Isolating the Escherichia coli Transcriptomic Response to Superoxide

Letter Cite This: ACS Biomater. Sci. Eng. XXXX, XXX, XXX−XXX

pubs.acs.org/journal/abseba

Isolating the Escherichia coli Transcriptomic Response to Superoxide Generation from Cadmium Chalcogenide Quantum Dots Thomas R. Aunins,† Kristen A. Eller,† Colleen M. Courtney,† Max Levy,†,‡ Samuel M. Goodman,†,‡ Prashant Nagpal,†,‡,∥ and Anushree Chatterjee*,†,§ †

Department of Chemical and Biological Engineering, ‡Renewable and Sustainable Energy Institute, §BioFrontiers Institute, and Materials Science and Engineering, University of Colorado Boulder, Boulder 80303, Colorado, United States

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S Supporting Information *

ABSTRACT: Nanomaterials have been extensively used in the biomedical field and have recently garnered attention as potential antimicrobial agents. Cadmium telluride quantum dots (QDs) with a bandgap of 2.4 eV (CdTe-2.4) were previously shown to inhibit multidrug-resistant clinical isolates of bacterial pathogens via light-activated superoxide generation. Here we investigate the transcriptomic response of Escherichia coli to phototherapeutic CdTe-2.4 QDs both with and without illumination, as well as in comparison with the non-superoxide-generating cadmium selenide QDs (CdSe-2.4) as a negative control. Our analysis sought to separate the transcriptomic response of E. coli to the generation of superoxide by the CdTe-2.4 QDs from the presence of cadmium chalcogenide nanoparticles alone. We used comparisons between illuminated CdTe-2.4 conditions and all others to establish the superoxide generation response and used comparisons between all QD conditions and the no treatment condition to establish the cadmium chalcogenide QD response. In our analysis of the gene expression experiments, we found eight genes to be consistently differentially expressed as a response to superoxide generation, and these genes demonstrate a consistent association with the DNA damage response and deactivation of iron−sulfur clusters. Each of these responses is characteristic of a bacterial superoxide response. We found 18 genes associated with the presence of cadmium chalcogenide QDs but not the generation of superoxide by CdTe-2.4, including several that implicated metabolism of amino acids in the E. coli response. To explore each of these gene sets further, we performed both gene knockout and amino acid supplementation experiments. We identified the importance of leucyl-tRNA downregulation as a cadmium chalcogenide QD response and reinforced the relationship between CdTe-2.4 stress and iron−sulfur clusters through examination of the gene tusA. This study demonstrates the transcriptomic response of E. coli to CdTe-2.4 and CdSe-2.4 QDs and parses the different effects of superoxide versus material effects on the bacteria. Our findings may provide useful information toward the development of QD-based antibacterial therapy in the future. KEYWORDS: Escherichia coli, quantum dots, RNA-sequencing, oxidative stress, antibiotics, transcriptome, reactive oxygen species

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INTRODUCTION

One possible solution is the use of light-activated quantum dots (QDs), semiconductor nanoparticles with tunable reduction and oxidation potentials due to size, shape, and material-based quantum confinement. When excited across their bandgap, QDs produce photoexcited electrons and holes that interact with molecules in biological environments. Previous research into the effects of cadmium chalcogenide QDs has hypothesized responses tied to oxidative stress, cadmium release, and membrane damage, and it has demonstrated the ability of QDs to inhibit growth.6−10

The rapid development of multidrug resistance and a dwindling pipeline of new small-molecule antimicrobial treatments will precipitate a global healthcare crisis in coming decades.1 Addressing this issue will require the development of new classes of rationally designed antibiotics. Nanoparticles made of silver, silica, zinc oxide, and titanium dioxide, among other materials, have shown antibacterial activity through photothermal therapy, production of nonspecific reactive oxygen species, electrostatic interactions, and cell wall disruption.2−5 While these mechanisms make them viable candidates for new antimicrobial therapies, the nonspecificity also makes them potentially lethal to nearby host cells. © XXXX American Chemical Society

Received: July 18, 2019 Accepted: August 2, 2019 Published: August 2, 2019 A

DOI: 10.1021/acsbiomaterials.9b01087 ACS Biomater. Sci. Eng. XXXX, XXX, XXX−XXX

Letter

ACS Biomaterials Science & Engineering

Figure 1. Characterization of cadmium quantum dot nanoparticles. (A) Cadmium telluride and cadmium selenide QDs were synthesized with the same 2.4 eV bandgap but different reduction potentials, such that the CdTe-2.4 QDs will produce superoxide upon light activation, whereas the CdSe-2.4 QDs will not. (B) Electron paramagnetic resonance spectroscopy and cyclic voltammetry were performed on each QD in both light and dark conditions, demonstrating the generation of ROS by CdTe-2.4 in light. Cyclic voltammetry is shown for CdTe-2.4 QD solutions both before and after argon bubbling. (C) Growth curves of E. coli MG1655 treated with varying QD concentrations of both types, in light. Significant growth inhibition is observed in all CdTe-2.4 conditions. The data shown are an average of at least three biological replicates, and error bars represent standard deviation between biological replicates. (D) For the transcriptomic experiments, the QD treatments were applied to E. coli MG1655 cultures for a 5 h period before RNA extraction and RNA-seq analysis. Five treatments were conducted in duplicate: CdTe-2.4 Light, CdTe-2.4 Dark, CdSe-2.4 Light, CdSe-2.4 Dark, and no treatment in light.

by CdTe QDs and the non-photoactived effects of cadmiumbased QDs in a bacterial culture. We have previously synthesized light-activated cadmium telluride QDs with a 2.4 eV bandgap (Figure 1A) and demonstrated that their reduction potential could be specifically tuned to inhibit growth in multidrug-resistant (MDR) bacteria via light-activated superoxide generation.19,20 In this study, we seek to explore and isolate the different transcriptomic effects of the superoxide-producing CdTe-2.4 QDs on E. coli at QD concentrations that are at the upper limit of the nonlethal range. We accomplish this by using RNAseq21 to monitor bacterial gene expression, with the nonsuperoxide-producing CdSe-2.4 QDs as a control to isolate the superoxide effect from the cadmium chalcogenide QD effect.

However, few studies have explored the transcriptomic response of Escherichia coli to QDs that produce specific reactive oxygen species (ROS) such as superoxide or even the transcriptomic response to other exogenous ROS producers. In one such study, two sizes of glutathione-capped CdTe QDs at high concentrations were found to modulate transcription in genes associated with possible cadmium poisoning, membrane damage, and oxidative stress.11 However, it is unclear which of these effects might result from each of the distinct properties of the QDsband gap, reduction potential, material, etc.as well as which effects may result from experimental design. Two stressors that have been hypothesized in previous QD studies, cadmium toxicity and the presence of nonspecific ROS in bacteria, have been the subject of more transcriptomic research than QDs themselves. In studies that have examined the transcriptomic response of E. coli and other bacteria to peroxide and superoxide ROS, oxidative stress regulators such as SoxR and OxyR have, as expected, been activated.12−16 These ROS studies also noted the induction of pathways associated with iron metabolism, redox processes, transport, and the regeneration of cellular reducing agents such as NADPH and NADH. Other research has found that introducing exogenous cadmium salts to E. coli modulated genes involved with an increased DNA damage response, decreased protein synthesis, a shift toward anaerobic metabolism, and a broad range of other bacterial stress response pathways, including oxidative stress.17,18 While this research does help to inform the expected transcriptomic response of E. coli in our experiments, no prior research has distinguished between the effects of specific ROS production

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RESULTS Characterization of CdTe-2.4 and CdSe-2.4 QDs. In previous work from our lab, we found that the CdTe-2.4 and CdSe-2.4 do not show significant size differences, with mean diameters of 3.0 ± 0.5 and 2.7 ± 0.4 nm, respectively.19 The redox activity of CdTe-2.4 relative to CdSe-2.4 is observed in both its production of superoxide and its toxicity in E. coli. Electron paramagnetic resonance (EPR) spectroscopy with spin trapping was used to measure ROS production22 by CdTe-2.4 and CdSe-2.4 (Figure 1B). Hydroxyl radical signal from CdTe-2.4 predominates in the light condition, which is due to dismutation of superoxide radical adducts in solution as has been demonstrated in our prior studies through use of superoxide dismutase and ascorbic acid as superoxide scavengers23while negligible signal is observed from CdSeB


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Figure 2. Expression profiles of genes differentially expressed in the superoxide and/or cadmium chalcogenide QD response. (A) Differentially expressed genes that fulfill each of the established criteria for cadmium chalcogenide QD response or superoxide response, categorized according to biological function. (B) The eight genes identified as differentially expressed in more than two conditions compared to CdTe-2.4 in light (without fulfilling the cadmium chalcogenide QD criterion). (C) The 18 genes identified as differentially expressed in more than two QD conditions compared to no treatment (without fulfilling the superoxide criterion). (D) The six genes that fulfill both criteria noted in (A, B).

2.4. We confirmed this effect using cyclic voltammetry. The appearance of superoxide and hydroxyl radical peaks in the cyclic voltammetry (at −0.2 and 1 V, respectively) prior to argon bubbling, and their subsequent disappearance after argon bubbling, indicates that CdTe-2.4 redox activity is invariably linked to the presence of oxygen (Figure 1B). The toxicity of CdTe-2.4 and CdSe-2.4 in light was evaluated in E. coli MG1655 at concentrations ranging from 10 to 50 nM, to establish the difference in growth inhibition between the two QDs. Prior work has established the nontoxicity of CdTe-2.4 in the dark at such concentrations.19,23 This experiment was also used to select a sublethal CdTe-2.4 concentration for the subsequent RNA-seq experiments. The growth curves demonstrate the growth inhibition in E. coli grown in the presence of CdTe-2.4 at all concentrations, though the inhibitory effect is found to be nonlethal at a concentration of 10 nM (Figure 1C). The CdSe2.4 treatments, as well as the no treatment condition, do not show growth inhibiton, corresponding to the demonstrated lack of redox activity. These CdTe-2.4 treatment data agree

with previous results that show a minimum inhibitory concentration (MIC) of 35 nM for illuminated CdTe-2.4 treatments.19 Our results for QD ROS generation and bacterial growth assays reiterate the difference between CdTe-2.4 QDs and the control CdSe-2.4 QDs, both in their effects on cellular growth and superoxide production. Transcriptomic Analysis. Cultures of E. coli MG1655 grown in M9 minimal salts media (0.4% glucose) were exposed to 10 nM treatments of CdTe-2.4 and CdSe-2.4 for a period of 5 h, with and without light, as well as to a no treatment control condition (Figure 1D). This concentration was chosen because it has demonstrated minor growth inhibition during the bacterial exponential phase, before recovering over the remainder of the 24 h experiment (Figure 1C). This effect has been noted in previous publications regarding CdTe-2.4 and superoxide toxicity, and it may be the result of the cell’s endogenous response temporarily mitigating the toxicity, though it has not been studied in depth. In prior publications, we have shown that a 5 nM treatment of E. coli strain MG1655 does not exhibit this same growth inhibition.19 Our study C


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(Figure 2A,C, Supporting Information Table S1), five are related to transport: bioP (biotin transport), afuC (sugar phosphate transport), lgoT (L-galactonate uptake), clcB (chloride/proton antiporter), and tqsA (autoinducer-2 exporter). The genes bioP, afuC, and tqsA show upregulation in QD conditions relative to no treatment, while lgoT and clcB show downregulation. Both of these downregulated genes are involved in proton-related transport; lgoT uses protons to drive L-galactonate uptake,30 and clcB likely uses chloride ions to remove protons from the cell as a means of acid resistance.31 Three of the 18 genes are related to metabolic processes: panM (pantothenate biosynthesis), gor (glutathione reductase), and tesB (acyl-CoA thioesterase). The genes panM and tesB are both upregulated with respect to no treatment, while gor is downregulated. Both upregulated genes are related to CoA metabolism.32,33 Another three of the genes are involved in regulation of transcription or translation: gadW (acid response), gcvB (regulatory RNA, implicated in amino acid availability), and rimO (ribosomal protein methylthiolation). The genes gadW and rimO are upregulated with respect to no treatment, while gcvB is downregulated. Two more of the 18 genes are related to cell wall processes, and are both downregulated with respect to no treatment: elyC (envelope biogenesis) and emtA (peptidoglycan degradation). The remaining genes are individually involved in RNA processing (rne, downregulated), stress response (ygaM, downregulated), and tRNA synthesis (leuQ, downregulated), in addition to two genes of unknown function (insD1 and ybdM). It may be notable that four of the 18 genes (clcB, gadW, gcvB, and rne) are known to be related to the acid shock response.31,34−37 Overlapping Response. Of the six genes that satisfied both criteria, three are involved in tRNA synthesis (tusA, leuV, and leuP), two are involved with metabolic processes (yeiG and ynjF), and one is of unknown function (yjaH) (Figure 2A,D, Supporting Information Table S3). The gene yeiG, a serine hydrolase that is implicated in methylglyoxal detoxification, is downregulated in three conditions with respect to no treatment and shows downregulation in CdTe-2.4 light with respect to CdSe-2.4 dark. The gene ynjH, which may be involved in phospholipid biosynthesis, shows significant downregulation in both CdSe-2.4 conditions relative to no treatment as well as to CdTe-2.4 light. The tRNA-related genes have opposite regulation patterns between tusA to the two leucyl-tRNAs. The gene tusA, a sulfur mediator in thiouridine synthesis, shows upregulation from no treatment in all conditions, whereas each leucyl-tRNA shows consistent downregulation from no treatment. In addition to the two leucyl-tRNAs from this response set, the third tRNA within the same operon, leuQ, was also found to be downregulated with respect to the no treatment condition (Figure 2A). Regulatory Networks Controlling E. coli Response. Analysis of the regulatory networks of genes identified in the cadmium chalcogenide QD and superoxide response reveals five common regulators (Figure 3). In our analysis we examined regulator genes that control two or more genes in any of the response categories, as well as the common regulators further upstream in the regulatory pathways. The regulator we observe with the most genes under its control is rpoD, the dominant sigma factor in the cell during exponential growth phase, which is the phase in which RNA was extracted in our experiments. This gene is known to regulate more than 1600 genes in E. coli, explaining its prevalence in our analysis.38

required that cells remain alive for RNA extraction, while also being challenged to adapt their transcriptomic profile to the QD stressor. For this reason we believe use of 10 nM is appropriate, as at a lower concentration the effect on transcriptome is likely to be weaker and less clear. The exposure period of 5 h was chosen so that the cells were in log phase (OD 0.3−0.6), at the time point at which we observe the minor growth inhibition, when RNA collection took place (Figure 1C). Illumina HiSeq sequencing was performed on RNA extracted during exponential phase of growth, and the sequencing data were processed according to a standard RNA-seq analysis pipeline (see Methods). Differential expression was determined using the DESeq R package,24 using the Benjamini−Hochberg procedure to correct for multiple testing false positives, with a P-value threshold of 0.1. In our analysis we searched for genes whose differential expression profile could be attributed to QD superoxide production or the only the presence of cadmium chalcogenide QDs. The criterion for E. coli response to superoxide production was differential expression in at least two of the following comparisons: the CdTe-2.4 light condition versus either no treatment, CdTe-2.4 dark, CdSe-2.4 light, or CdSe2.4 dark. The criterion for E. coli response to cadmium chalcogenide QDs was differential expression in at least two of the following comparisons: the CdTe-2.4 light, CdTe-2.4 dark, CdSe-2.4 light, or CdSe-2.4 dark conditions versus no treatment. We find eight genes uniquely associated with the superoxide-producing condition, 18 genes uniquely associated with the presence of cadmium chalcogenide QDs, and six genes associated with both (Figure 2A, Supporting Information Tables S1−S3). Superoxide Response. In the set of eight genes uniquely associated with the CdTe-2.4 light condition (Figure 2A,B, Supporting Information Table S2), two genes are directly related to DNA damage (recD and atl), a known consequence of superoxide stress,25,26 and two are related to stress response (dsrA and ridA). DsrA is a small RNA that controls the general stress regulator RpoSthough we do not see differential expression of RpoS itselfand ridA is a redox-regulated protein known to respond to oxidative stress from hypochlorous acid.27,28 The remaining four genes are involved with biofilm formation (pdeC), metabolism (yhbX), transcription regulation (hupA), and transport (yhf K). All genes in the set of eight are upregulated in the CdTe-2.4 light condition relative to the other comparisons. The biofilm-related gene pdeC is the most upregulated of these genes, ranging from a fivefold to a greater than 10-fold increase, and is significantly differentially expressed in all four comparisons (Figure 2B). The genes hupA and yhf K show significant upregulation in three of the four comparisons, while the remaining five show significant upregulation in two comparisons each. Cadmium Chalcogenide QD Response. Differentially expressed genes that are unique to the cadmium chalcogenide QD conditions are expected to represent a response to nontoxic factors, as we have demonstrated in previous research that QD phototoxicity is based on superoxide production.20,23,29 This is supported by our QD growth experiments, in which we have demonstrated that non-photoactivated cadmium chalcogenide QDsin this case, our CdSe-2.4 controlsdo not inhibit bacterial growth at a concentration of 10 nM (Figure 1C). In the set of 18 genes uniquely associated with the presence of cadmium chalcogenide QDs D


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condition. These data agree with transcriptomic response that showed downregulation of the leucyl-tRNAs in the presence of cadmium chalcogenide QDs versus no treatment (Figure 2). As a basis of comparison for the leucine-supplemented E. coli, we also examined the CdTe-2.4-challenged growth response of the bacteria when supplemented with the aliphatic amino acids isoleucine, L-alanine, and D-alanine (Figure 4B). When combined with CdTe-2.4 QDs, neither isoleucine nor Dalanine show significant difference with their respective individual treatments (amino acid only and QD only). However, when E. coli is supplemented with L-alanine and CdTe-2.4 in the dark, a significant difference in end-point growth is observed between this combination and each of the individual treatments. This is similar to the difference in growth that was found when E. coli is supplemented with leucine and CdTe-2.4 in the light (noted above). Furthermore, in both cases these combinations show significant interaction between the amino acid and CdTe-2.4 treatments, as opposed to a simple additive effect (L-alanine and QD P-value = 0.001, leucine and QD P-value = 0.014). It was found that L-alanine improves E. coli fitness under CdTe-2.4 stress in the dark more than was expected, and leucine damages E. coli fitness under CdTe-2.4 stress in the light more than was expected, based on the Bliss Independence model for drug combinations (Figure 4C).46 Quantum Dot Interaction with Gene Knockouts. We examined the sets of genes that were found in our transcriptomic analysis to be upregulated in response to either superoxide or to the presence of cadmium chalcogenide QDs. We grew E. coli knockouts, both with and without CdTe-2.4 QDs in the light and dark, for 24 h, and evaluated the growth curves with respect to no treatment and CdTe-2.4 only controls. For the superoxide response set we used knockout strains for all but the gene dsrA, which is a nonviable knockout (Supporting Information Figure S1). For the cadmium chalcogenide QD response set we used knockout strains for the genes panM, gadW, af uC, and bioP (Supporting Information Figure S2). The genes panM, afuC, and bioP were selected because they were each upregulated in three conditions with respect to no treatment, and the gene gadW was selected because it was upregulated and related to stress response. Additionally, we used knockout strains for the gene tusA of the overlapping response set, as well as the previously identified regulator genes rpoS, f is, dksA, and crp (the rpoD knockout is nonviable) (Supporting Information Figure S3). As each of these genes was upregulated in our transcriptome analysis, their knockouts were expected to interact synergistically with CdTe-2.4that is, have a higher CdTe-2.4 susceptibility than the wild typeunder their respective light/dark response conditions. A two-way ANOVA test was used to evaluate whether the gene knockouts showed significant interaction (P < 0.05) with the presence of CdTe2.4 QDs, both in light and dark conditions, according to the respective end-point optical density measurements. Synergy svalues were calculated using the Bliss Independence model.46 Of these sets, two knockouts were shown to interact with CdTe-2.4 in the dark: gadW (transcriptional regulator, cadmium chalcogenide QD response) and tusA (tRNA synthesis, overlapping response). Six of the knockout strains were shown to interact with CdTe-2.4 in the light: pdeC (biofilm formation modulator, superoxide response), atl (DNA repair, superoxide response), gadW, afuC (transport, cadmium chalcogenide QD response), rpoS (stress response regulator),

Figure 3. Regulation patterns in superoxide and cadmium chalcogenide QD response. Arrows show gene regulation, moving from regulator gene to regulated gene. Level 0 consists of genes within the established superoxide and cadmium responses that share a regulator with another gene in those response groups. Levels 1 and 2 show those regulators and others upstream that are shared within the gene network.

We identify the genes rpoS and f is in our first upstream level of regulation, each of which has a comparatively smaller regulation profile: 339 and 233 genes, respectively.38 The former, noted above to be controlled by DsrA, is an alternative sigma factor responsible for a large amount of the general stress response in E. coli, including DNA damage.39,40 In our response set, it regulates the genes pdeC (biofilm formation modulator, superoxide response set), gor (glutathione reductase, cadmium chalcogenide QD response set), and gadW (transcriptional regulator, cadmium chalcogenide QD response set). The gene f is is responsible for organizing the nucleoid structure, as represented in our response by its control of hupA, as well as regulating genes in a wide range of other pathways.41,42 This includes the leucyl-tRNA operon (leuQ, leuV, and leuP) identified in our response analysis. Level 2 of Figure 3 shows the apex of the regulation network we identify in our transcriptomic analysis, and it contains the genes dksA and crp. DksA is an RNA polymerase-binding protein that regulates the transcription of rRNA promoters and has shown important regulatory interaction with RpoS for stress tolerance.43−45 The gene crp codes for the cAMP receptor protein that is involved in transcriptional regulation. Quantum Dot Interaction with Leucine Supplementation. We sought to further investigate the role of leucine based on the observed differential expression of three leucyltRNAs in our analysis. This analysis intended to separate the leucine-related transcriptomic response to cadmium chalcogenide QDs from the response to superoxide. We grew leucinesupplemented (0.65 mM) E. coli cultures in the presence of CdTe-2.4 QDs, both in light and dark conditions for 24 h (Figure 4A). We found a significant decrease in fitness of these cultures when leucine is added to QD treatments in the light E


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Figure 4. E. coli response to CdTe-2.4 treatment during amino acid supplementation. (A) E. coli growth curves under conditions of no treatment, 25 nM CdTe-2.4, 0.65 mM leucine supplementation, and leucine/CdTe-2.4 combination treatment. Each condition was conducted in both light and dark conditions. (B) End-point growth measurements (OD 590 nm) for leucine and three other aliphatic amino acids. Brackets between conditions indicate P < 0.01 (omitted in each no treatment vs CdTe-2.4 comparison for clarity). The data shown are an average of at least three biological replicates, and error bars represent standard deviation between biological replicates. (C) End-point growth measurements vs expectation for the two combination treatments that were found to have significant interaction: L-alanine and CdTe-2.4 dark, and leucine and CdTe-2.4 light.

and dksA (transcription factor). We observe significant synergistic interaction for the knockout strains of gadW (dark, s = 0.19, P = 0.03; and light, s = 0.29, P = 0.003) and tusA (dark, s = 0.28, P = 0.02) (Figure 5A,E). The former was a member of the cadmium chalcogenide QD response, and this result affirms its importance to the both photoactivated and nonactivated QD conditions. The gene tusA is a member of the overlapping responses, so it is unexpected that the light condition would not show interaction as well. In the remaining five treatments in which we observed significant interactionpdeC, atl, af uC, rpoS, and dksA knockouts in the CdTe-2.4 light conditionwe observed an antagonistic effect between growth inhibition caused by the knockout strain and growth inhibition caused by the QDs. In

one of the treatments, the afuC knockout in the CdTe-2.4 light condition (s = −0.02, P = 0.02), the dual treatment condition is significantly inhibited with respect both single treatments, but their combination inhibits less than expected. In the remaining four treatments, there is no significant difference between the combination treatment and one or both of the individual treatments. In these counterintuitive antagonistic responses, this effect may be the result of examining interaction at the end-point growth (24 h) as opposed to the point at which transcriptomics were performed (5 h), and these genes may be more transiently important as a response to the QD treatment. The antagonistic effect of the regulators, similarly, presents unclear conclusions, though these proteins may be F


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Figure 5. Gene knockouts that demonstrate significant interaction with QD-induced effects. (A, B) Growth curves for gene knockouts from the cadmium chalcogenide QD response that showed significant interaction with CdTe-2.4 based on end-point measurements. (C, D) Growth curves for gene knockouts from the superoxide response that showed significant interaction with CdTe-2.4 based on end-point measurements. (E) Growth curve for tusA knockout when challenged with CdTe-2.4 in the dark, which shows significant interaction based on end-point growth measurement. (F, G) Growth curves for gene knockouts from the response regulators that showed significant interaction with CdTe-2.4 based on end-point measurements. The s-value was calculated using the Bliss Independence model (see Methods). The data shown are an average of at least three biological replicates, and error bars represent standard deviation between biological replicates.

E. coli,52,53 and it has been implicated in a gene network associated with mutagenic DNA repair. 54 These four upregulated genes represent half of the CdTe-2.4 light response set, which reaffirms the conclusion that light activation of CdTe-2.4 results in superoxide-induced oxidative stress that is toxic to E. coli. Numerous studies have established the link between superoxide, as well as its resultant hydroxyl radicals, and DNA damage.13,25,26,55 Superoxide causes oxidative DNA damage by generating hydroxyl radicals in reactions with ferric iron,25 and it has been shown that these reactions result from superoxide interaction with enzymic iron−sulfur clusters.26,55−57 Our previous work corroborates this mechanism for CdTe-2.4-generated superoxide, as light activation of these QDs was found to deactivate enzymes containing labile iron−sulfur clusters.23 The identification of these genes support the hypothesis that the toxicity of CdTe2.4, which we demonstrated here and in previous studies to be exclusively light-activated (Figure 1C),19 is the result of superoxide-induced DNA damage.

subject to more complex interactions than are surveyed in this study.

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DISCUSSION

Superoxide Production Induces a DNA Damage Response. In the superoxide response set of genes, we observe the upregulation of two genes directly involved in DNA damage repair (atl and recD), and two more that have been implicated in the E. coli DNA damage response (hupA and pdeC). The protein RecD is a member of the Exonuclease V complex involved in homologous recombination for repairing DNA and during bacterial conjugation,47 whereas the protein Atl works by turning mismatched DNA bases to the outside of the helix, and it has thus been speculated to work in the repair of mismatches.48,49 The gene hupA codes for the histone-like protein HU is predicted to interact with and organize bacterial genetic material.50 In a wide survey of E. coli transcription, hupA was among a set of more than 1000 genes that is implicated in a broad DNA damage response.51 PdeC is a phosphodiesterase known to modulate biofilm formation in G


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leucyl-tRNAs of the same operon with respect to the no treatment condition. Though two of these genes also fulfill the superoxide response condition, the expression profile appears likely to be an exclusively cadmium chalcogenide QD response. In the leucine supplementation experiments that followed, we observed bacterial growth results that support the transcriptomic data, as the leucine supplementation and CdTe2.4 light treatments acted synergistically to reduce growth in the E. coli culture. We do not observe a significant interaction in the combination treatment for the dark condition, which shows that the effect of leucine on E. coli adaptation to CdTe2.4 is more pronounced in the presence of superoxide. Additional experiments with other aliphatic amino acids (isoleucine, D- and L-alanine) confirm that this effect is specific to leucine supplementation rather than general amino acid supplementation, as leucine is the only treatment to show significant synergistic interaction with the CdTe-2.4 treatment (Figure 4B). Prior research has shown that E. coli may downregulate the expression of tRNAs to slow the translation process as a part of a stress response, and this may prevent misfolding or protein aggregation, as well as reduce growth to conserve resources.68−70 In one of these studies, this downregulation was induced by leucine starvation stress, whereas in the other two, interestingly, it was the result of oxidative stressors. In one of these oxidative stress studies, leucyl-tRNAs specifically were found to be downregulated in response to oxidative stress, while other tRNAs were upregulated.70 This result matches closely with the observations of our transcriptomic and supplementation experiments. It was hypothesized to result from the fact that leucine is the most commonly used E. coli amino acid, which would cause protein translation rates to be inordinately dependent on the leucyl-tRNA, such that translation could be modulated by downregulating these tRNAs, in particular. In our leucine supplementation experiments, the influx of exogenous leucine may have resulted in faster translation rates and toxic effects as a result. From these experiments we also observe an inhibitionmitigating interaction between L-alanine and CdTe-2.4 in the dark (Figure 4C). We observed a significant interaction between the supplementation of L-alanine and CdTe-2.4 in the dark condition, though we did not see the same significant interaction with D-alanine supplementation. This may indicate that the interaction between L-alanine and the CdTe-2.4 QD is more involved with the tRNA-charging and protein synthesis function of the amino acid, as this is the main process that the 38 D-enantiomer does not share in the E. coli metabolism. Along with the results from the leucine supplementation treatment, this provides further evidence that the regulation of protein translation plays a key role in the E. coli response to CdTe-2.4 QDs. Together, our amino acid supplementation results indicate a role of tRNA regulation in the E. coli response to nontoxic features of the cadmium chalcogenide QDs, though it is still unclear whether this response is stimulated by cadmium release itself or by another factor. Role of Sulfur-Mediator TusA in the Cadmium-QD Response. We encounter substantial evidence for the influence of the gene tusA on the E. coli response to CdTe2.4 in both the transcriptomic response and the knockout interaction experiments. The gene tusA is upregulated in all comparisons of the cadmium chalcogenide QD treatments (CdTe-2.4 and CdSe-2.4 in light and dark) versus the no

Additionally, we observe two genes in stress response that are upregulated in the superoxide response set: ridA and dsrA. The protein RidA is a redox-regulated chaperone protein and is activated by hypochlorous acid stress, an oxidizing agent that has also been shown to both target iron−sulfur clusters and induce DNA damage.27,28,58−60 DsrA is a small regulatory RNA that activates general stress response via RpoS and can be bound by histone-like protein HU.61 DsrA has been found to be essential for a response to protein mistranslation in E. coli, which confers tolerance to H2O2 oxidative stress.62 DsrA is also found to influence biofilm formation when overexpressed,63,64 relating it to the biofilm matrix-modulating function of PdeC, which is itself dependent on RpoS.52,53,65 As a broad stress regulator, RpoS has also been associated with a response to DNA damage in E. coli.39,54 Together with the four genes that are directly implicated in the DNA damage response, these two stress response genes contribute to the evidence for DNA damage as a primary cause of superoxide-induced toxicity. Notably, we do not observe the differential expression from several important systems associated with oxidative stress: soxRS, sodABC, oxyRS, and marRAB. Our past research on CdTe-2.4 QDs implicated the gene sodB, in particular, as an important element to the E. coli superoxide response, in addition to identifying the importance iron−sulfur clusters, a key facet of the soxRS system.23,66 One explanation for the soxRS system not being upregulated is past findings that it can remain inactivated even in the presence of superoxide.67 It is also possible that this is a result of the QD treatment concentration (10 nM) used in our transcriptomics experiments, which may be at a level where basal levels of these established superoxide response genes can handle the influx of stressors. This is supported by the low level of growth inhibition we observed with 10 nM CdTe-2.4 (Figure 1C). It may also be a result of the exposure time, 5 h, which contrasts with shorter exposures and more rapid transcriptomic response analyses in previous oxidative stress studies.12−16 This introduces the possibility that the stress and DNA damagerelated genes identified above may be activated as part of a particularly sensitive or persistent superoxide response. Acid Shock-Related Genes in the Cadmium Chalcogenide QD Response. Several genes of the QD response set show a relationship with acid shock response: gadW, clcB, rne, and gcvB. Deletion or mutation of each of these four genes shows a higher susceptibility to acid shock conditions in E. coli.31,34−37 However, conflicting regulation patterns are observed, as gadW is upregulated in cadmium chalcogenide QD conditions, while the other three genes are downregulated. We also find significant synergistic interaction between the ΔgadW knockout and the QD treatment in both light and dark conditions. The degree of its interaction with CdTe-2.4 suggests that the introduction of these QDs may play a role in the acidification of the intracellular environment (Figure 5A), as a significant detrimental effect of gadW deletion is observed. However, while the gadW gene is known to control system of glutamate-dependent acid resistance genes, the physiological inducer of gadW itself is unknown. It is not clear whether cadmium-QDs induce acidification of the intracellular environment or whether they interact with gadW through a different mechanism, which would fit more with the downregulation of the other acid response genes. Leucyl-tRNAs in the Cadmium Chalcogenide QD Response. Another trend identified by our differential expression analysis is the consistent downregulation of three H


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ACS Biomaterials Science & Engineering treatment condition (Figure 2D), and we find significant interaction between the CdTe-2.4 treatment and the ΔtusA knockout in the dark condition (Figure 5E). Unexpectedly, however, this interaction does not occur in the light condition of the QD treatment, despite fulfilling the superoxide response criteria in the transcriptomic analysis. The growth in light and dark for CdTe-2.4-challenged tusA knockout strains is essentially identical (Supporting Information Figure S3). TusA has been found to have an important role in conferring resistance to mutagenesis induced by DNA base oxidation, through its interaction with the cysteine desulfurase protein IscS.71 IscS is activated by TusA binding and is an important protein for the repair of iron−sulfur clusters,71−74 which we have previously shown are specifically damaged by the presence of superoxide in E. coli.23 Furthermore, TusA is known to be necessary for the expression and stability of the stress regulator RpoS,75,76 which we noted is related to two genes in the superoxide response set (dsrA and pdeC) as well as the acid shock gene gadW. The association of TusA with each of these processes suggests that it is related to the previously identified DNA damage response of E. coli to superoxide stress. However, the fact that the tusA knockout inhibition is specifically found to interact with the CdTe-2.4 dark treatment provides evidence for a confluence of the E. coli responses to superoxide and cadmium chalcogenide QDs. This is supported by the common observation of RpoS-related genes across transcriptomic categories and the prior research linking leucyltRNA downregulation to oxidative stress. Future studies may help to understand how the toxic factor (superoxide generation) and nontoxic factors (cadmium chalcogenide materials) of CdTe-2.4 treatments induce similar responses in E. coli.

adaptation of the bacteria and will further the goal to apply these QDs as an antibacterial therapeutic strategy.

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MATERIALS AND METHODS

Quantum Dot Synthesis. Cadmium telluride and cadmium selenide QDs were synthesized following methods in Courtney et al. 201619. QDs were synthesized sterilely and purified prior to use in studies. Particles were washed using 3 kDa Pall Nanosep centrifugal filter devices that were first sterilized, following manufacturer’s instructions, with 70% ethanol. QDs were stored at pH ≥ 11 for stability. RNA Extraction Cell Growth Conditions. E. coli MG1655 (ATCC700926) was plated streaked from freezer stock onto lysogeny broth (LB), agar plates (2% LB, 1.5% agar). Two individual colonies were selected and grown overnight in M9 minimal medium (1x M9 minimal media salts solution (MP Biomedicals), 2.0 mM MgSO4, 0.1 mM CaCl2, and 0.4% glucose). Cells were then diluted 1:100 into fresh M9 and were grown at 37 °C in a Tecan GENios with continuous shaking at 200 rpm during treatment. The conditions, collected in biological duplicates, were as follows: no treatment, 10 nM CdTe-2.4 in light, 10 nM CdTe-2.4 in dark, 10 nM CdSe-2.4 in light, and 10 nM CdSe-2.4 in dark. Nanoparticle concentration was held at 10 nM for both CdSe-2.4 and CdTe-2.4. For “Light” conditions, cultures were illuminated with a white light light-emitting diode (LED) sheet (1.6 mW/cm2). The cells were grown with treatment for 5 h in 96-well plates, using four wells per biological replicate that were pooled into 1 mL of culture at the end of the 5 h. This was done to maintain consistent growth behavior of the plate cultures that was observed in our QD treatment growth experiments. After 5 h, the OD was 0.3−0.6, and the 1 mL of culture was pelleted by centrifugation at 4000 rpm for 10 min. Electron Paramagnetic Resonance Spectroscopy. CdTe-2.4 and CdSe-2.4 QD samples filtered as described above prior to spectroscopy. Aliquots (100 μL) of respective QD were mixed with 1 μL of the spin trapping agent 5,5-dimethyl-1-pyrroline N-oxide (DMPO; Dojindo) and wrapped in foil to eliminate exposure to light. Three quartz capillaries were filled with the QD, DMPO mixture and measured in a Bruker Elexsys E 500 spectrometer (SHQE resonator) using a microwave attenuation of 16 dB, power of 5W, and operated in a dark room. After the machine was tuned, a measurement was taken in dark and subtracted from postillumination spectra. This protocol eliminated the minimal effects of ambient light exposure and the omnipresent SiO2 E′. The sample was then exposed to 60 s of white light (9 mW/cm2) and immediately remeasured. Both dark and light measurements consisted of 10 consecutive scans (20.48 s each) over a range of 200 G (0.05 G resolution) centered on 3515 G. Presence of DMPO adducts was confirmed using Bruker’s SpinFit software to fit measured spectra to the following parameters: DMPO−OH: aN = 14.90 G and aHb = 14.93 G, DMPO-OOH: aN = 14.2 G, aHb = 11.4 G, and aHg1 = 1.2 G. EPR to Determine ROS Concentration. Quantification of ROS present from the EPR spectra was done using SpinFit (Bruker). Dark spectra were subtracted from those after illumination, and the resulting spectra were fitted to the parameters detailed above. With the EPR software, the spectra were then double-integrated to yield a count of spins detected from DMPO-ROS adducts. Radical concentrations were then calculated using the known active volume consistent across all samples. Cyclic Voltammetry. A three-electrode configuration in phosphate-buffered saline (PBS) was used for the cyclic voltammetry study of CdTe-2.4 QDs using a Biologic SP-200 potentiostat/galvanostat. Glassy carbon plate, platinum wire, and Ag/AgCl were used as working, counter, and reference electrodes, respectively. For measurements in oxygen-free buffer, the solvent was bubbled with argon for 30 min, and an argon-rich headspace was maintained. RNA Sample Preparation. Cell pellets described above were treated with Qiagen RNAprotect and flash frozen in a dry ice, ethanol bath for storage at −80 °C. RNA was then extracted using Thermo Scientific GeneJET RNA Purification Kit. The RNA was then treated

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CONCLUSIONS Across our comparisons of differential expression, which aim to determine and isolate the varied transcriptomic responses of E. coli to CdTe-2.4 QDs, we identify consistent markers of DNA damage response, particularly in relation to iron−sulfur clusters that are known to be sensitive to superoxide. On the basis of the observed toxicity of the CdTe-2.4 light treatment as opposed to other conditions, this evidence suggests that these QDs induce toxicity primarily via deactivation of ironrich [Fe−S] clusters, which is supported by our prior research.20,23,29 Our observations regarding the sulfur mediator tusA contribute to these findings about the role of iron−sulfur cluster proteins in the superoxide effect on E. coli. In addition to this, the DNA damage and tusA response both point to a role for RpoS in regulation of CdTe-2.4 toxicity. Furthermore, in relation to the cadmium chalcogenide QD response, we identify the potential importance of tRNA processes, and leucine in particular. The effect of leucine is reinforced by synergistic inhibitory interaction of leucine supplementation with CdTe-2.4 light treatment, suggesting that leucyl-tRNAs are directly involved in cell fitness during CdTe-2.4 challenge. Additionally, the importance of tRNAs in this response is supported by the observation that L-alanine supplementation interacts with QD treatment, while D-alanine supplementation does not. In total, our experiments demonstrate a transcriptomic response of E. coli cells responding to both toxicity induced by superoxide and milder stress from the presence of cadmium chalcogenide QDs. Future work will help to understand how these responses may come together as an I


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between the two treatments was determined using a two-way ANOVA test.

with Thermo Scientific TURBO DNA-free kit following the rigorous digestion protocol. Library preparation of the 10 samples (two biological replicates of five conditions) was done according to Shishkin et al.77 Sequencing was performed as 1 × 50, stranded, on three lanes in an Illumina HiSeq at the BioFrontiers Next Generation Sequencing facility at the University of Colorado Boulder. The three lanes generated an average of 126.7 million reads with a mean quality score of 35.7. RNA-seq Data Processing. All data processing was done with resources on the University of Colorado BioFrontiers Institute computing core. The lanes were demultiplexed individually using fastq-multx in ea-utils v1.1.278 and then trimmed using TRIMMOMATIC v0.32.79 Trimmomatic was run to trim/remove reads for Illumina adapters, quality, and minimum length. Reads were trimmed to remove leading or trailing low quality (below quality 3) or “N” bases, and further a 4 bp sliding window was used with trimming occurring when the average quality per base dropped below 15. Reads were also removed if the length was less than 25 bp. The sample files from the three lanes were then merged to obtain 10 FASTQ files, one for each sample. The FASTQ files were then run through Rockhopper80,81 to determine the rRNA, which was 3−4% for each sample showing high rRNA depletion during library prep. The FASTQ files were then aligned using Bowtie2 v2.2.382 to E. coli MG1655 index (NCBI Reference Sequence NC_000913.3) with the “sensitive” preset settings. We then generated BAM files from the Bowtie2 output using Samtools v0.1.18. We then used HTSeq v0.6.183 to generate count tables for the 10 samples. Count tables were merged into a text file, and differential expression analysis between conditions, with pooled replicates, was performed using DESeq v3.4, using the Benjamini−Hochberg procedure to correct for multiple testing.24 Genes that were found to be significantly differentially expressed (P < 0.1) are displayed in Supporting Information Tables S4−S7. E. coli Growth and Toxicity Experiments. For all growth curve experiments bacterial cultures were grown overnight (16 h) in M9 media (1x M9 minimal media salts solution (MP Biomedicals), 2.0 mM MgSO4, and 0.1 mM CaCl2 in sterile water) with 0.4% glucose at 37 °C with 225 rpm shaking after inoculation from a single colony off of solid 2% LB with 1.5% agar. For long-term storage, bacterial strains were stored in freezer stocks in 60% LB broth, 40% glycerol at −80 °C. Overnight cultures were diluted 1:10 and regrown in M9 for 3 h prior to diluting 1:1000 into 100 μL of M9 media, supplemented with 25 nM of CdTe 2.4 eV where appropriate, in a 96-well plate. Cultures were grown for 22 h at 37 °C in a Tecan GENios, with continuous shaking at 200 rpm, with optical density measurements taken every 30 min at 562 nm with a bandwidth of 35 nm. For “Light” conditions, cultures were illuminated with a white-light LED sheet (1.6 mW/ cm2). Keio Collection strains84 were supplemented with 50 μg/mL of Kanamycin at all times, while the wild-type strain BW25113 had no antibiotics. For amino acid supplementation, powder amino acids (Sigma) where dissolved in ddH2O for a 100X stock solution (65 mM). E. coli MG1655 (ATCC700926) bacteria were cultured, and optical densities were measured as described above and supplemented with various amino acids. Interaction Calculation. Synergistic and antagonistic behavior of combination treatments was determined using the Bliss Independence model,46 according to the following equations:

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S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsbiomaterials.9b01087. Unique cadmium chalcogenide QD response genes. Unique superoxide response genes. Overlap superoxide and cadmium QD response genes. Calculated differentially expressed genes for CdTe-2.4. Light with respect to all other conditions and log2-fold change in expression, P < 0.1. Calculated differentially expressed genes for CdTe-2.4. Dark with respect to all remaining conditions and log2-fold change in expression, P < 0.1. Calculated differentially expressed genes for CdSe-2.4. Light with respect to all remaining conditions and log2fold change in expression, P < 0.1. Calculated differentially expressed genes for CdSe-2.4 Dark with respect to all remaining conditions and log2-fold change in expression, P < 0.1. Combination of gene knockout condition with CdTe-2.4 treatment, superoxide response genes. Combination of gene knockout condition with CdTe-2.4 treatment, cadmium-based QD response genes. Combination of gene knockout condition with CdTe-2.4 treatment, overlapping response genes, and regulators (PDF) Accession Codes

Data availability: Raw data RNA-seq FASTQ files and processed count tables can be found in the NCBI GEO repository under Accession No. GSE126008.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Prashant Nagpal: 0000-0002-7966-2554 Anushree Chatterjee: 0000-0002-8389-9917 Author Contributions

T.A.: RNA-seq data processing, experimental data analysis, manuscript writing and editing. K.E.: Experimental data collection and analysis, manuscript editing. C.C.: RNA-seq data collection and processing. M.L. and S.G.: Data collection and analysis. P.N. and A.C.: Supervision, manuscript editing. Notes

The authors declare no competing financial interest.

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ExpectedGrowth CombinedTreatments ObservedGrowth Treatment1 × ObservedGrowth Treatment2 = ObservedGrowthNoTreatment

ACKNOWLEDGMENTS We thank the BioFrontiers Next Generation Sequencing facility at the Univ. of Colorado Boulder. This work was supported by DARPA Young Faculty Award (D17AP00024) to A.C. and Translational Resesarch Institute through NASA Cooperative Agrrment NNX16AO69A to A.C. and P.N., NSF Graduate fellowship (DGE 1144083) to C.M.C. We also acknowledge financial support for this work by the W. M. Keck Foundation to P.N. and A.C.

(1)

S ‐value = (ExpectedGrowth CombinedTreatments − ObservedGrowth CombinedTreatments) /ObservedGrowthNoTreatment

ASSOCIATED CONTENT

(2)

Positive s-values denote synergistic interaction, whereas negative svalues denote antagonistic interaction. Significance of interaction J


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(19) Courtney, C. M.; Goodman, S. M.; McDaniel, J. A.; Madinger, N. E.; Chatterjee, A.; Nagpal, P. Photoexcited quantum dots for killing multidrug-resistant bacteria. Nat. Mater. 2016, 15, 529−534. (20) Courtney, C. M.; Goodman, S. M.; Nagy, T. A.; Levy, M.; Bhusal, P.; Madinger, N. E.; Detweiler, C. S.; Nagpal, P.; Chatterjee, A. Potentiating antibiotics in drug-resistant clinical isolates via stimuliactivated superoxide generation. Sci. Adv. 2017, 3, 1−11. (21) Wang, Z.; Gerstein, M.; Snyder, M. RNA-Seq: a revolutionary tool for transcriptomics. Nat. Rev. Genet. 2009, 10, 57−63. (22) Buettner, G. R. The spin trapping of superoxide and hydroxyl free radicals with DMPO (5,5-dimethylpyrroline-N-oxide): more about iron. Free Radical Res. Commun. 1993, 19, S79−S87. (23) Levy, M.; Courtney, C. M.; Chowdhury, P. P.; Ding, Y.; Grey, E. L.; Goodman, S. M.; Chatterjee, A.; Nagpal, P. Assessing Different Reactive Oxygen Species as Potential Antibiotics: Selectivity of Intracellular Superoxide Generation Using Quantum Dots. ACS Appl. Bio Mater. 2018, 1, 529−537. (24) Anders, S.; Huber, W. Differential expression analysis for sequence count data. Genome Biol. 2010, 11, 1−12. (25) Imlay, J. A.; Linn, S. Damage and Oxygen Radical. Science (Washington, DC, U. S.) 1988, 240, 1302−1309. (26) Keyer, K.; Imlay, J. A. Superoxide accelerates DNA damage by elevating free-iron levels. Proc. Natl. Acad. Sci. U. S. A. 1996, 93, 13635−13640. (27) Müller, A.; Langklotz, S.; Lupilova, N.; Kuhlmann, K.; Bandow, J. E.; Leichert, L. I. O. Activation of RidA chaperone function by Nchlorination. Nat. Commun. 2014, 5, 5804. (28) Sledjeski, D. D.; Gupta, A.; Gottesman, S. The small RNA, DsrA, is essential for the low temperature expression of RpoS during exponential growth in Escherichia coli. EMBO J. 1996, 15, 3993− 4000. (29) Goodman, S. M.; Levy, M.; Li, F.-F.; Ding, Y.; Courtney, C. M.; Chowdhury, P. P.; Erbse, A.; Chatterjee, A.; Nagpal, P. Designing Superoxide-Generating Quantum Dots for Selective Light-Activated Nanotherapy. Front. Chem. 2018, 6, 1−12. (30) Reed, J. L.; Patel, T. R.; Chen, K. H.; Joyce, A. R.; Applebee, M. K.; Herring, C. D.; Bui, O. T.; Knight, E. M.; Fong, S. S.; Palsson, B. O. Systems approach to refining genome annotation. Proc. Natl. Acad. Sci. U. S. A. 2006, 103, 17480−17484. (31) Iyer, R.; Iverson, T. M.; Accardi, A.; Miller, C. A biological role for prokaryotic ClC chloride channels. Nature 2002, 419, 715. (32) Nie, L.; Ren, Y.; Janakiraman, A.; Smith, S.; Schulz, H. A Novel Paradigm of Fatty Acid β-Oxidation Exemplified by the ThioesteraseDependent Partial Degradation of Conjugated Linoleic Acid That Fully Supports Growth of Escherichia coli. Biochemistry 2008, 47, 9618−9626. (33) Begley, T. P.; Kinsland, C.; Strauss, E. The biosynthesis of coenzyme A in bacteria. Vitam. Horm. 2001, 61, 157−171. (34) Sayed, A. K.; Odom, C.; Foster, J. W. The Escherichia coli AraC-family regulators GadX and GadW activate gadE, the central activator of glutamate-dependent acid resistance. Microbiology 2007, 153, 2584−2592. (35) Tramonti, A.; De Canio, M.; Delany, I.; Scarlato, V.; De Biase, D. Mechanisms of transcription activation exerted by GadX and GadW at the gadA and gadBC gene promoters of the glutamate-based acid resistance system in Escherichia coli. J. Bacteriol. 2006, 188, 8118−8127. (36) Takada, A.; Umitsuki, G.; Nagai, K.; Wachi, M. RNase E Is Required for Induction of the Glutamate-Dependent Acid Resistance System in Escherichia coli. Biosci., Biotechnol., Biochem. 2007, 71, 158−164. (37) Jin, Y.; Watt, R. M.; Danchin, A.; Huang, J. Small noncoding RNA GcvB is a novel regulator of acid resistance in Escherichia coli. BMC Genomics 2009, 10, 165. (38) Keseler, I. M.; Mackie, A.; Peralta-Gil, M.; Santos-Zavaleta, A.; Gama-Castro, S.; Bonavides-Martínez, C.; Fulcher, C.; Huerta, A. M.; Kothari, A.; Krummenacker, M.; Latendresse, M.; Muñiz-Rascado, L.; Ong, Q.; Paley, S.; Schröder, I.; Shearer, A. G.; Subhraveti, P.; Travers, M.; Weerasinghe, D.; Weiss, V.; Collado-Vides, J.; Gunsalus,

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Isolating the Escherichia coli Transcriptomic Response to Superoxide

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