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Journal of Bacteriology, September 2008, p. 5981-5988, Vol. 190, No. 17
0021-9193/08/$08.00+0     doi:10.1128/JB.01982-07
Copyright © 2008, American Society for Microbiology. All Rights Reserved.

Determination of Antibiotic Hypersensitivity among 4,000 Single-Gene-Knockout Mutants of Escherichia coli{triangledown} ,{dagger}

Cindy Tamae, Anne Liu, Katherine Kim, Daniel Sitz, Jeeyoon Hong, Elinne Becket, Ann Bui, Parrisa Solaimani, Katherine P. Tran, Hanjing Yang, and Jeffrey H. Miller*

Department of Microbiology, Immunology, and Molecular Genetics, the Molecular Biology Institute, and the David Geffen School of Medicine, University of California, Los Angeles, California 90095

Received 20 December 2007/ Accepted 30 June 2008


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ABSTRACT
 
We have tested the entire Keio collection of close to 4,000 single-gene knockouts in Escherichia coli for increased susceptibility to one of seven different antibiotics (ciprofloxacin, rifampin, vancomycin, ampicillin, sulfamethoxazole, gentamicin, or metronidazole). We used high-throughput screening of several subinhibitory concentrations of each antibiotic and reduced more than 65,000 data points to a set of 140 strains that display significantly increased sensitivities to at least one of the antibiotics, determining the MIC in each case. These data provide targets for the design of "codrugs" that can potentiate existing antibiotics. We have made a number of double mutants with greatly increased sensitivity to ciprofloxacin, and these overcome the resistance generated by certain gyrA mutations. Many of the gene knockouts in E. coli are hypersensitive to more than one antibiotic. Together, all of these data allow us to outline the cell's "intrinsic resistome," which provides innate resistance to antibiotics.


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INTRODUCTION
 
Antibiotics have had a major impact over the past 6 decades in the fight against infectious diseases (for a review by Davies, see reference 11). However, the spread of antibiotic-resistant microorganisms has reached an alarming point (1, 11, 35), prompting renewed efforts to find new antibiotics by detecting new targets through genomics, altering existing antibiotics, screening chemical (e.g., see reference 9) or peptide (21, 31) libraries for specific inhibitors (e.g., see reference 9), or finding new sources of antibiotics via metagenomics (e.g., see reference 53). While these lines of investigation show great promise, additional approaches are constantly being sought to yield a new generation of useful antimicrobial compounds. For instance, focusing on species-specific antibiotics rather than broad-spectrum antibiotics can result in important new agents (38), as could targeting bacterial transcription factors (5) or different processes, such as Holliday junction processing (21, 31) and quorum sensing (24), or even targeting host factors that support pathogen growth (33). Another approach, examined here, involves potentiating existing antibiotics by identifying targets for increasing susceptibility to specific antimicrobials. There are precedents for using such combinational therapy. For example, inhibitors of β-lactamase have been used together with β-lactam antibiotics (for a review by Buynak, see reference 7) and inhibitors of efflux pumps together with tetracycline in Escherichia coli (46) and with levofloxacin in Pseudomonas aeruginosa (37). In the case of chemotherapeutics, zebularine, a cytosine analog (41) and mutagen (34) that is converted in vivo to an inhibitor of cytosine deaminase (41), is used in combination with certain cytosine deaminase-susceptible cytosine-based drugs (14, 40). With regard to finding new targets for this type of approach, a number of genes that increase the sensitivities of microorganisms to different antibiotics have been identified (e.g., for a review by Drlica and Zhao, see reference 15; see also reference 42), but only recently have tools been available for systematic searches for these potential targets. A transposon library has been used to detect genes responsible for increased sensitivity to one of the antibiotics in a set of antibiotics in Acinetobacter baylyi (20), and a yeast deletion library has been screened against a set of DNA-damaging agents (58) and also a set of over 400 small molecules (25). In the work reported here, we used high-throughput screening of an E. coli knockout collection of close to 4,000 strains, each with a different gene inactivated (3), to look for mutants that are more susceptible to one of seven different antibiotics (see Table 1). We identify mutants with increased and decreased susceptibilities to ciprofloxacin (CPR) and those with increased susceptibilities to rifampin (RIF), vancomycin (VAN), ampicillin (AMP), sulfamethoxazole (SFX), gentamicin (GEN), and metronidazole (MET). In the case of CPR, VAN, and MET, we show that certain combinations of two mutations result in mutants with even greater susceptibilities. Moreover, for CPR, some of these mutations can counteract the resistance conferred by certain gyrA alleles. These results help to define new combinational drug targets and lay the groundwork for typing antibiotics by their resulting "sensitivity profile."


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  		TABLE 1. List of antibiotics


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MATERIALS AND METHODS
 
E. coli strains. The Keio collection is as described by Baba et al. (3), made from the starting strain BW25113 (10). This strain (lacIq rrnBT14 {Delta}lacZWJ16 hsdR514 {Delta}araBADAH533 {Delta}rhaBADLD78) is the starting strain used in the experiments reported here, unless otherwise stated. (Strains in the Keio collection with a JW designation, e.g., JW5115, JW5360, JW5474, carry deletions of sequences that were originally designated as open reading frames but were then demoted to an uncertain status.) We used the following strains for donors of the indicated markers for P1 transduction: CSH126 ({Delta}recA-srl)306 srl::Tn10-84 (44); P90C uvrD::mini-Tn10 (44; J. H. Miller, K. Kim, A. Liu, and C. Tamae, unpublished data); RJ3460 fis::cat (gift from Reid Johnson); CGSC6911 tolC6::mini-Tn10 (E. coli Genetic Stock Center); CGSC7550 ruvC67::cat (E. coli Genetic Stock Center); and CGSC7553 recG265::cat (E. coli Genetic Stock Center). DY330 (64) was converted to recC::cat by the procedure described below and was used as a donor for P1 transduction.

E. coli genetic methods. Unless otherwise stated, all genetic methods are as described by Miller (44), including P1 transduction and mutagenesis with 2-aminopurine (700 µg/ml) (see also reference 39 for exact details).

Use of the Deutz cryoreplicator. The Deutz cryoreplicator (12) contains 96 prongs on individual springs, allowing its frequent application to frozen glycerol cultures. The Keio collection (3) is maintained on 45 96-well microtiter plates and stored at –80°C in glycerol. Material from frozen microtiter plates was transferred to microtiter wells with 0.5 ml of LB medium, which were incubated overnight, and then the replicator was used to transfer a microdrop to microtiter wells with fresh LB medium containing 50 µg/ml kanamycin to prevent the growth of contaminants. (All of the strains in the Keio collection are Kanr.) After 3 to 4 h of growth, these plates were printed onto LB plates with different concentrations of different antibiotics. For the initial screening, kanamycin was present in the plates, but for all retests, Etests, and MIC determinations, kanamycin was not present. We screened four concentrations of CPR (5, 10, 15, and 25 ng/ml), two each of VAN (100 µg/ml and 150 µg/ml), RIF (7.5 µg/ml and 10 µg/ml), and GEN (0.3 µg/ml and 0.5 µg/ml), and one each of AMP (2 µg/ml) and SFX (400 µg/ml) as well as a control medium with no antibiotic. We initially screened 27 of the 45 microtiter plates in the collection with four different concentrations of MET (500, 600, 700, and 800 µg/ml) and the remaining 18 plates with 600 µg/ml.

Determination of MIC. MICs (2) were determined either by applying 104 to 105 CFU onto an LB plate with the appropriate concentration of the desired antibiotic and examining the plate after overnight incubation at 37°C or by Etests. In all cases, tests were performed on repurified strains. (In a few cases, MICs were confirmed by liquid culture tests, starting from an initial inoculum of 105 cells [2].) Etests were obtained from AB Biodisk North America Inc. (Piscataway, NJ). The appropriate test material was applied to a freshly plated lawn of an exponential culture of the desired strain on LB plates and incubated overnight at 37°C. Most of the mutants in the Keio collection grow indistinguishably from the starting strain on LB plates under the conditions tested. However, a number of mutants grow significantly more slowly (e.g., rnt, lptB, tonB, ubiG, and lpdA mutants), leading to potential artifacts in determining inhibition by antibiotics. In principle, all true inhibition by an antibiotic represents an inhibition of growth of a mutant to a greater degree than the inhibition of growth of the starting strain. MICs were therefore confirmed by optical density measurements of growth in liquid culture for all mutants that grow significantly more slowly than the starting strain in LB medium (without antibiotic).

Construction of E. coli knockout mutants. The procedure for constructing E. coli single-knockout mutants is essentially the same as described by Yu et al. (64). Briefly, a PCR product was prepared, one which contained an antibiotic resistance gene cassette, in this case the cat gene, flanked at both ends by 50-bp DNA sequences that are identical to sequences flanking the open reading frame of the target gene, in this case recC. The purified PCR product was used to transform the recombination-proficient E. coli strain DY330 (64). The transformants that were resistant to the antibiotic selection were further purified on the LB plates and were verified for the loss of the target gene by PCR. Standard P1 transduction was used to transfer the knockout allele from DY330 to a desired genetic background for analysis of its phenotype.

DNA sequencing of gyrA. We isolated a series of mutants resistant to high (100 and 500 ng/ml) concentrations of CPR, using BW25113 as the starting strain. We sequenced the relevant part of the gyrA gene (see Materials and Methods for details), and found four different mutations (generating S83L, D87G, G81D, and D87N), two of which have been described previously (4). One of these, resulting in a serine-to-leucine change at position 83 in the GyrA protein, confers resistance to CPR up to a concentration of 750 ng/ml. A second mutation, resulting in D87G, has also been detected in E. coli, although the two other mutations (G81D and D87N), have not been described previously. The protocol used to PCR amplify directly from a single colony was adapted from Haldimann and Wanner (22). Isolated colonies were resuspended in 50 µl of water. One microliter of the suspension was used to PCR amplify the gyrA gene by using the GyrA1 primer, 5'-TTATGGTTTACCGGCGAT-3', and the GyrA2 primer, 5'-ACGACCGTTAATGATTGCC-3'.

The PCR product was purified using the MinElut PCR purification kit (Qiagen, Valencia, CA). The purified PCR products were then sequenced using the GyrA1 primer. The DNA sequencing reactions were carried out using the BigDye Terminator v3.1 cycle sequencing kit (Applied Biosystems) on iCycler thermal cyclers (Bio-Rad), and the sequencing was performed on Applied Biosystems 3730 DNA analyzers at the UCLA Genotyping and Sequencing Core.

Chemicals. Kanamycin, tetracycline, chloramphenicol, RIF, VAN, SFX, GEN, AMP, and MET were purchased from Sigma (St. Louis, MO). CPR was purchased from ICN Biomedicals, Inc., Aurora, OH.


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RESULTS AND DISCUSSION
 
Screening. We screened the entire Keio collection of close to 4,000 strains (3) for mutants that are more sensitive than the wild type to one or more antibiotics of a set of seven different antibiotics (Table 1), CPR, VAN, RIF, AMP, SFX, GEN, and MET, at several different concentrations (see Materials and Methods for details). Figure 1 shows an example. We also tested for mutants resistant to CPR. This generated an initial set of close to 65,000 data points. Mutants showing increased susceptibility (or in the case of CPR, resistance or susceptibility) were then purified and retested from single colonies by several methods to determine the MIC. Figure 2 incorporates all of the data (see the supplemental material for detailed charts), and selected examples are given in subsequent tables. The mutants in Fig. 2 have been arranged according to the type of function affected, with black bars indicating the strongest effects. We see several types of mutants in most cases. Namely, some hypersensitive mutants are specific for each class of antibiotic and reflect the initial target and process affected. Other sensitivities probably arise from secondary targets and indirect effects and reflect the complexities of antibiotic action (see below; also see references 6 and 23). Also, some mutants show up on the sensitivity profiles of several different antibiotics and represent functions involved in general intrinsic resistance.


Figure 1
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  		FIG. 1. Effect of 7.5 ng/ml CPR on Escherichia coli. Ninety-six mutants from the Keio collection were printed onto LB plates with no CPR (left panel) and LB plates with 7.5 ng/ml CPR (right panel). Here, only two mutants, with knockouts of the xseA and recB genes, fail to grow on the plate with 7.5 ng/ml CPR. Further tests on purified colonies confirm their hypersensitivities.


Figure 2
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  		FIG. 2. Gene knockouts affecting increased sensitivity to one or more of the seven antibiotics tested. Strong sensitivity to a particular antibiotic is indicated by a black panel, while weaker sensitivities are indicated with a gray panel. See tables in the supplemental material for numerical values of MICs. The locus tags refer to the accession number (http://www.ecocyc.org). Categories are as follows: category 1, DNA replication, recombination, and repair; category 1A, functions indirectly affecting category 1; category 2, transport, efflux, cell wall, and cell membrane synthesis; category 2A, chaperones and functions related to category 2; category 3, protein synthesis; category 4, general metabolic reactions; category 5, regulation; category 6, prophage-encoded genes and cell adhesion; and category 7, unassigned genes.

CPR. CPR is a fluoroquinolone that binds to DNA gyrase and topoisomerase IV (for a review by Drlica and Zhao, see reference 15). DNA gyrase, which controls DNA supercoiling, is encoded by the gyrA and gyrB genes in E. coli. CPR-bound gyrase forms a complex with DNA that blocks replication and also results in the exposure of double-stranded DNA breaks. It is not surprising, therefore, that some of the strongest-susceptibility mutants are defective in genes involved in DNA binding, replication, and repair functions and in the repair of double-stranded breaks. New findings include the fis, xseA, and xseB genes leading to hypersusceptible phenotypes when inactivated. FIS is the most abundant of the DNA binding proteins (HU, IHF, HNS, FIS) that are associated with the bacterial nucleoid and is believed to play a role in compaction by bending the DNA (56). The xseAB genes encode ExoVII (8). It has been reported that recA and recB mutants are more susceptible to nalidixic acid, a related quinoline antibiotic (42). We find that recA and recC mutants are particularly sensitive to CPR (Fig. 2 and Table 2), with recB mutants also being sensitive (Fig. 2). This may be related to the repair of double-stranded breaks or, in the case of recA mutants, be a response to the generation of reactive oxygen species that have been postulated to be involved in cell death by bactericidal antibiotics (32). Mutants that are more sensitive to CPR as well as a set of other antibiotics (Fig. 2) are defective in cell wall and membrane synthesis and in efflux pumps (tolC). Previous work with E. coli had shown that polA and uvrD mutants have increased sensitivity to nalidixic acid (for a review by Drlica and Zhao, see reference 15), and recent studies revealed several genes in Acinetobacter baylyi that result in increased sensitivity to CPR, although only the acrB gene gave similar results in E. coli when the homologous gene knockouts were tested (20).


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  		TABLE 2. CPR sensitivities of single and double mutantsa

In the work reported here, the mutants with the strongest effects are close to 1 order of magnitude more sensitive than the starting strain to CPR. Double mutants with certain combinations of mutations, such as fis tolC and recC tolC (Table 2), approach sensitivities that are 2 orders of magnitude greater. The increased sensitivity can also counteract the effect of mutations that increase resistance to CPR, such as gyrA mutations. The change S83L in the gyrase A subunit is a single-step mutation that confers a high level of CPR resistance in E. coli (4). We rederived this mutation in strain BW25113 (see Materials and Methods). We used P1 transduction to transfer several of the gene knockouts conferring increased susceptibility (recC, fis, xseA, recA, and tolC) into BW25113 containing the S83L CPR-resistance-generating gyrA mutation. Table 3 shows the results. Clearly, the increased resistance to CPR can be partially reversed by sensitive single-step mutants and totally reversed by certain double-mutation combinations, for instance, tolC recC.


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  		TABLE 3. Effect of gene knockouts in CPR-resistant mutants

Table 4 shows the single-gene-knockout mutants that have measurably higher levels of CPR resistance than the wild type. Although close to 200 mutants were detected in the initial screen, a much smaller number of mutants show reproducible effects when examined more closely. None of the single-gene knockouts confer resistance to CPR at the levels seen for strains with certain point mutations in the gyrA gene (4; see below).


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  		TABLE 4. CPR-resistant strainsa

Sensitivity to VAN. VAN, a glycopeptide antibiotic that is effective on many gram-positive bacteria, does not normally affect gram-negative bacteria because it cannot sufficiently penetrate the outer cell membrane (47), which excludes many small molecules (e.g., see references 28, 50, and 51). Once in the cell, VAN interferes with the synthesis of peptidoglycan, the major structural component of the cell wall, specifically inhibiting peptidoglycan polymerase and transpeptidation reactions. It operates at an earlier stage in peptidoglycan biosynthesis than AMP. Although these latter enzymes are the primary targets once inside the cell, for a gram-negative bacterium such as E. coli, we would expect to see mutants that facilitate permeation of VAN well represented among the strains with increased sensitivity. We did detect numerous mutants that render E. coli susceptible to VAN at concentrations (100 µg/ml to 150 µg/ml) that do not affect the starting strain BW25113, which has a MIC of 500 µg/ml. The smpA mutant displays a MIC of 70 µg/ml. In one exceptional case, in a mutant with a surA defect, the MIC is lowered to 4 µg/ml, and the surA smpA double mutant displays a MIC of 1.5 µg/ml. (The increased sensitivities to VAN and certain other agents, resulting from surA defects, have been noted previously, although not quantified in this manner, as has an enhanced sensitivity in the surA fkpA ppiA ppiD quadruple mutant [28].) The SurA protein is one of four cis-trans proyl isomerases that aid protein folding in the periplasm, thus promoting maturation of outer membrane porins (see references 28 and 50 and references therein). SmpA is part of the YaeT outer-membrane-protein assembly complex (55), and mutations in some of these components have been shown to cause increased sensitivity to bacitracin, novobiocin, and RIF (51). Although many of the strong susceptibilities do, in fact, result from defects in genes involved in cell wall or outer membrane synthesis or integrity (e.g., pal, ompF, rfaC, htrB), other genes are involved in intracellular functions, including protein synthesis (tusC, tusD, rimK), perhaps indicating this latter process as a secondary target. These results suggest that VAN does indeed get into E. coli, although clearly at subinhibitory concentrations. This is supported by our findings that VAN partially induces the SOS system in E. coli at the concentrations used here (Miller, Kim, Liu, and Tamae, unpublished).

Sensitivity to RIF. RIF binds to the β-subunit of RNA polymerase in virtually all prokaryotes, blocking transcription. Extensive work has been carried out on RIF-resistant mutants in many different microorganisms (see references 18 and 45 and references therein). We screened for mutants more susceptible to RIF, using concentrations of 7.5 µg/ml and 10 µg/ml. (The MIC for RIF of strain BW25113 is 16 µg/ml.) Here, the pattern of sensitive mutants is more varied. The primary target cannot be eliminated by a gene knockout in a viable cell, but we do see mutants with defects in replication, recombination, and repair (e.g., uvrA mutants) and in protein synthesis (rpmE, rpmF, and rplA mutants), processes affected secondarily by blocking transcription. More general mutants are affected in the cell wall, cell membrane, or transport systems, and in some cases, these are the same mutants that are more sensitive to VAN (see below).

Sensitivity to AMP. We screened for mutants sensitive to 2 µg/ml AMP. (Strain BW25113 displays a MIC for AMP of 5 µg/ml with Etests and 6 µg/ml by plating.) The primary target of AMP, an aminopenicillin, is DD-transpeptidase (59), which is involved in generating peptidoglycan cross-links in the cell wall. This and other enzymes (e.g., carboxypeptidase and endopeptidase) are part of a set of "penicillin binding proteins." Several of the strongly sensitive mutants, mrcB and dacA mutants, have defects in penicillin binding proteins, and are found only in the AMP profile. Some mutants, however, have defects in protein synthesis (e.g., rpmF mutants). Again, we see that many of the strongly susceptible mutants have defects in the cell wall, cell membrane, or transport systems, and some of these are involved in susceptibilities to other antibiotics.

Sensitivity to SFX. SFX blocks the fifth step in the de novo synthesis of folic acid by inhibiting dihydropteroate synthetase (52), leading to defects in the synthesis of DNA since the synthesis of purines and thymine is interrupted. Thus, a set of susceptible mutants is involved in functions related to this target, including aspects of DNA recombination and repair (e.g., recA, recB, recC, and recG mutants). One of the moderately sensitive mutants has a knockout of the nudB gene, which encodes dihydroneopterin triphosphate pyrophosphatase (17), which catalyzes the second step in folate biosynthesis (17; see also reference 52).

Sensitivity to GEN. We screened strains at two different concentrations of GEN, 0.3 and 0.5 µg/ml. This antibiotic is an aminoglycoside that interferes with protein synthesis by binding to the 30S subunit of bacterial ribosomes yet, as can be seen from Fig. 2, has increased effectiveness against some mutants defective in 50S ribosomal proteins or the protein elongation factor Tu, in addition to a set of mutants with altered permeability. Some of these are sensitive to other antibiotics, as exemplified by tolC mutants, defective in the AcrAB-TolC efflux system, but others are specific to GEN, namely sapC and secG mutants.

Sensitivity to MET. MET is used in the treatment of Clostridium difficile-associated disease and in therapeutic regimens for Helicobacter pylori (e.g., see references 49 and 57). The active form of MET, generated by pyruvate-ferredoxin oxidoreductase-mediated reduction of the nitro group, directly interacts with DNA to distort its structure. In line with this, mutants that we found to be hypersensitive to MET include those with defects related to DNA functions. Thus, from Fig. 2, we see the helicase RecG and the UvrABC repair proteins UvrA and UvrC represented. Clearly, glutathione, a thiol involved in detoxifying certain stress-inducing factors, including oxidative stress, plays a key role in preventing killing by subinhibitory concentrations of MET, since the most susceptible mutant, the gshA mutant (see the supplemental material and Table 5), lacks the first step in the synthesis of glutathione ({gamma}-glutamylcysteine synthetase). (Gomez and Neyfakh [20] detected the gshA mutant as being involved in MET sensitivity in Acinetobacter baylyi but did not find sensitivity in an E. coli gshA knockout mutant, in contrast to the results reported here.) A mutant (the gshB mutant) lacking the second step is also sensitive, as is the cysB mutant, lacking the positive regulator of the cys regulon, and mutants (gorA and gorB mutants) defective in glutathione reductase. We constructed several double mutants, (gshA fis, gshA recC, gshA recG, and gshA uvrD mutants), and found that each was more sensitive than either of the two single mutants involved (Table 5).


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  		TABLE 5. Effect of single and double knockouts on sensitivity to MET

Perspective. Small molecules with antimicrobial properties can be characterized in any one of a number of ways, such as by their spectrum of activity on different bacterial strains, their effects on transcription at subinhibitory or inhibitory concentrations (19, 62, 63), or the type of synergistic interactions displayed with other antibiotics (30, 36, 60, 61). One can also examine antibiotics by their mechanism of action of stopping cellular growth or provoking cellular death, and recently, Collins and coworkers have argued that bactericidal antibiotics induce cellular death by a common mechanism involving the generation of deleterious hydroxy radicals (32). Here, we view antibiotics through their resulting susceptibility or "sensitivity profiles," namely which mutants among the 4,000 E. coli knockout mutants in the Keio collection (3) are strongly susceptible to a particular antibiotic. Looking at the overall picture displayed in Fig. 2, several trends emerge. We see that among the 4,000 gene knockouts, only a subset of these generate phenotypes hypersusceptible to even one of the seven different antibiotics that we examined in this study. In total, 140 gene knockouts, approximately 3.5% of all the viable knockouts, are involved in generating strongly increased sensitivities to even one of the seven antibiotics. (This number should increase as a larger number of antibiotics are examined.) These data define potential targets for small-molecule inhibitors that might potentiate one or multiple antibiotics, as has been done in several cases (7, 37, 46; see the introduction). On the one hand, each antibiotic (or at this stage, class of antibiotic) is associated with a specific set of gene knockouts that result in strong susceptibilities, for instance, gshA, gshB, and gor in the case of MET and mrcB and dacA in the case of AMP. These are related to primary targets of the respective antibiotics, although pinpointing these is not always simple, as the mechanisms and targets of antibiotics are more complicated than previously thought (23; see also reference 6). On the other hand, there is a distinct group of gene knockouts that appear in the sensitivity profiles of more than one antibiotic (Fig. 2). Many of these involve efflux systems, chaperones, and genes involved in cell wall and cell membrane synthesis and integrity. Thus, tolC mutants, lacking a key efflux system, are more sensitive to six of the seven antibiotics tested and tatC mutants to four of the seven. Interestingly, some mutants in this category, such as deoT and dksA mutants, are transcriptional regulators. DeoT, a member of the DeoR family of global regulators, is involved in the control of multiple unrelated genes (16), while the DksA transcription factor is also involved in many processes (48), including double-stranded-break repair (43). Taken together, all of these data allow us to envision the cell as having points of vulnerability in each of the essential processes that are favored targets of antibiotics. Specific proteins play a crucial role in providing intrinsic resistance by, in some way, protecting these points of vulnerability. Thus, we can imagine the bacterial "intrinsic resistome," a conceptual structure that is defined by the effects that we observe as we systematically dismantle it, as seen in the increased effects of double-gene knockouts (Tables 2 and 5). The intrinsic resistome involves not only multidrug efflux systems and proteins that maintain the integrity of the cell wall and outer membrane but also those that shield DNA from access to certain damaging agents and processes and those that repair DNA, the ribosomal proteins that, while not absolutely essential for cell growth, give the ribosome some resistance to certain agents.

How do "sensitivity profiles" correlate with microarray studies? Does one see an increase in expression for the genes that are pinpointed by the increased sensitivity resulting from their inactivation? The best comparison would be with E. coli studies using subinhibitory concentrations of the same antibiotics, such as those carried out by Shaw and coworkers (54), who used AMP, RIF, and also norfloxacin (NOR), a fluoroquinolone closely related to CPR. There is little correlation between their results and those reported here. Thus, none of the eight genes upregulated by subinhibitory concentrations of AMP and none of the five scorable genes upregulated by RIF appear in the profiles reported here. Of the eight genes upregulated by NOR, two cause increased susceptibility to CPR when inactivated, these being among the SOS genes (recA, recN) induced by this agent. At concentrations at and above the MIC, the lack of correlation is pronounced (see also reference 29). Only 2 of 55 genes upregulated by NOR, 0 of 14 scorable genes upregulated by RIF, and 1 of 11 upregulated by AMP appear in the CPR sensitivity profile. Microarray analyses are being employed to characterize the mechanism of action of antibiotics (e.g., see reference 6 and 27). Sensitivity profiles might offer a way of further characterizing mechanisms of action (see below).

Future experiments. Extensions and applications of this work are aimed at the following: (i) high-throughput screening of small-molecule libraries for codrugs that work at the subinhibitory concentration shown here and that are specific inhibitors of some of the enzymes pinpointed as being involved in preventing hypersensitivity to various antibiotics (recall that the targets revealed by the study reported here do not, in most cases, result in growth inhibition or cell death when inactivated in the absence of antibiotics); (ii) design of specific inhibitors of some of this latter group of enzymes whose three-dimensional structure is known; (iii) using the most-sensitive single and double mutants to screen for additional antibiotics in soil communities and other microbial communities (there is precedent for this, as a number of groups have utilized engineered strains to detect antimicrobial activity [e.g., see references 13 and 26]); (iv) determining the mechanism of increased sensitivity in a number of cases revealed here, for instance, those involving transcriptional regulators; and (v) characterizing additional antibiotics, both in the exact manner described here and also by using the reduced set of strains determined by this work, to rapidly detect the sensitivity profiles of large numbers of characterized and uncharacterized antibiotics after a more complete catalog of these profiles for known antibiotics is compiled.


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ACKNOWLEDGMENTS
 
This work was supported by a grant from the National Institutes of Health (ES0110875).


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FOOTNOTES
 
* Corresponding author. Mailing address: Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, CA 90095. Phone: (310) 825-8460. Fax: (310) 206-3088. E-mail: jhmiller{at}microbio.ucla.edu Back

{triangledown} Published ahead of print on 11 July 2008. Back

{dagger} Supplemental material for this article may be found at http://jb.asm.org/. Back


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Journal of Bacteriology, September 2008, p. 5981-5988, Vol. 190, No. 17
0021-9193/08/$08.00+0     doi:10.1128/JB.01982-07
Copyright © 2008, American Society for Microbiology. All Rights Reserved.



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