folA and triclosan did not differ from samples treated with triclosan alone (cf. bar 16 and 17 with bar 18). Therefore, the result demonstrates Ec107fabI inhibition of EACPR production and mutual PNA/drug inhibitory effects on FabI activity.
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Antimicrobial synergy has been attributed to the hyperbolic or logarithmic nature of dose-responses.3,18 In a similar way, doseresponse effects could explain positive interactions between mRNA- and protein-level inhibitors. To test this, we examined pairwise inhibition of the non-essential ß-galactosidase gene, a reporter system that enables inhibition over a large range without altering growth. As expected, inhibition kinetics for treatment with Ec274lacZ PNA, or the competitive ß-galactosidase inhibitor D-galactal, displayed hyperbolic doseresponse curves (Figure 3a and b, respectively). When cultures were pre-treated with low doses of Ec274lacZ, the response curve for D-galactal shifted towards more complete inhibition at every dose tested (Figure 3b). By setting arbitrary threshold inhibition levels it is possible to calculate FICIs for combinations of the inhibitors. For example, a threshold at 80% protein activity reduction gives:
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Knowledge of proteinsmall molecule interactions is based on genetic and in vitro studies that often lack physiological relevance or fail to uncover significant interactions.20 For example, sulfa antimicrobials are the oldest synthetic anti-infectives used in the clinic, yet their mechanism(s) of action and the mechanism(s) underlying their synergy with trimethoprim remain controversial.3 The main target of sulfa drugs is dihydropteroate synthase (FolP), which provides an early step in folate biosynthesis. A later step in the same pathway is provided by dihydrofolate reductase (FolA), the target of trimethoprim. Synergy between sulfa and trimethoprim is typically explained as a case of sequential inhibition.4,21 However, several studies suggest that sulphonamides target both dihydropteroate synthase (FolP) and dihydrofolate reductase (FolA) and, therefore, mutual inhibition of FolA could explain the observed synergy.2224 Interestingly, our results for combinations of PNAs and drugs against folate biosynthesis targets show more than additive effects when anti-folA PNA was combined with sulfamethoxazole, but not when anti-folP PNA was used in combination with trimethoprim (Figure 4). Poor specificity for the anti-folP PNA cannot explain the result as this PNA gives more than additive effects with sulfamethoxazole (Figure 4). Therefore, our results are consistent with sulfa inhibition of FolA.22 This suggestion requires further investigation, but the analysis shows how combinations of mRNA and protein level inhibitors can be applied to help decipher drugs mechanism of action.
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Acknowledgements |
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