Abstract
Bacteria coordinate the response to oxidative stress through LysR-type transcriptional regulator (LTTR) OxyR. However, only fragmentary information on the regulation and function of OxyR has been gleaned in the opportunistic pathogen Pseudomonas aeruginosa. Here, we delineate the OxyR regulon using multi-omics analyses. OxyR is found to positively regulate several genes involved in quorum sensing (QS) and energy metabolism. OxyR is further involved in the negative regulation of amino acid transporters that was confirmed by metabolomics analysis. Finally, we uncover gltS, an OxyR regulon gene, could be used as a potential drug potentiation target. Altogether, our results confirm that, apart from its dominant role in defense against oxidative stress in P. aeruginosa, OxyR acts as a global regulator of QS, energy metabolism and amino acid homeostasis, but also serves as a model system to identify potential antibacterial target such as gltS.
Similar content being viewed by others
Introduction
Pseudomonas aeruginosa is a ubiquitous, Gram-negative bacterium that inhabits diverse ecological niches such as soils, marshes, and coastal marine waters as well as the surfaces of plants and animals1. As an opportunistic pathogen, P. aeruginosa is able to infect plants, animals, and humans, and has been recognized as one of the primary causative agents of nosocomial diseases with generalized symptoms such as inflammation and sepsis2,3,4. Due to its versatile adaptability and diverse metabolism and ever-mounting evidence for increased antibiotic resistance, diseases caused by P. aeruginosa represent a significant health threat despite significant advances in treatment alternatives.
During infection, P. aeruginosa produces a battery of virulence factors that contribute to colonization and infectivity, among which are the phenazine pyocyanin, the fluorescent siderophore pyoverdine and serine proteases such as elastase5,6,7. Expression of a large subset of those virulence factor-encoding genes is controlled via an intercellular, cell-to-cell communication system commonly referred to as quorum sensing (QS), whereby P. aeruginosa produces, secretes and responds to small extracellular signaling molecules called autoinducers (AI)8,9,10. In addition, QS in P. aeruginosa also regulates several other cellular processes including biofilm formation, adhesion, and genes involved in the oxidative stress response11.
As a consequence of its growth in highly diverse environmental niches, P. aeruginosa has to adapt to ever-changing environments, one of which is when it is exposed to a variety of oxidants. The most prominent and commonly found oxidants are reactive oxygen species (ROS), including hydrogen peroxide (H2O2), superoxide anion (O2.−) and hydroxyl radical (OH•)12,13. As one of the major challenges for living organisms, ROS cause damage to DNA, lipid membranes, proteins, and cofactors, and are therefore implicated in numerous human degenerative diseases (e.g., aging, atherosclerosis, inflammation, etc.). In addition, in contact with free ferrous iron, H2O2 is further reduced to the most damaging oxygen radical, OH•, via the Fenton reaction14. OH• reacts with virtually all known biomolecules at diffusion-limited rates.
Protection from oxidative stress is largely based on several defense mechanisms, including the production of antioxidant enzymes (catalase, superoxide dismutase, and peroxidase), iron sequestering proteins such as bacterioferritin and ferritin15, proteins like thioredoxins, glutaredoxin as well as the tripeptide, glutathione16. Extensive studies have focused on Escherichia coli as a model organism to investigate the regulation of oxidative stress responses. Many of these studies revealed that the bacterial genetic responses to oxidative stress are controlled through two major transcriptional regulators, OxyR and SoxR12,17,18,19,20. H2O2 activates the LysR-type transcriptional regulator (LTTR) OxyR via the oxidation of two conserved cysteines (Cys 199 and Cys 208) and formation of an intramolecular disulfide bond19,21. In E. coli, the oxidized form of OxyR induces the expression of a set of defensive genes including katG, ahpCF, dps, gorA, grxA, and oxyS20,22,23.
Similarly, to defend itself against oxidative stress, P. aeruginosa produces two superoxide dismutases (SOD, Mn-cofactored SodA and Fe-cofactored SodB), which represent the first line of defense against the superoxide anion O2.− converting it to H2O2 while three catalases (KatA, KatB and KatE) protect the bacteria from H2O2. Finally, at least four alkylhydroperoxide reductases (AhpA, AhpB, AhpCF, and Ohr) detoxify H2O2 and several organic peroxides24. The OxyR homologue in P. aeruginosa is crucial for the upregulation of the antioxidant genes katA, katB, ahpB, and ahpCF after exposure to H2O224. Other findings have revealed its role in the pathogenesis of P. aeruginosa25, in the iron uptake mediated by the siderophore pyoverdine26,27, and in the regulation of pyocyanin production28 and type VI secretion system29,30. Aside from those, transcriptomic analyses have shown that when faced with H2O2, P. aeruginosa exhibits an upregulation of the protection mechanism and a downregulation of the primary metabolism, suggesting a link between both processes31,32, possibly in part mediated by OxyR.
However, there is still little information concerning OxyR regulon in pathogenic bacteria including P. aeruginosa using RNA-seq analyses, especially under hypoxia. Recently, we described, via chromatin immunoprecipitation, that P. aeruginosa OxyR binds to other targets, suggesting that the OxyR regulon is not confined to the oxidative stress response genes30. In this study, we used transcriptomic and metabolomic analysis to identify the effects of oxyR disruption under normal growth condition (in the absence of exogenous H2O2) and determined that OxyR not only regulates the oxidative stress protection response, but also controls the expression of an array of QS-related genes and amino acid transporters. Further phenotypic analysis has showed that several genes such as gltS, encoding a glutamate/sodium symporter, within OxyR regulon could be used to enhance the antibacterial killing, suggesting the potential role of oxyR in drug discovery. These findings shed light on the complexity of oxidative stress response in P. aeruginosa and provide valuable insights into the functionality of OxyR in bacteria.
Results
OxyR regulon revisited in P. aeruginosa
To gain insight into the regulatory breadth of OxyR in P. aeruginosa, we carried out a global analysis of the transcriptional responses without the addition of H2O2, to determine the number of OxyR-regulated genes under normal growth conditions. The reason to exclude the induction of extra oxidative stress via the addition of H2O2 lies in the possible secondary signals generated by the inducer, which distinguishes this study from previously published transcriptome analyses22,31,32. Our goal was, therefore, to determine the global effect of oxyR deletion under standard lab growth conditions for P. aeruginosa.
P. aeruginosa cells were harvested at the early stationary phase and RNA was extracted and processed according to the recommendations of Illumina system for RNA-seq analyses. After data qualification control and processing, we finally obtained a comprehensive data set summarized in Supplementary Table 1 and Fig. 1. Overall, our results exhibited high quality and accuracy since only little difference can be detected between two separate data sets by applying a stringent cut-off on P-value (P < 0.01, Supplementary Table 1). As shown in Fig. 1, when bacteria were grown in LB, disruption of P. aeruginosa oxyR caused changes in the expression of 510 genes (9% of all P. aeruginosa genes), among which 411 genes were repressed and 99 genes upregulated, suggesting that OxyR mainly acts as an activator. A complete list of differentially expressed genes is shown in Supplementary Table 1. Functional classification reveals that genes involved in adaptation, energy metabolism, membrane proteins, putative enzymes, secreted factors, and transcriptional regulators showed a decreased transcription level in oxyR mutant (Fig. 1A), while genes involved in the transport of small molecules as well as genes related to phage are largely increased at transcriptional levels (Fig. 1A). As anticipated, the typical OxyR regulon associated with the oxidative stress response, including katE, snr1 and pntAA were found to be down-regulated in this study (Supplementary Table 1; −2.4, −2.8 and −1.1 in log2FC, respectively)30, which clearly demonstrated oxyR mutation led to dysfunction of these genes.
A Functional classification of P. aeruginosa OxyR regulon under hypoxia condition. Functional classes were obtained from www.pseudomonas.com82. Two groups of values (promoted genes and repressed genes in the oxyR mutant) were chosen and compared. Values indicate the number of oxyR-controlled genes within the respective classes. B qRT-PCR validation of the microarray data. Randomly selected genes from were checked with quantitative real-time PCR analysis as described in Materials and Methods. All data were obtained from at least two independent experiments with at least three replicates. C Mean log2 ratios of the qRT-PCR data are plotted against the mean log2 ratios of the RNA-seq data.
In addition, a selection of differentially expressed genes from each condition was used to confirm the RNA-seq data using quantitative Real-Time PCR (qRT-PCR) and the results demonstrated good correlation with the RNA-seq results (linear correlation analysis, R2 = 0.9809) (Fig. 1B, C). Furthermore, we have used Sanger sequencing to identify the integrity of lasR in our oxyR mutant and ruled out the possibility that lasR point mutations in the oxyR background. Since this mutation occurs in vitro and in vivo and might complicate the interpretation of our RNA-seq results.
OxyR positively regulates virulence associated genes
As can be seen from Supplementary Table 1 and Fig. 2A, the expression of several virulence genes was downregulated in the oxyR mutant, including QS-regulated genes. Specifically, two phenazine biosynthesis operons (phzA1B1C1D1F1G1 and phzA2B2C2D2F2G2), amb antimetabolite biosynthesis operon (ambABCDE)33, PQS signal synthase operon (pqsABCDE), hydrogen cyanide synthase operon (hcnABC), alkaline protease operon (aprXDEFAI), rhamnolipid synthesis operon (rhlAB), lasA, lasB, chiC, were highly repressed in oxyR mutant. In addition, a group of key regulators such as rhlR, mvfR, vqsR, vqsM, pprA, and pprB were also found to be repressed in oxyR mutant, explaining why these QS-regulated genes were downregulated and indicating that oxyR plays a vital role in the regulation of QS signaling in P. aeruginosa28.
A OxyR positively regulates virulence associated genes. Top 15 genes involved in virulence are shown as representatives of QS-regulated genes. PA number and gene names (if available) are both shown. B OxyR regulon shared overlap with custom QS regulon. Venn diagrams showing the overlap between QS regulon and P. aeruginosa OxyR regulon. More than 224 genes were shown in both regulons in P. aeruginosa. C OxyR positively regulates energy metabolism in P. aeruginosa. D OxyR positively regulates putative enzymes in P. aeruginosa, mainly of those enzymes belong to oxygenase. E OxyR negatively regulates amino acid homeostasis. Transporters of small molecules are selected to show.
Given the inhibition of known QS systems in P. aeruginosa, we aimed to determine the overlap between OxyR regulon and QS regulon under typical growth conditions. We then integrated the previously identified QS regulon into a custom made QS regulon34,35 and compared it with the revisited OxyR regulon. Clearly, we found that our determined OxyR regulon showed a close relationship with custom QS regulon (Fig. 2B). More than 200 genes (224) were identified to overlap with the custom QS regulon (489 genes) in P. aeruginosa, suggesting that oxyR has a substantial impact on the regulation of QS systems and clearly this positive regulation of QS systems will contribute to the complex regulatory network of P. aeruginosa.
In addition, genes involved in protein secretion were also downregulated in the oxyR mutant. For instance, type VI secretion system (T6SS) gene clusters H2-T6SS (PA1656 to PA1669) and H3-T6SS (PA2360 to PA2373) were both repressed in the oxyR mutant, probably due to the inhibition of QS systems that positively regulate H2- and H3-T6SS expression36,37. Besides, the general secretion pathway (type II secretion system) was also repressed in the oxyR mutant, suggesting that the secretion of most signal-peptide-dependent exoproteins was probably decreased.
Altogether, we have unraveled that the expression of a large battery of genes involved in virulence is downregulated in oxyR mutant, indicating that OxyR acts as a positive regulator of virulence in P. aeruginosa.
OxyR positively regulates energy metabolism in P. aeruginosa
It was previously reported that H2O2 treatment of P. aeruginosa led to decreased expression of primary metabolism, including genes involved in energy generation, respiration chain complex, and oxidative phosphorylation31. In our study, we observed a tuning of energy metabolism in the oxyR mutant (Fig. 2C and Supplementary Table 2), suggesting that without protection from intact OxyR, P. aeruginosa cells are undergoing oxidative stress similar to H2O2 exposure. Among these genes, the heme-copper oxidase superfamily of enzymes, cytochrome c and ubiquinol oxidases were highly repressed at the transcriptional level. The expression of genes involved in denitrification was also decreased in the oxyR mutant compared with wild type PAO1, suggesting that the oxyR mutant was undergoing reduced cellular respiration and denitrification even without the addition of extra oxidants.
In addition, we noticed that in the oxyR mutant, the expression of multiple monooxygenases was reduced (Fig. 2D and Supplementary Table 2). As we mentioned earlier, we observed a downregulation of PQS biosynthesis genes (pqsABCDE operon) in the oxyR mutant (Supplementary Table 1). Interestingly, the pqsH gene was found to be downregulated (46-fold) when the oxyR mutant was grown in LB. This is of note because PqsH catalyzes the terminal reaction from 2-heptyl-4-quinolone (HHQ) to PQS, a process involving oxygen (O2) and NADH38. It is worth to mention that PQS was also demonstrated to exhibit both oxidant and antioxidant properties39 partly because of its iron-chelating properties40,41. When we overproduced pqsH in the oxyR mutant using a constitutive expression system, we found that increased PqsH production sensitized the oxyR mutant to oxidative stress and led to a decreased survival rate in a serial dilution analysis in oxyR (Fig. 3A and 3B). Likewise, another FAD-dependent monooxygenase, PqsL, involved in HQNO production42, when overproduced in the oxyR mutant renders cells even more sensitive to oxidative stress (Fig. 3A and 3B). In contrast, overexpression of pqsH and pqsL in wild-type PAO1 cells elicited the opposite response, namely, a higher plating efficiency in LB (Fig. 3B), which could be explained by the induction via the functional OxyR of the expression of a battery of defensive genes.
A Growth inhibition by H2O2 as determined by agar diffusion assays. Monooxygenase-producing strains (with pUCP-pqsH and pUCP-pqsL) in PAO1 exhibited an increased resistance towards H2O2 as compared to that of wild type (student’s t test; p < 0.01; *, p < 0.001). However, monooxygenase-producing strains in the oxyR mutant exhibited an increased sensitivity towards H2O2 as compared to the control (student’s t test; p < 0.01; *, p < 0.001; n = 3). The diameter of the inhibition zone is given as the mean ± SEM of triplicate samples. B Serial dilution analysis of the monooxygenase-producing strains as compared to the control. The results validated the growth inhibition effect of the monooxygenases in the oxyR mutant and the increased fitness when expressed in PAO1 wild type. The overnight bacterial cultures were diluted from 109 to 102 per ml.
To resist the challenge of iron-related Fenton reaction, we have noticed that in the oxyR mutant, several iron-associated genes, such as fpvF, fpvG, and feoB (Supplementary Table 1) were upregulated, indicating that OxyR negatively regulates these genes and related processes.
Altogether, we have uncovered the tuning of a repertoire of energy metabolism-associated genes as one of the underlying protective mechanisms in P. aeruginosa.
OxyR negatively regulates amino acid homeostasis
To further understand the survival strategies adopted by oxyR, we noticed that a wide variety of genes encoding transporters of small molecules were altered, especially these involved in amino acid transport (Fig. 2E and Supplementary Table 3). Homeostasis of more than 13 amino acids were affected in the oxyR mutant, indicating that OxyR mediated this newly identified process in bacteria to resist against oxidative stress. Among these genes, gltS (PA5176), encoding a transporter involved in glutamate/sodium symport, showed the highest expression level in the oxyR mutant (10-fold increase). In addition, genes encoding transporters involved in branched-chain amino acids (leucine, isoleucine, and valine), aromatic amino acids (tryptophan, tyrosine, phenylalanine), lysine, arginine, ornithine, histidine, glycine-glutamate, proline, and alanine were all upregulated in oxyR mutant compared to wild type PAO1. This finding has raised the possibility whether the transport of these amino acids could be involved in oxidative stress defense.
To prove this hypothesis, we used untargeted metabolomics to verify these physiological changes in oxyR mutant compared to wild type PAO1. As shown in Fig. 4A and Supplementary Table 4, we showed that a wide array of pathways has been affected, especially the amino acid metabolism including cysteine and methionine, tryptophan, and glutamate. Furthermore, we have classified these differential metabolites into five major groups (Fig. 4B) and found that majority of these metabolites have been overproduced in oxyR mutant compared to wild type PAO1, indicating these metabolites are playing protection roles against ROS. Interestingly, most of them are amino acids or derivatives of amino acids, further suggesting the involvement of amino acids in defense against oxidative stress. In addition, one of the most prominent findings in our metabolite analysis is that we confirmed that oxyR mutant, which has cell death caused by ROS attack, underwent oxidation of guanine43 and finally a reduced dGTP pool in cells (Fig. 4B).
A Score plot of OPLS-DA (orthogonal projections to latent structures-discriminant analysis) model obtained from PAO1 and oxyR metabolic profiling data (R2X = 0.491, R2Y = 0.885, Q2 = 0.549). Both groups showed significant separation and most data sets are located in Hotelling’s T-squared ellipse ( > 95%), with one exception in PAO1 data set. (B) Pathway enrichment analysis of oxyR metabolites as compared to PAO1. C Differential metabolites in oxyR mutant. Gray bars, solvents; blue bars, amino acids; Khaki bars, amino acid derivatives; orange bars, nucleotides; pink bars, groups of reduced metabolites. Data are means ± SEM (n = 6). D Spot assay of amino acids in growth complement of oxyR mutant under aerobic condition. 5 μM methionine (Met), cysteine (Cys), and aspartate (Asp) were used in a final concentration supplemented in LB agar plates (CK). The overnight bacterial cultures were diluted from 109 to 102 per ml.
To prove the potential involvement of amino acids in defense against oxidative stress, we sought to determine whether certain amino acid found in this study could restore or promote the growth of oxyR mutant under normal growth condition (Fig. 4C). We incorporated one of the amino acids, methionine, into LB agar plate and revealed that it could improve the growth of oxyR mutant under normal growth condition, where oxidative stress exists. Supplementation of cysteine and aspartate to LB agar plates gave rise to the same restoration results for oxyR mutant (Fig. 4C).
Altogether, we have determined that oxyR has been involved in amino acid homeostasis in bacterial cells.
Elucidation of gltS as a drug potentiation target in P. aeruginosa
The growth defect of oxyR mutant has been described previously and it was noticed that under hypoxia, the oxyR mutant restored its growth as compared to wild type28. Furthermore, we have observed that under hypoxia, the transcription of gltS was greatly upregulated in oxyR mutant, prompting us to hypothesize that gltS might be involved in defense against oxidative stress in P. aeruginosa. To prove this, we constructed an in-frame deletion mutant of gltS and measured intracellular ROS production of gltS compared to PAO1 by using the redox dye dihydro-dichloro-fluorescein diacetate (H2DCFDA). As shown in Fig. 5A, disruption of gltS could significantly increase the production of ROS and complementing gltS in a low-copy shuttle vector pUCP20 could restore the ROS levels in gltS mutant to the wild type level. Our results clearly demonstrate that GltS is involved in the generation of endogenous ROS in P. aeruginosa.
A ROS generation in gltS, PAO1, and its derivatives. The median of fluorescence intensity of 50,000 log phase grown cells treated with 20 mM H2DCFDA is given. The assays were performed three times with independent cultures. Data are means ± SEM. Significance was determined by Student’s t test; p < 0.01; n = 3. Evaluation of susceptibility to killing by antibiotics. Time course survival analysis of gltS and PAO1 treated with gentamicin (B), tobramycin (C) and ampicillin (D). Error bars are indicated, mean ± SEM for all plots. Student’s t test; p < 0.01; n = 3. (E) Synteny analysis of GltS in ESKAPE pathogens. Complex syntenies were obtained by using P. aeruginosa GltS protein sequence as query sequence to search against indicated Pseudomonads species. A consistent color coding permitted the correct identification of both orthologs and paralogs. The genes corresponding to the query proteins are drawn in bold and boxed with light olive color.
It is widely acknowledged that bactericidal antibiotics share a common mechanism of action through generation of ROS to mediate cell death44. Furthermore, the generation of endogenous ROS in bacterial cells could potentiate the action of bactericidal antibiotics45. To test whether gltS could be used as a drug potentiation target, we determined bacterial killing during treatment with the aminoglycoside gentamicin and tobramycin, the β-lactam ampicillin and the fluoroquinolone ciprofloxacin. We found that the gltS mutant presented an increased sensitivity to the aminoglycosides (Fig. 5B, C) and β-lactam (Fig. 5D).
To further explore the mechanisms underlying gltS-mediated drug potentiation, we initially conducted growth curve analyses comparing the gltS mutant, its parental strain PAO1 and complementary derivates. As depicted in Supplementary Fig. 1A, the gltS mutant exhibited robust growth fitness comparable to PAO1, while the complementary strain with functional gltS showed intermediate growth. Notably, overexpression of gltS resulted in growth inhibition. These findings effectively dispelled the notion that the impaired survival of gltS in the presence of antibiotics stemmed from slower growth. Subsequently, we monitored the growth of these strains over 24 h under various antibiotic treatments. It was striking that treatment with bactericidal antibiotics gentamicin (Supplementary Fig. 1B), tobramycin (Supplementary Fig. 1C), and ampicillin (Supplementary Fig. 1D), significantly impaired the growth of gltS mutant relative to PAO1, solidifying the link between gltS disruption and heightening antibiotic susceptibility in P. aeruginosa. In contrast, the gltS mutant displayed no growth inhibition when exposed to the bacteriostatic antibiotics tetracycline (Supplementary Fig. 1E), underscoring the specificity of the observed effects.
We next asked whether GltS is conserved among ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, P. aeruginosa, and Enterobacter spp.) and therefore could be broadly used as a drug potentiation target to treat bacterial infections46. As can be seen from Fig. 5E, gltS is presents in all ESKAPE pathogens except in Enterococcus faecium, suggesting that GltS is well conserved among pathogens (5 out of 6 major pathogens, 83.3% prevalence).
In summary, we have elucidated that gltS is involved in endogenous ROS production and could be used as a potential drug potentiation target to enhance antibacterial killing by bactericidal antibiotics, especially aminoglycosides and β-lactams.
Discussion
OxyR is an important regulator of the oxidative stress response in bacteria that functions as a H2O2 sensor to activate gene expression via the formation of an intermolecular disulfide bond19. In the model organism E.coli, it was reported that OxyR could not only control the expression of the oxidative stress response genes but is also implicated in other processes such as iron uptake, Fe-S cluster assembly and repair, heme biosynthesis and sRNA regulation22,23,47. In the human opportunistic pathogen P. aeruginosa, it is acknowledged that OxyR is involved in the oxidative stress response genes, iron uptake, virulence, and the production of the phenazine compound pyocyanin25,26,27,28. In addition, transcriptomic analyses have shown that exposure to H2O2 in P. aeruginosa resulted in an upregulation of genes involved in protection mechanisms and a downregulation of those for primary metabolism31,32. More recently, structural details of OxyR in diverse bacteria provided valuable insights into the mode of action of peroxide sensing48,49,50.
In this report, we demonstrate that P. aeruginosa OxyR is engaged in more processes than previously appreciated, particularly via its connection with QS, energy metabolism, and transport of small molecules (Fig. 2). By using systems-level transcriptomic and metabolic analysis, we revealed (i) the mechanism of survival of oxyR in hypoxia, involving the downregulation of energy metabolism, virulence, and putative enzymes, particularly monooxygenases, such as pqsL and pqsH (Fig. 3); (ii) the OxyR regulon in routine growth conditions confirms the strong link with QS, suggesting that oxyR is a master regulator of virulence; (iii) the OxyR regulon provides insights into the antibacterial killing by antibiotics, providing substantial number of novel drug targets in bacteria. Therefore, we have not only uncovered the OxyR regulon in P. aeruginosa, but also established its potential application in antibiotics discovery against human pathogens.
To survive in aerobic environments, the oxyR mutant has evolved numerous strategies to combat the attack of ROS. One of the known strategies is the production of protective pigments such as pyocyanin to complement the growth defect of the oxyR mutant in aerobic conditions28. This is due to the reversible redox trait of pyocyanin51. In this study, we have unraveled another survival strategy adopted by oxyR, which involves the downregulation of genes controlled by QS, genes encoding putative enzymes such as monooxygenases, and genes involved in energy metabolism. For example, we have confirmed that overexpression of monooxygenases pqsL and pqsH sensitized P. aeruginosa to oxidative stress (Fig. 3), indicating that endogenous utilization of oxygen and subsequent production of ROS are simultaneously occurring in bacterial cells. In line with this result, Schertzer and colleagues confirmed that PqsH catalyzes the terminal step in PQS production using the substrates HHQ, NADH and oxygen38. Furthermore, PQS has also been shown to have pro-oxidant and iron-chelating activity, both of which are related to oxidative stress response39,40. Therefore, P. aeruginosa has evolved strategies to avoid the use of oxygen and generation of ROS to survive in aerobic conditions. Besides this strategy, downregulation of energy metabolism such as cytochrome c-mediated respiration (Fig. 2) has been further employed to mitigate the effect of oxidative stress, consistent with previous findings31,52.
Interestingly, we discovered a large repertoire of transporters of small molecules that have been upregulated by our systems-level transcriptomic and metabolic analysis of oxyR mutant compared to wild type PAO1. Our conclusion has been reinforced by a study of Acinetobacter baumannii exposed to H2O253. Metabolic analysis has provided complementary measurement of amino acid influx in bacterial cells and offered opportunities to identify new metabolites or biomarkers for certain biological processes. In our study, this combinatory method has led to the identification of amino acids such as methionine, cysteine and aspartate necessary for the recovery of growth defect of oxyR mutant under aerobic condition (Fig. 4). Sulfur-containing amino acids such as methionine and cysteine are the most easily oxidized and these oxidation events are usually reversible and physiologically relevant54,55,56. In E. coli, it was found that proline metabolism could increase oxidative stress resistance57. Also, it was confirmed that glutamate could promote survival of Neisseria meningitidis during evasion of polymorphonuclear neutrophil leukocytes58. Therefore, bacterial amino acid homeostasis has arisen as a survival tactic to cope with oxidative stress.
The unexpected result from our study is that we have leveraged the OxyR regulon for the identification of one potential drug potentiation target, gltS. We have shown that deletion of gltS led to enhanced sensitivity to aminoglycosides and β-lactam, which was probably caused by the accumulation of ROS in P. aeruginosa cells. Previously, the potentiation of endogenous microbial ROS production has been utilized to enhance the antibacterial activity by oxidants and antibiotics45. Our study further strengthened this finding by extending endogenous ROS-potentiating gene repertoire to include amino acid transporters into ROS metabolic pathways45. Further study found that clinically relevant mutations in core metabolic genes confer antibiotic resistance and it was particularly interesting to note that glutamate synthase encoding genes gltB, gltD, and gltA were found to acquire mutations during antibiotic treatment59. Both studies strongly support our finding and conclusion that gltS could be potentially useful in antibiotic potentiation treatment. However, the idea that ROS mediated bacterial cell death has faced significant challenges, as several technical and biological concerns have emerged60,61,62. Therefore, it would be essential to conduct rigorous experiments to exclude the potential involvement of factors other than ROS in gltS-mediated antibiotic potentiation.
The predicted function of gltS is associated with glutamate/sodium ion symport, yet it has been seldom studied63,64,65. Previous study proved that disruption of gltS did not affect the utilization of glutamate but did impair the utilization of N-acetyl-L-glutamate65. It was further hypothesized that gltS, acting as a novel transporter, collaborates with its upstream gene (PA3175, a homologue of formiminoglutamate hydrolase) to form an operon for N-acetyl-L-glutamate utilization. In our study, we generated an in-frame deletion mutant of gltS and observed robust growth compared to wild type PAO1. Conversely, overexpression of gltS resulted in growth inhibition. The distinct growth response of the gltS mutant to bactericidal and bacteriostatic antibiotics suggest a novel role for gltS, potentially linking N-acetyl-L-glutamate utilization to the ROS response. The detailed mechanisms involved in these processes need further investigation.
Altogether, we have revisited the OxyR regulon and found OxyR acts as a global regulator of QS, energy metabolism and amino acid homeostasis. Importantly, by using multi-omics techniques and phenotypic verification, we have confirmed our results and discovered that gltS, one of the OxyR regulon genes, could be used as a potential drug potentiation target in pathogenic bacteria, such as P. aeruginosa. Our future work will focus on searching for more potential drug targets by using oxyR as a model and for drugs specifically targeting gltS as well as the molecular mechanisms underlying gltS-mediated antibiotic potentiation.
Methods
Bacterial strains and culture conditions
The P. aeruginosa wild-type PAO1 strain, its isogenic mutant oxyR, gltS as well as other derivative strains were used in this study and triplicate cultures were grown in Luria-Bertani (LB, BD) at 37 °C. When necessary, various class of antibiotics and other chemicals, such as glutamine, were supplemented at the specified concentrations.
Spot assay
0.1 M stock solutions of L-Asp, L-Met, L-Cys, and L-His (Biotopped Technology Co., Ltd., Beijing) were prepared. The solutions were sterilized using a 0.22 µm filter to ensure aseptic conditions and stored at 4 °C for subsequent use. PAO1 and its derivatives were selected and cultured in 5 mL of LB liquid medium. A total of 28.5 mL of LB agar medium was aliquoted into square petri dishes pre-marked with scale lines. To do this, 1.5 mL of each amino acid solution was added to achieve a final concentration of 5 mM for each amino acid. The medium was gently agitated to ensure homogenous distribution of the amino acids. The overnight bacterial cultures were serially diluted to a range of concentrations from 10−1 to 10−9. Aliquots of 5 µL from each dilution were spotted onto the prepared LB agar plates containing the amino acids. The inoculated plates were incubated in a 37 °C constant temperature incubator. The growth of the bacterial colonies was monitored and recorded over a set period.
Growth curve
Overnight cultures of bacterial strains in LB were diluted (1:100) in 3 ml LB medium and precultures incubated aerobically at 37 °C in a shaker at 200 rpm to an OD600nm of 0.5. The precultures were further diluted (1:100) in 1 ml LB medium. Growth was then analyzed in 96-wells microtitre plate containing 100 µl LB medium to which 100 µl of diluted precultures containing 105 cells was added to obtain a final 1:200 dilution. The microtitre plates were incubated for 24 h at 37 °C in SpectraMax ID3 (Molecular Devices, USA) using the following settings: absorbance measured every 1 h at 600 nm after shaking for 10 s. Each culture was prepared in triplicate.
Molecular manipulation
Isolation of plasmid and genomic DNA from E. coli and restriction enzyme digestion were performed according to the manufacturer’s instructions (Qiagen). DNA cloning, transformations and agarose gel electrophoresis were done as previously described66. In-frame and unmarked gltS deletion mutant in P. aeruginosa PAO1 was constructed using the suicide vector pEX18Ap as described with modifications67,68. Briefly, approximately 500 bp upstream and downstream sequences flanking gltS were amplified by PCR and fused with overlapping PCR. The PCR product was excised from the agarose gel and cloned into the pEX18Ap vector, resulting in the plasmid pEX18Ap-gltS. The pEX18Ap-based deletion allele was mobilized to P. aeruginosa and integrated into the chromosome by single crossover using E. coli S17-1 λpir as the delivery strain. Double crossover events were subsequently selected by growth in the presence of 5% sucrose. The gltS deletion mutant was confirmed by both PCR and sanger sequencing. Complementation analysis was done by cloning the intact gltS gene into the shuttle vector pUCP20 to generate the pUCP-gltS and introducing into the deletion mutants and wild type PAO1. The empty vector pUCP20 was also introduced to the gltS mutant and PAO1 as a control.
RNA extraction
RNA extraction and subsequent sequencing data processing were carried out according to our previous study69, with minor modifications. Overnight cultures of P. aeruginosa in LB were used to inoculate fresh LB medium in a 1:1000 dilution. After 12 h of incubation at 120 rpm at 37 °C, one ml of culture with an OD600nm of ~2.0 was immediately fixed with 2 ml of RNA Protect Reagent (Qiagen), following the manufacturer’s instructions, and the fixed cell pellets were frozen at −80 °C until further use. All experiments were performed with three technical replicates. Total RNA was extracted using TRIzol® Reagent according to the manufacturer’s instructions (Invitrogen) and genomic DNA was removed using RNase-free DNase I (TaKaRa). Then RNA quality was determined using 2100 Bioanalyzer (Agilent) and quantified using the ND-2000 (NanoDrop Technologies). High-quality RNA sample (OD260/280 = 1.8 ~ 2.2, OD260/230 ≥ 2.0, RIN ≥ 6.5, 28S:18S ≥ 1.0, >10 μg) was used to construct the sequencing library.
Library preparation, and Illumina Hiseq sequencing
RNA-seq strand-specific libraries were prepared following TruSeq RNA sample preparation Kit from Illumina (San Diego, CA), using 5 μg of total RNA. Briefly, rRNA was removed by RiboZero rRNA removal kit (Epicenter), fragmented using fragmentation buffer. cDNA synthesis, end repair, A-base addition and ligation of the Illumina-indexed adaptors were performed according to Illumina’s protocol. Libraries were then size selected for cDNA target fragments of 200 ~ 300 bp on 2% Low Range Ultra Agarose followed by PCR amplified using Phusion DNA polymerase (NEB) for 15 PCR cycles. After quantification by TBS380 Mini-Fluorometer, paired-end libraries were sequenced by Shanghai Biozeron Biotechnology Co.,Ltd (Shanghai, China) with the Illumina HiSeq PE 2 × 151 bp read length.
Reads quality control and mapping
The raw paired end reads were trimmed, and quality controlled by Trimmomatic with default parameters70. Then clean reads were separately aligned to the reference genome (Pseudomonas aeruginosa PAO1, Accession number NC_002516) with orientation mode using Rockhopper software71,72, which was a comprehensive and user-friendly system for computational analysis of bacterial RNA-seq data. As input, Rockhopper takes RNA sequencing reads generated by high-throughput sequencing technology to calculate gene expression levels with default parameters.
Differential expression analysis and functional enrichment
To identify DEGs (differential expression genes) between two different samples, the expression level for each transcript was calculated using the fragments per kilobase of read per million mapped reads (RPKM) method. The method edgeR was used for differential expression analysis73. The DEGs between two samples were selected using the following criteria: the logarithmic of fold change was greater than 2 and the false discovery rate (FDR) should be less than 0.05. To understand the functions of these differential expressed genes, GO functional enrichment and KEGG pathway analysis were carried out by Goatools74 and KOBAS75, respectively. DEGs were significantly enriched in GO terms and metabolic pathways when their Bonferroni-corrected P-value was less than 0.05.
Quantitative real-time PCR (qRT-PCR)
Bacterial cells were harvested in the stationary phase, bacterial RNA was extracted by using RNeasy Midi Kit (Qiagen). The purity and concentration of the RNA was determined by NanoDrop ND-1000 spectrophotometer (Thermo Scientific). First-strand cDNA was reverse transcribed from one microgram of total RNA by using First-strand cDNA Synthesis Kit (Amersham Biosciences). qRT-PCR was performed in a Bio-Rad iCycler with Bio-Rad iQ SYBR Green Supermix (Bio-Rad). For all primer sets, the following cycling parameters were used: 94 °C for 3 min, followed by 40 cycles of 94 °C for 30 s, 55 °C for 45 s, and 72 °C for 30 s, followed by 72 °C for 7 min. The outer membrane lipoprotein oprI gene was used to normalize gene expression76. Amplification products were verified by electrophoresis on a 0.8% agarose gel. For statistical analysis of relative gene expression, the 2-∆∆CT method was used77. All experiments were carried out in triplicate with three biological replicates. Signification difference was considered when p value < 0.5 using Student’s t test.
Metabolites extraction
Metabolomics analyses were carried out according to previous studies78,79, with minor modifications. 60 mg of sample was taken and placed in an EP tube, then add 1200 μL extraction liquid (V methanol: V acetonitrile: V water = 2:2:1, which was kept at −20 °C before extraction) and 20 μL internal standard. Homogenized in a ball mill for 4 min at 45 Hz, then ultrasound treated for 5 min (incubated in ice water). After homogenization for 3 times, incubation for 1 h at −20 °C to precipitate proteins. Then centrifuged at 12000 rpm for 15 min at 4 °C. Transfer the supernatant (320 μL) fresh into EP tubes, dry the extracts in a vacuum concentrator without heating, add 100 μL extraction liquid (V acetonitrile: V water = 1:1) reconstitution. Vortex 30 s and sonicate 10 min (4 °C water bath), centrifuge for 15 min at 12000 rpm, 4 °C. Transfer the supernatant (60 μL) into a fresh 2 mL LC/MS glass vial, take 10 μL from each sample and pooled as QC samples, Take 60 μL supernatant for the UHPLC-QTOF-MS analysis.
LC-MS/MS analysis
LC-MS/MS analyses were performed using an UHPLC system (1290, Agilent Technologies) with a UPLC BEH Amide column (1.7 μm, 2.1*100 mm, Waters) coupled to TripleTOF 6600 (Q-TOF, AB Sciex). The mobile phase consisting of 25 mM NH4OAc and 25 mM NH4OH in water (pH = 9.75) (A) and acetonitrile (B) was carried out with elution gradient as follows: 0 min, 95% B; 7 min, 65% B; 9 min, 40% B; 9.1 min, 95% B; 12 min, 95% B, which was delivered at 0.5 mL min−1. The injection volume was 2 μL. The Triple TOF mass spectrometer was used for its ability to acquire MS/MS spectra on an information-dependent basis (IDA) during an LC/MS experiment. In this mode, the acquisition software (Analyst TF 1.7, AB Sciex) continuously evaluates the full scan survey MS data as it collects and triggers the acquisition of MS/MS spectra depending on the preselected criteria. In each cycle, 12 precursor ions whose intensity greater than 100 were chosen for fragmentation at a collision energy (CE) of 30 V (15 MS/MS events with a product ion accumulation time of 50 msec each). ESI source conditions were set as following: Ion source gas 1 as 60 Psi, Ion source gas 2 as 60 Psi, Curtain gas as 35 Psi, source temperature 650°C, Ion Spray Voltage Floating (ISVF) 5000 V or 4000 V in positive or negative modes, respectively.
Data preprocessing and annotation
MS raw data (.d) files were converted to the mzXML format using ProteoWizard and processed by R package XCMS (version 3.2). The preprocessing results generated a data matrix that consisted of the retention time (RT), mass to charge ratio (m/z) values, and peak intensity. R package CAMERA was used for peak annotation after XCMS data processing80,81. In-house MS2 database was applied in metabolite identification.
Statistical and reproducibility
The data of virulence factor production, transcriptional analysis, and growth curve test were analysed by one-way ANOVA. Student’s t test was used when one-way ANOVA showed significant differences (P < 0.05). All statistical analyses were performed with GraphPad Prism statistical software (GraphPad Software, La Jolla, USA) with the assistance of Excel (Microsoft).
Reporting summary
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.
Data availability
The data that support the findings of the current study are available online or upon reasonable request. The RNA-seq datasets have been deposited in National Center for Biotechnology Information (NCBI) with an accession number GSE156842. The source data underlying the graphs and charts in the figures are uploaded as Supplementary Data. The values underlying Figs. 1A-C, 2A-D, 3A, 4C, 5A-D, and Supplementary Fig. 1A-E can be found in Supplementary Data.
References
Stover, C. K. et al. Complete genome sequence of Pseudomonas aeruginosa PAO1, an opportunistic pathogen. Nature 406, 959–964 (2000).
Lyczak, J. B., Cannon, C. L. & Pier, G. B. Lung infections associated with cystic fibrosis. Clin. Microbiol. Rev. 15, 194–222 (2002).
Lyczak, J. B., Cannon, C. L. & Pier, G. B. Establishment of Pseudomonas aeruginosa infection: lessons from a versatile opportunist. Microbes Infect./Inst. Pasteur 2, 1051–1060 (2000).
Harrison, F. Microbial ecology of the cystic fibrosis lung. Microbiology 153, 917–923 (2007).
Britigan, B. E., Railsback, M. A. & Cox, C. D. The Pseudomonas aeruginosa secretory product pyocyanin inactivates alpha1 protease inhibitor: implications for the pathogenesis of cystic fibrosis lung disease. Infect. Immun. 67, 1207–1212 (1999).
Cornelis, P., Matthijs, S. & Van Oeffelen, L. Iron uptake regulation in Pseudomonas aeruginosa. Biometals 22, 15–22 (2009).
Galloway, D. R. Pseudomonas aeruginosa elastase and elastolysis revisited: recent developments. Mol. Microbiol. 5, 2315–2321 (1991).
Venturi, V. Regulation of quorum sensing in. Pseudomonas. FEMS Microbiol. Rev. 30, 274–291 (2006).
Camilli, A. & Bassler, B. L. Bacterial small-molecule signaling pathways. Science 311, 1113–1116 (2006).
Lumjiaktase, P. et al. Quorum sensing regulates dpsA and the oxidative stress response in Burkholderia pseudomallei. Microbiology 152, 3651–3659 (2006).
Hassett, D. J. et al. Quorum sensing in Pseudomonas aeruginosa controls expression of catalase and superoxide dismutase genes and mediates biofilm susceptibility to hydrogen peroxide. Mol. Microbiol. 34, 1082–1093 (1999).
Storz, G. & Imlay, J. A. Oxidative stress. Curr. Opin. Microbiol. 2, 188–194 (1999).
Imlay, J. A. Pathways of oxidative damage. Annu. Rev. Microbiol. 57, 395–418 (2003).
Pierre, J. L. & Fontecave, M. Iron and activated oxygen species in biology: the basic chemistry. Biometals 12, 195–199 (1999).
Hassett, D. J., Charniga, L., Bean, K., Ohman, D. E. & Cohen, M. S. Response of Pseudomonas aeruginosa to pyocyanin: mechanisms of resistance, antioxidant defenses, and demonstration of a manganese-cofactored superoxide dismutase. Infect. Immun. 60, 328–336 (1992).
Cabiscol, E., Tamarit, J. & Ros, J. Oxidative stress in bacteria and protein damage by reactive oxygen species. Int Microbiol. 3, 3–8 (2000).
Storz, G., Tartaglia, L. A. & Ames, B. N. Transcriptional regulator of oxidative stress-inducible genes: direct activation by oxidation. Science 248, 189–194 (1990).
Zhang, A., Wassarman, K. M., Ortega, J., Steven, A. C. & Storz, G. The Sm-like Hfq protein increases OxyS RNA interaction with target mRNAs. Mol. cell 9, 11–22 (2002).
Zheng, M., Aslund, F. & Storz, G. Activation of the OxyR transcription factor by reversible disulfide bond formation. Science 279, 1718–1721 (1998).
Zheng, M., Doan, B., Schneider, T. D. & Storz, G. OxyR and SoxRS regulation of fur. J. Bacteriol. 181, 4639–4643 (1999).
Lee, C. et al. Redox regulation of OxyR requires specific disulfide bond formation involving a rapid kinetic reaction path. Nat. Struct. Mol. Biol. 11, 1179–1185 (2004).
Zheng, M. et al. DNA microarray-mediated transcriptional profiling of the Escherichia coli response to hydrogen peroxide. J. Bacteriol. 183, 4562–4570 (2001).
Altuvia, S., Weinstein-Fischer, D., Zhang, A., Postow, L. & Storz, G. A small, stable RNA induced by oxidative stress: role as a pleiotropic regulator and antimutator. Cell 90, 43–53 (1997).
Ochsner, U. A., Vasil, M. L., Alsabbagh, E., Parvatiyar, K. & Hassett, D. J. Role of the Pseudomonas aeruginosa oxyR-recG operon in oxidative stress defense and DNA repair: OxyR-dependent regulation of katB-ankB, ahpB, and ahpC-ahpF. J. Bacteriol. 182, 4533–4544 (2000).
Lau, G. W., Britigan, B. E. & Hassett, D. J. Pseudomonas aeruginosa OxyR is required for full virulence in rodent and insect models of infection and for resistance to human neutrophils. Infect. Immun. 73, 2550–2553 (2005).
Vinckx, T., Matthijs, S. & Cornelis, P. Loss of the oxidative stress regulator OxyR in Pseudomonas aeruginosa PAO1 impairs growth under iron-limited conditions. FEMS Microbiol. Lett. 288, 258–265 (2008).
Melstrom, K. A. Jr. et al. Cytotoxicity of Pseudomonas secreted exotoxins requires OxyR expression. J. Surg. Res. 143, 50–57 (2007).
Vinckx, T., Wei, Q., Matthijs, S. & Cornelis, P. The Pseudomonas aeruginosa oxidative stress regulator OxyR influences production of pyocyanin and rhamnolipids: protective role of pyocyanin. Microbiology 156, 678–686 (2010).
Hersch, S. J., Manera, K. & Dong, T. G. Defending against the Type Six Secretion System: beyond Immunity Genes. Cell Rep. 33, 108259 (2020).
Wei, Q. et al. Global regulation of gene expression by OxyR in an important human opportunistic pathogen. Nucleic Acids Res. 40, 4320–4333 (2012).
Palma, M., DeLuca, D., Worgall, S. & Quadri, L. E. Transcriptome analysis of the response of Pseudomonas aeruginosa to hydrogen peroxide. J. Bacteriol. 186, 248–252 (2004).
Chang, W., Small, D. A., Toghrol, F. & Bentley, W. E. Microarray analysis of Pseudomonas aeruginosa reveals induction of pyocin genes in response to hydrogen peroxide. BMC Genom. 6, 115 (2005).
Rojas Murcia, N. et al. The Pseudomonas aeruginosa antimetabolite L -2-amino-4-methoxy-trans-3-butenoic acid (AMB) is made from glutamate and two alanine residues via a thiotemplate-linked tripeptide precursor. Front. Microbiol. 6, 170 (2015).
Hentzer, M. et al. Attenuation of Pseudomonas aeruginosa virulence by quorum sensing inhibitors. EMBO J. 22, 3803–3815 (2003).
Schuster, M., Lostroh, C. P., Ogi, T. & Greenberg, E. P. Identification, timing, and signal specificity of Pseudomonas aeruginosa quorum-controlled genes: a transcriptome analysis. J. Bacteriol. 185, 2066–2079 (2003).
Lesic, B., Starkey, M., He, J., Hazan, R. & Rahme, L. G. Quorum sensing differentially regulates Pseudomonas aeruginosa type VI secretion locus I and homologous loci II and III, which are required for pathogenesis. Microbiology 155, 2845–2855 (2009).
Sana, T. G. et al. The second type VI secretion system of Pseudomonas aeruginosa strain PAO1 is regulated by quorum sensing and Fur and modulates internalization in epithelial cells. J. Biol. Chem. 287, 27095–27105 (2012).
Schertzer, J. W., Brown, S. A. & Whiteley, M. Oxygen levels rapidly modulate Pseudomonas aeruginosa social behaviours via substrate limitation of PqsH. Mol. Microbiol. 77, 1527–1538 (2010).
Haussler, S. & Becker, T. The Pseudomonas quinolone signal (PQS) balances life and death in Pseudomonas aeruginosa populations. PLoS Pathog. 4, e1000166 (2008).
Bredenbruch, F., Geffers, R., Nimtz, M., Buer, J. & Haussler, S. The Pseudomonas aeruginosa quinolone signal (PQS) has an iron-chelating activity. Environ. Microbiol. 8, 1318–1329 (2006).
Diggle, S. P. et al. The Pseudomonas aeruginosa 4-quinolone signal molecules HHQ and PQS play multifunctional roles in quorum sensing and iron entrapment. Chem. Biol. 14, 87–96 (2007).
Hoffman, L. R. et al. Selection for Staphylococcus aureus small-colony variants due to growth in the presence of Pseudomonas aeruginosa. Proc. Natl. Acad. Sci. USA 103, 19890–19895 (2006).
Foti, J. J., Devadoss, B., Winkler, J. A., Collins, J. J. & Walker, G. C. Oxidation of the guanine nucleotide pool underlies cell death by bactericidal antibiotics. Science 336, 315–319 (2012).
Kohanski, M. A., Dwyer, D. J., Hayete, B., Lawrence, C. A. & Collins, J. J. A common mechanism of cellular death induced by bactericidal antibiotics. Cell 130, 797–810 (2007).
Brynildsen, M. P., Winkler, J. A., Spina, C. S., MacDonald, I. C. & Collins, J. J. Potentiating antibacterial activity by predictably enhancing endogenous microbial ROS production. Nat. Biotechnol. 31, 160–165 (2013).
Mulani, M. S., Kamble, E. E., Kumkar, S. N., Tawre, M. S. & Pardesi, K. R. Emerging strategies to combat ESKAPE pathogens in the era of antimicrobial resistance: a review. Front. Microbiol. 10, 539 (2019).
Zheng, M. et al. Computation-directed identification of OxyR DNA binding sites in Escherichia coli. J. Bacteriol. 183, 4571–4579 (2001).
Pedre, B. et al. Structural snapshots of OxyR reveal the peroxidatic mechanism of H2O2 sensing. Proc. Natl. Acad. Sci. USA 115, E11623–E11632 (2018).
Jo, I. et al. The hydrogen peroxide hypersensitivity of OxyR2 in Vibrio vulnificus depends on conformational constraints. J. Biol. Chem. 292, 7223–7232 (2017).
Jo, I. et al. Structural details of the OxyR peroxide-sensing mechanism. Proc. Natl. Acad. Sci. USA 112, 6443–6448 (2015).
Alatraktchi, F. A., Svendsen, W. E. & Molin, S. Electrochemical detection of pyocyanin as a biomarker for Pseudomonas aeruginosa: a focused review. Sensors 20. https://doi.org/10.3390/s20185218 (2020).
Salunkhe, P., Topfer, T., Buer, J. & Tummler, B. Genome-wide transcriptional profiling of the steady-state response of Pseudomonas aeruginosa to hydrogen peroxide. J. Bacteriol. 187, 2565–2572 (2005).
Juttukonda, L. J. et al. Acinetobacter baumannii OxyR regulates the transcriptional response to hydrogen peroxide. Infect. Immun. 87, https://doi.org/10.1128/IAI.00413-18 (2019).
Janssen-Heininger, Y. M. et al. Redox-based regulation of signal transduction: principles, pitfalls, and promises. Free Radic. Biol. Med. 45, 1–17 (2008).
Corcoran, A. & Cotter, T. G. Redox regulation of protein kinases. FEBS J. 280, 1944–1965 (2013).
Ezraty, B., Gennaris, A., Barras, F. & Collet, J. F. Oxidative stress, protein damage and repair in bacteria. Nat. Rev. 15, 385–396 (2017).
Zhang, L., Alfano, J. R. & Becker, D. F. Proline metabolism increases katG expression and oxidative stress resistance in Escherichia coli. J. Bacteriol. 197, 431–440 (2015).
Tala, A. et al. Glutamate utilization promotes meningococcal survival in vivo through avoidance of the neutrophil oxidative burst. Mol. Microbiol. 81, 1330–1342 (2011).
Lopatkin, A. J. et al. Clinically relevant mutations in core metabolic genes confer antibiotic resistance. Science 371, https://doi.org/10.1126/science.aba0862 (2021).
Keren, I., Wu, Y., Inocencio, J., Mulcahy, L. R. & Lewis, K. Killing by bactericidal antibiotics does not depend on reactive oxygen species. Science 339, 1213–1216 (2013).
Liu, Y. & Imlay, J. A. Cell death from antibiotics without the involvement of reactive oxygen species. Science 339, 1210–1213 (2013).
Van Acker, H. & Coenye, T. The role of reactive oxygen species in antibiotic-mediated killing of bacteria. Trends Microbiol. 25, 456–466 (2017).
Deguchi, Y., Yamato, I. & Anraku, Y. Nucleotide sequence of gltS, the Na + /glutamate symport carrier gene of Escherichia coli B. J. Biol. Chem. 265, 21704–21708 (1990).
Lewenza, S., Gardy, J. L., Brinkman, F. S. & Hancock, R. E. Genome-wide identification of Pseudomonas aeruginosa exported proteins using a consensus computational strategy combined with a laboratory-based PhoA fusion screen. Genome Res. 15, 321–329 (2005).
Johnson, D. A. et al. High-throughput phenotypic characterization of Pseudomonas aeruginosa membrane transport genes. PLoS Genet. 4, e1000211 (2008).
Tarighi, S. et al. The PA4204 gene encodes a periplasmic gluconolactonase (PpgL) which is important for fitness of Pseudomonas aeruginosa. Microbiology 154, 2979–2990 (2008).
Bhasme, P. et al. Evaluation and characterization of the predicted diguanylate cyclase-encoding genes in Pseudomonas aeruginosa. Microbiologyopen 9, e975 (2020).
Wei, Q. et al. Diguanylate cyclases and phosphodiesterases required for basal-level c-di-GMP in Pseudomonas aeruginosa as revealed by systematic phylogenetic and transcriptomic analyses. Appl. Environ. Microbiol. 85 https://doi.org/10.1128/AEM.01194-19 (2019).
Yang, W. et al. Traditional Chinese medicine Tanreqing inhibits quorum sensing systems in Pseudomonas aeruginosa. Front. Microbiol. 11, 517462 (2020).
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
McClure, R. et al. Computational analysis of bacterial RNA-Seq data. Nucleic Acids Res. 41, e140 (2013).
Tjaden, B. De novo assembly of bacterial transcriptomes from RNA-seq data. Genome Biol. 16, 1 (2015).
Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).
Klopfenstein, D. V. et al. GOATOOLS: a Python library for gene ontology analyses. Sci. Rep. 8, 10872 (2018).
Xie, C. et al. KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res. 39, W316–W322 (2011).
Cornelis, P. et al. Cloning and analysis of the gene for the major outer membrane lipoprotein from Pseudomonas aeruginosa. Mol. Microbiol. 3, 421–428 (1989).
Schmittgen, T. D. & Livak, K. J. Analyzing real-time PCR data by the comparative C(T) method. Nat. Protoc. 3, 1101–1108 (2008).
Xu, X. et al. Early diagnosis of the Need for surgical drainage in chronic pancreatitis patients based on serum metabolomics. Clin. Chim. Acta 576, 120369 (2025).
Dunn, W. B. et al. Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry. Nat. Protoc. 6, 1060–1083 (2011).
Kuhl, C., Tautenhahn, R., Bottcher, C., Larson, T. R. & Neumann, S. CAMERA: an integrated strategy for compound spectra extraction and annotation of liquid chromatography/mass spectrometry data sets. Anal. Chem. 84, 283–289 (2012).
Smith, C. A., Want, E. J., O’Maille, G., Abagyan, R. & Siuzdak, G. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal. Chem. 78, 779–787 (2006).
Winsor, G. L. et al. Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database. Nucleic Acids Res. 44, D646–D653 (2016).
Acknowledgements
This work was supported by The Fundamental Research Funds for the Central Public Welfare Research Institutes (N0.JJPY2022014), Training Object of the Second Medical Leading Talent Project in Hubei Province, the Hubei Famous Doctor Studio Project of the Health Commission of Hubei Province (e.w.t. [2019] No. 47), the Scientific and Technological Innovation Project of China Academy of Chinese Medical Sciences [CI2021B003], and the Fundamental Research Funds for the Central Public Welfare Research Institutes of China [Z0735].
Author information
Authors and Affiliations
Contributions
Conceptualization: P.W., Q.W., D.W., and W.Y., Methodology: K.C., Z.F., R.S., Q.Y., and F.W., Formal analysis: K.C., Z.F., and X.S., Investigation: K.C. R.S., Q.Y., Y.T., and Y.X., Resources: P.W. and D.W., Data curation: F.W., X.S., Writing original draft: K.C. and Z.F., Writing review & editing: P.W., Q.W. and W.Y., Visualization: Y.T. and Y.X., Supervision: P.W., Q.W., D.W., and W.Y., Project administration: D.W., Funding acquisition: P.W. and W.Y.
Corresponding authors
Ethics declarations
Competing interests
Qing Wei, Weifeng Yang and Kaiyu Cui are joint inventors of a patent filed with the China National Intellectual Property Administration (No.202511090940.9), covering the application of OxyR regulon as antibacterial targets.
Peer review
Peer review information
Communications Biology thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editors: Ranjana Pathania and Tobias Goris. A peer review file is available.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Cui, K., Fu, Z., Sun, R. et al. Systems-level exploitation of OxyR regulon unravels a potential antibacterial target in Pseudomonas aeruginosa. Commun Biol 8, 1370 (2025). https://doi.org/10.1038/s42003-025-08770-w
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s42003-025-08770-w
