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. Author manuscript; available in PMC: 2013 Dec 14.
Published in final edited form as: Mol Cell. 2012 Oct 30;48(5):713–722. doi: 10.1016/j.molcel.2012.10.001

Protein aggregation caused by aminoglycoside action is prevented by a hydrogen peroxide scavenger

Jiqiang Ling 1, Chris Cho 1, Li-Tao Guo 1, Hans Aerni 2,3, Jesse Rinehart 2,3,*, Dieter Söll 1,4,*
PMCID: PMC3525788  NIHMSID: NIHMS413596  PMID: 23122414

SUMMARY

Protein mistranslation causes growth arrest in bacteria, mitochondrial dysfunction in yeast, and neurodegeneration in mammals. It remains poorly understood how mistranslated proteins cause such cellular defects. Here we demonstrate that streptomycin, a bactericidal aminoglycoside that increases ribosomal mistranslation, induces transient protein aggregation in wild-type Escherichia coli. We further determined the aggregated proteome using label-free quantitative mass spectrometry. To identify genes that reduce cellular mistranslation toxicity, we selected from an overexpression library protein products that increased resistance against streptomycin and kanamycin. The selected proteins were significantly enriched in members of the oxidation-reduction pathway. Overexpressing one of these proteins, alkyl hydroperoxide reductase subunit F (a protein defending bacteria against hydrogen peroxide), but not its inactive mutant, suppressed aggregated protein formation upon streptomycin treatment and increased aminoglycoside resistance. This work provides in-depth analyses of an aggregated proteome caused by streptomycin, and suggests that cellular defense against hydrogen peroxide lowers the toxicity of mistranslation.

Keywords: Protein synthesis, translational fidelity, oxidative stress

INTRODUCTION

Translational fidelity is maintained throughout all three domains of life, suggesting a high selective pressure during evolution to minimize protein synthesis errors (Drummond and Wilke, 2008). It is estimated that the average amino acid misincorporation rate is 10−4-10−3 (Ling et al., 2009; Zaher and Green, 2009). Increased levels of translational errors have been shown to result from aminoglycoside antibiotics (Davies et al., 1964), oxidative stress (Ling and Söll, 2010; Netzer et al., 2009), or mutations in tRNAs (Cochella and Green, 2005), the ribosome (Ogle and Ramakrishnan, 2005), and aminoacyl-tRNA synthetases (Ling et al., 2009; Reynolds et al., 2010a). Severe mistranslation leads to growth arrest or cell death in bacteria (Bacher et al., 2005; Karkhanis et al., 2007; Kohanski et al., 2008; Mascarenhas et al., 2008; Roy et al., 2004), and respiratory defects in yeast (Reynolds et al., 2010b). Strikingly, a slight decrease in translational fidelity (caused by a mutation in alanyl-tRNA synthetase) leads to a severe neurological disorder in mice (Lee et al., 2006). The mechanism by which mistranslated proteins leads to such cellular defects remains poorly understood. In bacteria, erroneous protein synthesis induces the heat shock response (Ruan et al., 2008), implying that mistranslated proteins are susceptible to misfolding. It is proposed that the toxicity of mistranslation likely results from a gain in deleterious function of misfolded proteins (Drummond and Wilke, 2009).

Protein misfolding and aggregation are strongly associated with bacterial cellular defects and multiple human neuropathies, such as amyotrophic lateral sclerosis and Alzheimer’s disease (Tyedmers et al., 2010; Winklhofer et al., 2008). In many diseases, misfolding and aggregation of proteins primarily lead to a toxic gain of function (Winklhofer et al., 2008), but a recent study shows that in mammalian cells, amyloid-like protein aggregates also sequester many proteins with essential functions, thus reducing cell viability through a loss of function (Olzscha et al., 2011). Aggregated protein formation is normally prevented by molecular chaperones and proteases through refolding and degradation of aberrant proteins (Bukau et al., 2006; Hartl and Hayer-Hartl, 2009), yet mutations, aging and stresses may severely perturb cellular proteostasis and result in protein aggregation (Powers et al., 2009; Tyedmers et al., 2010).

Aminoglycosides, including streptomycin (Str) and kanamycin (Kan), are a group of bactericidal antibiotics that target the ribosome to induce amino acid misincorporation (Davies et al., 1964; Gromadski and Rodnina, 2004; Sharma et al., 2007). It has been suggested that misread proteins could disrupt the integrity of membranes in bacteria, causing increased aminoglycoside uptake and irreversible inhibition of the ribosome (Davis, 1987). The bactericidal effect of aminoglycosides has been proposed to result from an increased level of oxidative damage of DNA, proteins and membranes (Kohanski et al., 2010; Kohanski et al., 2007). In Escherichia coli, Str does not appear to increase the intracellular levels of hydrogen peroxide (H2O2) and superoxide, yet the protein oxidation (carbonylation) level is significantly elevated upon Str treatment (Dukan et al., 2000). This has led to the hypothesis that mistranslated proteins are more susceptible to oxidation due to misfolding (Dukan et al., 2000; Maisonneuve et al., 2008). In this work, we show that Str causes transient protein aggregation in E. coli, and provide an in-depth mass spectrometry analysis of the aggregated proteome resulting from Str-induced mistranslation. We have further identified a critical role of alkyl hydroperoxide reductase in protecting bacteria from aminoglycoside-induced protein aggregation and cell death, suggesting that decreasing the intracellular level of H2O2 improves the bacterial tolerance against mistranslated proteins. Our study thus raises intriguing possibilities to reduce the toxicity of protein mistranslation via modulating the cellular level of oxidative stress.

RESULTS

Selection of proteins critical for aminoglycoside resistance

To identify genes that reduce the toxicity of aminoglycosides, we utilized an E. coli overexpression (ASKA) library (Kitagawa et al., 2005) to select for proteins that could increase bacterial resistance against Str and Kan. The ASKA library covers all E. coli open reading frames (ORF), with ORFs individually cloned into an overexpression plasmid with a pBR322 origin and a T5-lac promoter. The plasmid library was transformed into the wild-type (WT) E. coli strain MG1655, and the transformants were selected aerobically on Luria Agar plates containing either 10 μg/ml Str or 10 μg/ml Kan (2.5-fold higher than the minimal inhibitory concentration, or MIC) with over 10-fold library coverage. Less than 1% of the transformants were able to grow under the selection conditions. Plasmids from surviving clones were extracted and sequenced, and selections with Str and Kan each uncovered 18 genes, including 9 identified in both selections (Tables 1 and S1). Pathway enrichment analyses (Carbon et al., 2009) revealed that the only significantly enriched biological process during the selections was oxidation-reduction (P<0.01) (Tables S2 and S3).

Table 1.

Genes selected on plates with 10 μg/ml Str

Gene
name		 Description
ahpF alkyl hydroperoxide reductase, subunit F, FAD/NAD(P)-binding
azoR NADH-azoreductase, FMN-dependent
cysJ sulfite reductase, alpha subunit, flavoprotein
fldA flavodoxin 1
fpr ferredoxin-NADP(+) reductase
gor glutathione oxidoreductase
iscU FeS cluster assembly scaffold
IpdA dihydrolipoamide dehydrogenase
mdaB NADPH quinone reductase
moaA molybdopterin biosynthesis protein A
murB UDP-N-acetylenolpyruvoylglucosamine reductase, FAD-binding
nudE adenosine nucleotide hydrolase
paaD phenylacetate-CoA oxygenase, PaaJ subunit
ribC riboflavin synthase, alpha subunit
ubiX 3-octaprenyl-4-hydroxybenzoate carboxy-lyase
ydhF oxidoreductase
yejG hypothetical protein, glutamine metabolism
yqjD Putative acyl-CoA carboxylase
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See also Figure S3 and Tables S1-S3.

To validate the selected genes, we extracted individual plasmids from the original library, re-transformed them into fresh MG1655 and BW25113 (the parental strain for the Keio knockout library) competent cells, and tested for MICs. Overexpression of the selected genes increased the MICs of Str and Kan 2- to 8-fold, but showed no effect on the MICs of spectinomycin (Spc) and ampicillin (Amp) (Figure 1). Spc is a bacteriostatic aminocyclitol antibiotic closely related to aminoglycosides; it inhibits protein synthesis but does not increase translational errors (Kohanski et al., 2008). Amp, on the other hand, is a bactericidal antibiotic targeting cell wall synthesis and has been suggested to trigger hydroxyl radical formation in E. coli (Kohanski et al., 2007). Our results show that the selected genes specifically affect bacterial resistance against mistranslation-inducing aminoglycosides.

Figure 1. Minimum inhibitory concentrations of WT E. coli strains overexpressing the selected proteins.

Figure 1

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The selected proteins specifically enhance resistance against Str and Kan in (A) MG1655 and (B) BW25113, but have no effect on Spc or Amp. The average of three replicate experiments are shown with p-values indicated. See also Figure S2.

Increased aminoglycoside resistance requires the catalytic activities of the selected proteins

The enrichment of oxidation-reduction genes during our selections prompted us to investigate whether other antioxidant enzymes could also increase aminoglycoside resistance. Unlike alkyl hydroperoxide reductase subunit F (AhpF) that was identified during our selection, overexpression of AhpC, catalases (KatE, KatG), superoxide dismutases (SodA, SodB), or a H2O2 sensor (OxyR) failed to enhance bacterial resistance against Str or Kan (Figure 2A). Given the well-characterized function of chaperones and proteases in detoxifying aberrant proteins (Bukau et al., 2006; Hartl and Hayer-Hartl, 2009), it was unexpected that no such genes were identified during the selections. Further MIC tests showed that overexpression of individual chaperones or proteases (ClpB, GroS, GroL, HslO, HslV, IbpA and IbpB) had little effect on aminoglycoside resistance (Figures 2A and S1). Previous gene profile analyses have shown that Kan treatment upregulates the expression of a number of chaperones and proteases involved in the unfolded protein response, including ClpB, GroS, GroL, Lon, HslO, HslU, HslV, DnaJ, DnaK, IbpA and IbpB (Kohanski et al., 2008). It appears that the cellular level of protein refolding and degradation power is already high in the presence of aminoglycosides, and thus overexpression of individual chaperones or proteases does not further increase aminoglycoside resistance.

Figure 2. Minimum inhibitory concentrations of E. coli strains overexpressing (A) chaperones, proteases and anti-oxidant proteins, and (B) WT and active-site mutants of the selected proteins.

Figure 2

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The average of three replicate experiments are shown with p-values indicated. See also Figure S1.

Next we tested how deletion of the selected genes affected E. coli resistance against antibiotics. The Keio single-gene knockout strains (Baba et al., 2006) contain a Kan resistance gene (kanR), which also affects the MIC of Str. We thus attempted to delete kanR as described (Datsenko and Wanner, 2000) in the knockout strains lacking the genes of interest. 14 kanR-free strains were obtained and subsequently used for MIC tests. Unexpectedly, deleting certain selected genes, such as azoR, hyfA, lpdA, paaD, and yejG, increased the MIC levels of Str and Kan (Figure S2). This indicates that these genes may be involved in the networks critical for aminoglycoside resistance; perturbing such networks (by either overexpression or deletion of these genes) may result in improved fitness in the presence of aminoglycosides. AhpF is a component of alkyl hydroperoxide reductase, which is the primary scavenger of H2O2 in E. coli (Imlay, 2008). The peroxidase subunit AhpC converts H2O2 to water, and AhpF reduces oxidized AhpC for the next round of H2O2 scavenging. It has been previously shown that the reduction activity of AhpF is dependent on Cys345 and Cys348, and mutating either cysteine to serine significantly decreases the peroxidase activity of AhpCF (Li Calzi and Poole, 1997). We therefore tested whether the mechanism of resistance was dependent on the catalytic activity of AhpCF. In contrast to the WT AhpF, the C345S and C348S variants were not able to increase bacterial resistance against Str or Kan (Figure 2B). Similarly, mutating the active-site cysteine residues of Gor (C47) and IscU (C63), which are essential for glutathione reduction (Deonarain et al., 1990) and iron-sulfur cluster assembly (Kato et al., 2002), respectively, abolished the role of Gor and IscU to enhance aminoglycoside resistance (Figure 2B). These results suggest that the catalytic activities of AhpF, Gor and IscU are required for improving bacterial fitness in the presence of aminoglycosides.

Streptomycin-induced protein aggregation is suppressed by overexpressing AhpF

Mistranslation has been suggested to increase the level of misfolded proteins (Kohanski et al., 2008; Powers et al., 2009; Tyedmers et al., 2010), which are prone to aggregation (Bukau et al., 2006; Hartl and Hayer-Hartl, 2009). A previous study indicates that Str can induce protein aggregation in E. coli (Lindner et al., 2008). We thus decided to directly measure the effects of aminoglycosides on protein aggregation. WT E. coli cells were grown to mid-log phase and treated with Str or Spc for 0.5, 1, and 2 hours. Total membrane-free protein aggregates were isolated based on an established method from Bukau and colleagues (Tomoyasu et al., 2001). Aggregated proteins significantly increased after 0.5 hour treatment with Str, and returned to the background level after 1 hour (Figure 3). In contrast, Spc treatment did not increase protein aggregation. These data suggest that the transient aggregated protein formation in the presence of Str is caused by the misfolding of erroneously-synthesized proteins, or the destabilization of proteins that prevent protein aggregation.

Figure 3. Str induces protein aggregation in WT E. coli.

Figure 3

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BW25113 cells were grown to A600 ~0.5 before addition of 10 g/ml Str or 100 g/ml Spc. Cells were harvested after 0.5, 1 or 2 hours of treatment with antibiotics, and protein aggregates were isolated. (A) Soluble proteins and (B) aggregated proteins were separated using SDS-PAGE and revealed with Coomassie blue and silver staining, respectively. See also Figure S4.

To understand the correlation between protein aggregation and aminoglycoside sensitivity, we further tested how overexpression of the selected proteins affected aggregate formation. Overexpressing AhpF, AzoR, Fpr, Gor and IscU significantly decreased Str-induced protein aggregation (Figure 4A). Using a previously established mistranslation reporter assay (Ballesteros et al., 2001), we showed that overexpression of AhpF did not affect the rate of nonsense suppression in the presence of Kan (Figure S3), suggesting that AhpF did not decrease the level of mistranslation. In contrast, overproducing Gor or IscU decreased Kan-induced nonsense suppression, likely through reduced uptake of aminoglycosides into cells. We thus focused on the role of AhpF in suppressing aggregation. In contrast to the WT AhpF, the C348S variant did not prevent aggregated protein formation in the presence of Str (Figure 4B), suggesting that H2O2 contributes to protein aggregation. Consistent with this notion, higher concentrations of Str is required to induce aggregation under anaerobic conditions (Figure S4).

Figure 4. Overexpression of the selected proteins prevents Str-induced protein aggregation.

Figure 4

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(A) BW25113 cells overexpressing selected proteins were treated with 10 g/ml Str or 100 g/ml Spc for 0.5 hour. Asterisks indicate the size of the overexpressed proteins. (B) Hydrogen peroxide scavenging activity is required for AhpF to prevent Str-induced protein aggregation. BW25113 cells overproducing WT and C348S AhpF were treated with 10 g/ml Str for 0.5 and 1 hour. The WT AhpF, but not the inactive C348S variant, was able to suppress Str-induced protein aggregation.

Characterization of the aggregated proteomes

To understand what proteins are susceptible to Str-induced aggregation, we determined the aggregated proteomes from Spc- and Str-treated E. coli (Figure S5) using label-free quantitative mass spectrometry (Table S4). Applying high stringency cut-off parameters (Figure 5), a total of 647 proteins were identified in the Str-induced aggregated proteome, of which only 28 were present in the aggregate from Spc-treated cells (Table S4). Using the MS-identified E. coli proteins (a total of 977 in this study) from aggregated and soluble samples as the background, we show that the ribosomal proteins are significantly enriched in the Spc aggregated proteome (P=4×10−6) (Table S5); this is likely because these proteins form a large complex and are highly abundant in the cell (Ishihama et al., 2008). For the aggregated proteome from Str-treated cells, significantly enriched pathways (P<0.05) include tRNA aminoacylation, citrate cycle and pyruvate metabolism (Figure 5). According to the emPAI score (Ishihama et al., 2005), the most abundant proteins in the Str aggregated proteome are mainly ribosomal proteins and chaperones (Table S6), and there is no strong correlation of protein abundance between the soluble and aggregated fractions (Figure S6). Next, we normalized the protein abundance in the Str-induced aggregate with that in soluble fractions from both Str- and Spc-treated cells (Table S4). A total of 225 proteins (including a number of chaperones, proteases and metabolic proteins) were found to be enriched in the Str-induced aggregated proteome compared to those proteins in the soluble fractions (emPAI ratio ≥2) (Figure 6 and Table S4). Among them, 146 proteins were only identified in the Str aggregated proteome, but not in the soluble samples from either Spc- or Str-treated cells. The enrichment of chaperones (IbpA, IbpB, ClpB and DnaJ) and heat-shock proteases (HslU, HslV, ClpX, ClpP and Lon) in the aggregated proteome is consistent with their roles in reversing aggregation and cleaving misfolded proteins (Mogk et al., 2003a; Mogk et al., 1999; Sauer and Baker, 2011).

Figure 5. Quantitative mass spectrometry analyses of the aggregated proteomes.

Figure 5

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(A) Numbers of proteins identified in the aggregates isolated from Spc- or Str-treated cells. Proteins with at least 2 significant peptides shown by LC-MS/MS, with a protein score of greater than 65, and present in at least 3 out of 4 biological replicates were considered to be identified. (B-D) Pathways enriched in the aggregated proteome induced by Str. The aggregated proteome from Str-treated cells was searched using DAVID Bioinformatics Resources 6.7 for pathway enrichment. All the proteins from soluble and aggregated samples identified by LC-MS/MS were set as the background. The figures were generated using STRING 9.0, where the lines indicate physical and functional interactions between proteins. Blue, purple and black lines indicate binding, catalysis and reaction, respectively. See also Figure S5 and Tables S4-S8.

Figure 6. Networks of proteins prone to Str-induced aggregation.

Figure 6

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We compared the relative abundance of the proteins identified in the aggregated proteome from Str-treated cells and in the soluble fractions from Spc- and Str-treated cells. 225 proteins were found to be enriched in the Str-induced aggregate compared to those in the soluble fractions. Shown here are two networks of interest. (A) Chaperones that have been shown to reverse protein aggregation and heat shock proteases (Mogk et al., 2003a; Mogk et al., 1999; Sauer and Baker, 2011) are enriched in the aggregated proteins. (B) Proteins involved in nitrogen metabolism are susceptible to aggregation. See also Figure S6.

Misfolded membrane proteins have been suggested to cause membrane disruption (Hancock, 1981), which lead to bacterial cell death. In our proteomics analyses, we identified 31 membrane proteins in the Str-induced aggregate; only 4 of these were also found in the Spc aggregate (Table S7), suggesting that the aggregated membrane proteins in the presence of Str results from misfolding events rather than membrane contamination. These membrane proteins identified here could serve as interesting candidates for future studies of the bactericidal mechanism of aminoglycosides.

Previous studies suggest that carbonylated proteins mainly accumulate in the aggregates (Maisonneuve et al., 2008). In line with this, we uncovered that 211 significant peptides in the Str-induced aggregated proteome contain carbonylated arginine (glutamic semialdehyde or GluSA) and lysine (aminoadipic acid) residues (Table S8). In addition, 37 peptides were found to contain cysteine trioxidation. These oxidized peptides result from 84 proteins that are significantly enriched in tRNA aminoacylation (P=5×10−7), tryptophan metabolism (P=0.004) and cellular respiration pathways (P=0.009) (Tables S5 and S8). It is possible that such proteins might be immediate targets for oxidation, and could serve as the seeds for the aggregation of other proteins.

DISCUSSION

Protein mistranslation and aggregation

The accuracy during protein synthesis is critical to ensure normal cellular functions and is maintained throughout evolution (Drummond and Wilke, 2009). Although mistranslation could be beneficial under certain conditions (Li et al., 2011; Netzer et al., 2009; Ruan et al., 2008), a high level of errors during protein synthesis is almost certainly detrimental to the cell (Reynolds et al., 2010a). Disruption of translational fidelity is suggested to cause protein misfolding and aggregation (Drummond and Wilke, 2009). Here, we show that a mistranslation-inducing aminoglycoside leads to protein aggregation in WT E. coli cells (Figure 3). The aggregated proteins disappear over time, presumably due to the disaggregation activities of chaperones like IbpA, IbpB, ClpB and DnaJ (Mogk et al., 2003a; Mogk et al., 2003b), which are found to be enriched in the Str-induced aggregated proteins (Figure 6 and Table S4). Our work thus provides evidence that IbpA, IbpB, ClpB and DnaJ directly associate with aggregated proteins, and could be critical for regulating the homeostasis of mistranslated proteins. Protein aggregation is considered a mechanism to sequester toxic misfolded proteins when the protein quality control machinery is over-saturated (Tyedmers et al., 2010; Winkler et al., 2010). The burst of aggregated protein formation in the presence of aminoglycosides suggests that the stress level of protein misfolding substantially increases due to mistranslation. It remains intriguing for future studies to investigate whether aminoglycoside-induced protein aggregation protects bacteria by reducing the toxicity of misfolded proteins, or instead harms cells by lowering the concentrations of essential proteins.

Aggregated proteomes have been determined in E. coli treated with heat shock and oxidative stress conditions (Tomoyasu et al., 2001; Winter et al., 2005), and in aging C. elegans (David et al., 2010). Here, we provide deep coverage of an aggregated proteome formed under error-prone translation conditions. 77 out of 93 proteins that aggregate in the ΔrpoH strain at 42 °C (Tomoyasu et al., 2001) are also present in the Str-induced aggregated proteome (Table S4), suggesting that these proteins are susceptible to unfolding and aggregation under both mistranslation and heat stress conditions.

Aminoglycosides and protein oxidative damage

Aminoglycoside antibiotics promote mistranslation by increasing decoding of mRNA codons by near-cognate tRNAs on the ribosome (Gromadski and Rodnina, 2004). Furthermore, treating E. coli cells with Str increases the level of protein carbonylation (Dukan et al., 2000; Maisonneuve et al., 2008). Because the activities of catalases and superoxide dismutases are not stimulated by Str, it is hypothesized that Str-induced mistranslation does not increase the intracellular concentrations of H2O2 and superoxide, but instead mistranslated proteins are more susceptible to oxidation (Dukan et al., 2000). Later studies show that aminoglycosides cause a depletion of the cellular NADH pool (Kohanski et al., 2007). We found that metabolic proteins, including those involved in the citrate cycle and pyruvate metabolism, are prone to aggregation in the presence of Str (Figures 5, 6, and Tables S4 and S5), which could contribute to the reduced level of NADH. Our proteome-wide identification of oxidized peptides provides a valuable resource in understanding the location and targets of protein oxidation events.

The peroxiredoxin AhpCF is the primary scavenger of H2O2 in bacteria and is active at low (nanomolar) concentrations of H2O2 (Imlay, 2008). The catalytic subunit AhpC is oxidized by H2O2 to form a disulfide bond, which is reduced by AhpF. It is suggested that the activity of AhpF may be limiting for AhpCF (Imlay, 2008; Poole, 2005). Our results show that overexpressing AhpF, but not AhpC or catalases, increases E. coli resistance against aminoglycosides. DNA microarray studies indicate that aminoglycoside treatment does not affect the expression of the endogenous AhpCF (Kohanski et al., 2008), and our proteomics results show that both AhpC and AhpF are present in the Str-induced aggregated proteome (Table S4). Overproduction of AhpF thus likely enhances the capacity of AhpC to maintain a low level of H2O2, whereas catalases are not effective under these conditions due to their high Km values for H2O2 (Imlay, 2008). The peroxidase activity of AhpF plays a critical role in preventing protein aggregation (Figure 4) and increasing resistance against Str and Kan (Figure 2B). In summary, we propose that overexpression of AhpF in E. coli reduces the oxidative damage of mistranslated proteins, alleviates the cellular toxicity of protein misfolding, and improves bacterial fitness in the presence of aminoglycosides.

EXPERIMENTAL PROCEDURES

Strains, reagents, and general protocols

E. coli strains MG1655 (λ−, rph-1) and BW25113 (Δ(araD-araB)567, ΔlacZ4787(∷rrnB-3), λ−, rph-1, Δ(rhaD-rhaB)568, hsdR514) were obtained from The E. coli Genetic Stock Center at Yale University. The ASKA E. coli ORF library was a gift from National BioResource Project (NBRP) in Japan. Antibiotics were purchased from Sigma-Aldrich (St. Louis, MO), and the silver staining kit was purchased from Thermo Scientific. Site-directed mutagenesis was performed using Pfu Ultra II DNA polymerase (Agilent, CA). Urea, Tris-HCl, CaCl2, iodoacetamide (IAA) were from Sigma-Aldrich (St. Louis, MO). Chloroform and Dithiothreitol (DTT) were from American Bioanalytical (Natick, MA). Methanol, Acetonitrile (ACN), trifluoroacetic acid (TFA), formic acid (FA) and HPLC grade water were obtained from Burdick and Jackson (Morristown, NH). Sequencing grade modified trypsin was from Promega (Madison,WI).

Selection of overexpression library

To select for proteins that reduce aminoglycoside toxicity, plasmids were extracted from the mixed E. coli ORF library and transformed into MG1655 with over 10-fold library coverage. Transformants were selected on Luria Agar plates containing 0.5 mM Isopropyl β-D-1-thiogalactopyranoside and 10 μg/ml Str or Kan. Plasmids from individual colonies were extracted and sequenced. The pathway enrichment analyses were performed using AmiGo (the Gene Ontology). For MIC tests, strains were grown in Luria Broth overnight at 37 °C. The overnight culture was diluted 50-fold and spotted on Luria Agar plates containing various concentrations of antibiotics. The growth was monitored after 24 hour incubation at 37 °C.

Aggregate isolation and determination

Protein aggregates were isolated from E. coli as previously described (Tomoyasu et al., 2001). The aggregated proteins were separated with SDS-PAGE and visualized with silver staining.

β-galactosidase assay

E. coli strain BW25113 was used in this study. The plasmid (pLacZ) used in the β-galactosidase assay was derived from pCDFDuet-1 vector. The transcription of the lacZ gene was controlled by an lpp promoter, and the mutant version of lacZ harbored an amber nonsense codon at amino acid position 3. pLacZ contained a Spc resistance gene that also affected the efficacy of Str. Therefore, Kan was used to measure the suppression rates.

To determine the β-galactosidase activity, 200 μl cultured cells were mixed with 800 μl buffer (60 mM Na2HPO4, 40 mM NaH2PO4, 10 mM KCl, 1 mM MgSO4, and 38.6 mM 2-mercaptoethanol), 15 μl 0.1% sodium dodecyl sulfate, 12 μl chloroform, and 100 μl 2-nitrophenyl β-D-galactopyranoside (10 mg/ml). After 25 minutes at 30 °C, the reaction was terminated by addition of 0.5 ml Na2CO3 (1 M). The Miller units for enzyme activity were calculated as A420/min per A600 unit of culture.

Protein extraction and digestion

The protein pellet was dissolved in 40 μl freshly prepared 8 M urea buffer prepared with 20 mM CaCl2 and 0.4 M Tris-HCl pH 8.0 (23 °C). Cysteines were r educed with 4.1 mM DTT for 10 minutes at 60 °C and then quenched on ice. Carbamidomethylation of cysteines was carried out in 8.3 mM IAA at room temperature in the dark for 30 minutes. Excess IAA was quenched with DTT and diluted with 271 μl 80 mM Tris-HCl buffer pH 8.0 (23 °C). Trypsin was adde d at an enzyme/protein ratio of 1:15 and the reaction was incubated for 15 h at 37 °C. The diges t was quenched with 16 μl of a 20 % TFA solution. Peptides were desalted using UltraMicroSpin columns (C18) from the Nest Group Inc. (Southborough, MA) and dried in a vacuum centrifuge. Finally, peptides were reconstituted in 15 μl 3:8 by volume of 70 % FA/0.1 % TFA. The peptide concentration was determined on a NanoDrop spectrophotometer (Thermo Fisher Scientific, Pittsburgh, PA), and the concentration was adjusted to 0.4 μg/μl for both the soluble and Str-induced aggregated protein samples. The Spc-treated cells were adjusted to the same OD as the Str-treated cells.

Mass spectrometry

LC-MS/MS was performed on an Orbitrap Velos (Thermo Fisher Scientific) equipped with an online nanospray source operated at 1.8 kV spray voltage. One survey scan in the Orbitrap from m/z 298-1750 was followed by up to 10 tandem MS experiments of the most abundant precursor ions using Higher Collisional Energy Dissociation (HCD) (Olsen et al., 2007). Spectra were acquired with data-dependent acquisition at a resolving power of 30,000 and 7,500 for the survey and product ion scans, respectively. Methyl stearate was applied to a calibrant reservoir within the nanospray spray chamber (Pelander et al., 2011) providing a constant signal at m/z 299.294457 for lockmass calibration. Liquid chromatography was carried out on a nanoAcquity UPLC (Waters, Milford, MA) equipped with a 180 μm × 20 mm C18 nanoAcquity UPLC trap column and a BEH130C18 Waters symmetry 75 μm ID × 250 mm capillary column packed with 5 and 1.7 μm particles, respectively. The mobile phases were (A) 0.1 % FA in water and (B) 0.1 % FA in acetonitrile. A vented split set-up was used for trapping of up to 2 μg peptides at a flow rate of 5 μl/min performed for 3 minutes at 1 % B. Gradient elution was carried out with a 200-minute method using a flow rate of 0.3 μl/min. The gradient was 1-10 % B for 2 minutes, 10-25 % B for 150 minutes and 25-50 % B for 20 minutes followed by 7 minutes at 95 % B with subsequent re-equilibration of the column at 1 % B. Five microliters with up to 2 μg peptides were injected for each analysis.

Data analysis

Raw spectra from the Orbitrap were processed using Mascot Distiller and searched in-house with MASCOT (v. 2.3.2) against the EcoCyc (Keseler et al., 2011) protein database release 16.0 for E. coli K-12 (MG1655). Forward and decoy database searches were performed with full trypsin specificity allowing up to 2 missed cleavages and using a mass tolerance of ±30 ppm for the precursor and ±0.6 Da for fragment ions, respectively. The following variable modifications were considered for searching: Carbamidomethyl (C), Arg-> GluSA (R) Lys->aminoadipic acid (K) Oxidation (M), Trioxidation (C). Typical FDR were <0.3% for peptides above identity threshold and <2% considering all peptides above identity or homology threshold. A protein was considered identified when MASCOT listed it as significant with a protein score of >65, and more than 2 peptides matched the same protein. The emPAI scores were calculated as (Ishihama et al., 2005). The MASCOT search results were deposited in the Yale Protein Expression Database (YPED) (Shifman et al., 2007).

Pathway enrichment of MS-identified proteins was performed using DAVID Bioinformatics Resources 6.7 (Huang da et al., 2009a, b). The protein interaction maps were generated using STRING 9.0 (Szklarczyk et al., 2011) with a high confidence score (0.700).

Supplementary Material

01

Highlights.

  • In-depth coverage of the aggregated proteome induced by streptomycin in E. coli

  • Identified proteins susceptible to oxidation and streptomycin-induced aggregation

  • Alkyl hydroperoxide reductase suppresses protein aggregation caused by streptomycin

  • Oxidation-reduction proteins increase bacterial resistance against aminoglycosides

ACKNOWLEDGMENTS

We thank NBRP for providing us with the E. coli ORF library. We also thank Robert A. LaRossa (Dupont), Patricia J. Kiley (University of Wisconsin) and Christian Schlieker (Yale) for insightful discussion on this project, and Terence Wu for technical support. This work was supported by grant GM022854 from the National Institute of General Medical Sciences to DS. JL was a Brown-Coxe Postdoctoral Fellow, and CC had support from the Beckman Scholars Program of the Arnold and Mabel Beckman Foundation.

Footnotes

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The authors declare no conflict of interest.

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