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Proteomic analysis of the copper resistance of Streptococcus pneumoniae† Zhong Guo, Junlong Han, Xiao-Yan Yang, Kun Cao, Ke He, Gaofei Du, Guandi Zeng, Liang Zhang, Guangchuang Yu, Zhenghua Sun, Qing-Yu He* and Xuesong Sun* Streptococcus pneumoniae is a Gram-positive bacterial pathogen causing a variety of diseases, including otitis media, bacteraemia and meningitis. Although copper is an essential trace metal for bacterial growth, high intracellular levels of free-copper are toxic. Copper resistance has emerged as an important virulence determinant of microbial pathogens. In this study, we determined the minimum inhibition concentration of copper for the growth inhibition of S. pneumoniae. Two-dimensional-electrophoresis coupled with mass spectrometry was applied to identify proteins involved in copper resistance of S. pneumoniae. In total, forty-four proteins with more than 1.5-fold alteration in expression (p o 0.05) were identified.
Received 20th October 2014, Accepted 13th January 2015 DOI: 10.1039/c4mt00276h
Quantitative reverse transcription PCR was used to confirm the proteomic results. Bioinformatics analysis showed that the differentially expressed proteins were mainly involved in the cell wall biosynthesis, protein biosynthesis, purine biosynthesis, pyrimidine biosynthesis, primary metabolic process, and the nitrogen compound metabolic process. Many up-regulated proteins in response to the copper treatment directly or indirectly participated in the cell wall biosynthesis, indicating that the cell wall is a critical determinant in
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copper resistance of S. pneumoniae.
Introduction Streptococcus pneumoniae (S. pneumoniae) is a Gram-positive pathogenic bacterium, causing bacteraemia, bacterial meningitis and otitis media.1–4 To infect a wide range of the host cells, S. pneumoniae must be able to adapt to the change in the environmental conditions, including the various concentrations of metal ions.5 Copper is considered as an essential trace element for all organisms from bacterial cells to humans,6 which functions as a catalytic cofactor in the electron transfer reaction, aerobic respiration, photosynthesis, oxidative stress resistance and metabolic enzymes,7 but it is toxic at high concentrations. The Cu(II)/ Cu(I) redox couple results in a Fenton-like Haber–Weiss reaction: Cu(II) is reduced by a superoxide radical O2 to Cu(I), then Cu(I) is oxidized by H2O2 to Cu(II) and OH; in the meantime, the toxic ROS are generated in this process.8–10 Copper resistance in S. pneumoniae is mainly mediated by a single operon encoding a copper-dependent repressor protein (CopY),11 a copper transporting ATPase (CopA)12 and a functionunknown protein (CupA). The S. pneumoniae cop operon is induced Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, Institute of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China. E-mail: [email protected], [email protected]; Fax: +86-20-85227039; Tel: +86-20-85227039 † Electronic supplementary information (ESI) available. See DOI: 10.1039/ c4mt00276h
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by copper in vitro and is autoregulated by the CopY.1 The third gene is a non-conservative gene encoding a 123-amino acid protein, CupA, which may bind copper and play a role in copper resistance,1,12 with its molecular function being unknown. In addition to the above information, the detailed mechanism of copper resistance in S. pneumoniae is far from clear. To help understanding the molecular mechanism of copper resistance in S. pneumoniae, we performed a proteomics study to identify the differentially expressed proteins upon excessive copper treatment on the bacterium. Quantitative reverse transcription PCR (qRT-PCR) was carried out to confirm the proteomic alterations. Bioinformatics analysis showed the functional categorizations and metabolic processes of the identified proteins. This work provides informative clues for further investigations of the mechanism of copper resistance in S. pneumoniae.
Materials and methods 2.1
Bacterial strains and growth conditions
The S. pneumoniae D39 was routinely cultured in Todd-Hewitt broth supplemented with 0.5% yeast extract (THY) in the presence or absence of CuSO4 with various concentrations at 37 1C and 5% CO2. The OD600 were determined at different time to measure the MIC value of copper. Cells at OD600 of B0.6 (an exponential phase) were harvested by centrifugation at 5000 g for 10 min at
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4 1C and washed thrice with prechilled phosphate-buffered saline (PBS) for a proteomic study.
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2.2
Determination of intracellular copper content
The intracellular copper content was determined by inductively coupled plasma mass spectrometry (ICP-MS, Thermo Scientific) analysis as previously described.13 5 108 CFU of bacteria at OD600 of B0.6 were harvested by centrifugation at 3000g for 10 min and washed five times with PBS. The dry cell mass was resuspended with 1.5 mL of 14% HNO3, and boiled at 95 1C for 20 min. The samples were then centrifuged at 13 200g for 30 min, and the supernatant was collected for ICP-MS analysis. Three independent biological experiments were repeated. 2.3
Isolation of whole proteins
Pelleted cells were resuspended in an appropriate volume of the lysis buffer [7 M urea, 2 M thio-urea and 4% CHAPS, 40 mM Tris-base with 40 mM DTT, 1 mM PMSF, 2% IPG buffer (pH 4–7), a protease inhibitor and a nuclease mix], freeze–thawed three cycles, and then sonicated with 20% power, 5 s on/5 s off for 10 min on ice. The lysate was centrifuged at 13 200 g for 30 min at 4 1C. The resulting supernatants were stored in aliquots at 80 1C until further use. Protein concentrations were determined using Bradford assay. 2.4
Two-dimensional gel electrophoresis (2-DE)
2-DE was performed in accordance with our previously described protocol.14 Briefly, 100 mg of D39 whole cell proteins were mixed into 250 mL rehydration solution containing 7 M urea, 2 M thio-urea, 2% CHAPS, 20 mM DTT and 0.5% IPG buffer. Subsequently, the immobilized pH gradient strips were equilibrated for 15 min in reducing buffer, followed by equilibration for 15 min in alkylation buffer, and then transferred onto 12.5% SDS-PAGE. Gels were stained with silver using a previously described protocol compatible with mass spectrum analysis.15
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2.6
Protein categorization and network construction
The information on protein functions and their biological processes was analyzed by using a bioconductor (http://www.bioconductor.org/) package, clusterProfiler (v1.12.0),17 for statistical analysis of Gene Ontology (GO), which was operated by R (v3.0.2), based on the GO annotation of S. pneumoniae D39 according to their molecular function and the biological process.18 The GO annotation was obtained by querying the BioMart database (http://bacteria. ensembl.org/index.html). The interaction networks, which were inferred from STRING webserver,19 include direct interactions and functional associations. Functional associations were derived from the genomic context (homology and fusion events), co-expression, text-mining and biological knowledge (e.g. GO annotation). 2.7
RNA extraction and qRT-PCR
Total RNA was extracted from S. pneumoniae D39 using TRIzol (Invitrogen Life Technologies) according to the manufacturer’s protocol. The RNA concentration was determined using an NanoDrop 2000 spectrophotometer (Thermo Scientific) and the quality was assessed on SYBR Safe DNA gel stain (Invitrogen Life Technologies). Reverse transcription reactions were carried out by using the ThermoScript RT-PCR system (Invitrogen Life Technologies). The 20 mL RT-PCR reaction mixture contained 1 mg extracted total RNA, 4 mL 5 iscript reaction mix, 1 mL iscript reverse transcriptase, and nuclease-free ddH2O. qRT-PCRs were run using the Miniopticon Real-time PCR detection system (Bio-Rad) and reactions were carried out by using the EvaGreen Dye (Bio-Rad). The PCR reaction mixture of 20 mL contained 1 mL sample cDNA, 1 mL (500 nM) forward and reverse primer, respectively, 10 mL Eva mix, and 6 mL nuclease-free ddH2O. PCR specificity was verified by melt-curve analysis of products. The cycle threshold (Ct) value was measured, and the relative quantification of specific genes expression was determined using the 2DDCt method, with the 16S rRNA as the reference gene. The primer sequences used for qRT-PCR are shown in Table 1.
Results and discussion 2.5
In-gel digestion and protein identification
2-DE profiles were analyzed using Progenesis software, and differentially expressed protein spots with 41.5-fold change from three repeated experiments were selected. In-gel digestion of proteins was carried out using our previously described protocol.16 Peptides dissolved in 1.2 mL solution (50% ACN containing 0.1% TFA) were spotted on the MALDI-TOF target plates, and deposited with 0.5 mL matrix solution (5 mg mL1 CHCA, 70% ACN, and 0.1% TFA). Mass spectra of peptides were acquired on an ABI 4800 plus MALDI TOF/TOF mass spectrometer (Applied Biosystems, Foster city, CA.). Proteins were identified by using MASCOT 2.2.04 (Matrix Science, Boston, MA, USA) and searching against the NCBInr database of S. pneumoniae D39, the following parameters were used: fixed modification carbamidomethyl, variable modification oxidation, a maximum of two missed cleavages, MASCOT protein scores of greater than 65 were considered statistically significant ( p o 0.05). The false discovery rate (FDR) was below 1%.
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3.1
Excessive copper suppressed S. pneumoniae growth
To determine the minimum inhibition concentration (MIC) of copper, a series of concentrations of CuSO4 were used to treat S. pneumoniae D39. We found that the bacterial growth was inhibited
Table 1
The primer sequences used for qRT-PCR experiments
Primer
Sequence (5 0 –3 0 )
16SrRNA-F 16SrRNA-R glmM-F glmM-R GlnQ-F GlnQ-R pepQ-F pepQ-R lysS-F lysS-R tyrS-F tyrS-R
5 0 -CTGCGTTGTATTAGCTAGTTGGTG-3 0 5 0 -TCCGTCCATTGCCGAAGATTC-3 0 5 0 -TCCGTGGAGAAGCTAACCTA-3 0 5 0 -AATCCCTACTGAAAGGAGACC-3 0 5 0 -GTGAAAGAAGGCTTGGTTGT-3 0 5 0 -ATAAATGGCGAGGATAATGG-3 0 5 0 -AGTGGGCTATGTCGATTCTG-3 0 5 0 -ATGCGTTGGATACGAGGAGT-3 0 5 0 -GCTGTATCTCCACTCGCTAA-3 0 5 0 -CTGTCGCTTCATCATCACCA-3 0 5 0 -ACGGAGAAGAAGCCTACAAA-3 0 5 0 -GAGACGAGCAGTTCCACGAT-3 0
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cultured in THY and in THY plus 1.5 mM CuSO4 (Fig. 2). Forty-four proteins were differentially expressed between the untreated and copper-treated groups with more than 1.5-fold change ( p o 0.05). Nine proteins were down-regulated upon addition of CuSO4 while 35 proteins were up-regulated. The detailed information on the identified proteins is shown in Table 2 and ESI,† Table S1. MASCOT searching showed that four spots corresponded to the same protein possibly due to protein modifications or fragmentation, thus the number of unique proteins was 40. As compared with the untreated group, a large number of proteins in copper-treated bacteria exhibited obvious up-regulation (Table 2), implying that excessive intracellular copper may result in a high rate of the biosynthetic process and the cellular metabolic process. 3.3 Fig. 1 The effect of copper with different concentrations on the growth of S. pneumoniae D39. The OD600nm of D39 were determined for statistical analysis.
with the increasing concentrations of copper (Fig. 1). The MIC for S. pneumoniae D39 was determined to be 3.0 mM, close to the MIC values of Cu for Geobacillus thermoleovorans (1.37 mM), Geobacillus toebii (1.918 mM),20 Escherichia coli (1.0 mM),21 and Bacillus EB4 (2.5 mM),22 implying that most Gram-positive and Gram-negative bacteria have similar copper resistance ability. Thereafter, a sub-MIC concentration of 1.5 mM was used in the subsequent cell cultures. To find out whether the growth inhibition was induced by excessive intracellular copper, the copper concentration in cells was determined by ICP-MS. As shown in Table 3, the copper concentration in the copper-treated bacterium was almost 100 times higher than that in the untreated bacterium. Therefore, the high abundance of the intracellular copper was toxic to S. pneumoniae and can suppress the bacterial growth. 3.2 A large number of proteins were up-regulated upon copper treament Using the gel image analysis software, Progenesis, we compared the 2DE maps of whole cell proteins extracted from S. pneumoniae D39
Validation of differentially expressed proteins by qRT-PCR
To verify the reliability of the proteomic data, five differentially expressed proteins, GlmM, glutamine transport ATP-binding protein (GlnQ), proline dipeptidase PepQ, LysS, and TyrS, were randomly selected and subjected to qRT-PCR (Fig. 3). The mRNA levels of glmM, glnQ, and pepQ were significantly down-regulated in comparison with the untreated group while lysS and tyrS were up-regulated. These change in tendencies of the mRNA expression level of the five genes were consistent with that of the protein level. 3.4
Cell wall played a vital role in copper resistance
The bioinformatics analysis showed that these diffrentially expressed proteins identified in this study belong to over 10 functional clusters including small molecule binding, organic cyclic compound binding, ion binding, transferase activity and hydrolase activity (Fig. 4). Further investigation of biological processes showed that these proteins are mainly related to the cell wall biosynthesis, primary metabolic process, cellular metabolic process and nitrogen compound metabolic process, indicating that S. pneumoniae executes resistance to copper toxicity by activating several biological pathways (Fig. 5). Moreover, string analysis showed that most differently expressed
Fig. 2 Comparison of 2-DE maps of whole cell lysate (100 mg) from S. pneumoniae cultured in THY (A) and THY plus 1.5 mM Cu2+ (B). Arrows indicate protein spots with differential expression.
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Table 2
Metallomics Differentially expressed proteins identified by MALDI-TOF MS
No. Protein name
Accession no.
Gene name
Protein MW
Protein Protein score Total ion PI C. I. (%) C. I. (%) F.D.
Small molecule binding 1 Tyrosyl-tRNA synthetase 5 Aromatic amino acid aminotransferase 7 Lactate oxidase 8 Rrecombinase A 11 Acetyl-CoA carboxylase biotin carboxylase subunit 14 GTP-binding protein EngA 20 Tyrosyl-tRNA synthetase 21 UDP-N-acetylmuramate-L-alanine ligase 27 Thiamine biosynthesis protein Thi 28 Capsular polysaccharide biosynthesis protein, putative 32 Sugar ABC transporter, ATP-binding protein 37 ATP-dependent Clp protease ATP-binding subunit ClpE 38 Ribonucleotide-diphosphate reductase subunit alpha 39 ATP-dependent Clp protease ATP-binding subunit ClpE 46 Amino acid ABC transporter, ATP-binding protein
gi|116516055 gi|116516139 gi|116517149 gi|116516275 gi|116515928 gi|116515879 gi|116516055 gi|116515384 gi|116516659 gi|116516120 gi|116515854 gi|116516310 gi|116516073 gi|116516310 gi|116516709
tyrS araT lctO recA accC engA tyrS murC thiI SPD1619 SPD0740 clpE nrdE clpE SPD1289
47451.2 43259.4 41577.1 41923.9 49862.3 49051.3 47451.2 49842.7 45232.3 45833.4 55029.2 84016.3 81825.9 84016.3 27350.4
5.46 5.16 5.67 5.13 5.16 5.27 5.46 5.43 5.37 5.33 5.47 5.48 5.32 5.48 6.01
100 100 100 100 100 100 97.102 100 100 100 100 100 100 100 100
99.995 97.43 99.998 100 74.009 100
2.2 1.7 1.7 2.0 1.8 2.4 2.5 2.4 1.7 2.5 2.9 2.6 3.6 2.2 2.4
Ion binding 6 Inositol-5-monophosphate dehydrogenase gi|116515965 guaB 10 UDP-N-acetylglucosamine pyrophosphorylase gi|116516172 glmU 13 Threonyl-tRNA synthetase gi|116515338 thrS 24 Metallo-beta-lactamase domain-containing protein gi|116516160 SPD0130 25 Adenylosuccinate synthetase gi|116515772 purA 34 Lysyl-tRNA synthetase gi|116517090 lysS 40 Phosphoglucomutase/phosphomannomutase family protein gi|116516422 glmM 42 Ribose-phosphate pyrophosphokinase gi|116517035 prs2 43 Putative manganese-dependent inorganic gi|116516825 ppaC 45 Proline dipeptidase PepQ gi|116516123 pepQ
52525.9 49454.4 74831.5 61195 47711.6 56702.9 48092.6 35331.5 33457.9 40347.3
5.18 5.3 5.26 5.67 5.49 5.32 4.65 5.93 4.57 4.73
100 100 100 100 100 100 100 100 100 100
100 100 97.519 100 100 100 100 100 100 100
1.6 2.3 1.7 1.9 2.6 2.5 1.8 2.0 1.2 1.2
38188.1 37020.2 48936.7 50281.2 38166.4 45922.9 52923.9 52923.9 30223.4 55087.5 44075.1 55087.5 35421.6 52160.3
5.26 5.47 5.43 5.09 5.46 5.38 5.14 5.14 4.63 5.51 5.44 5.51 5.15 4.82
100 100 100 100 100 99.336 100 100 99.618 100 100 100 100 100
100 100 100 100 100 99.732 100 99.997 97.652 99.97 100 97.594 100 100
2.6 1.8 2.1 1.9 2.7 2.5 1.7 2.4 1.5 3.9 1.6 2.6 2.3 1.6
gi|116515581 pyrG 59504.5 5.45 gi|116516619 SPD0378 28831.2 5.84 gi|116516523 gapN 51101.9 5.2
100 100 100
100 100 100
2.6 3.0 2.2
gi|116516084 SPD0533 61128 5.38 gi|116516293 rpoA 34242.8 4.64
100 100
100 100
3.1 1.2
Others 2 Hypothetical protein SPD_0547 3 Catabolite control protein A 4 Glutamate dehydrogenase 9 Aminopeptidase C 12 Glutamyl aminopeptidase PepA 15 UDP-N-acetylglucosamine 1-carboxyvinyltransferase 16 Pneumolysin 17 Pneumolysin 18 Cell division protein DivIVA 19 Hypothetical protein SPD_0310 22 3-Oxoacyl-(acyl carrier protein) synthase II 23 Hypothetical protein SPD_0310 26 PTS system, mannose-specific IIAB components 29 Cof family protein/peptidyl-prolyl cis–trans isomerase,cyclophilin type 31 CTP synthetase 33 Enoyl-CoA hydratase 36 Glyceraldehyde-3-phosphate dehydrogenase, NADP-dependent 41 Metallo-beta-lactamase superfamily protein 44 DNA-directed RNA polymerase subunit alpha
gi|116516393 gi|116517109 gi|116516965 gi|116516913 gi|116516201 gi|116516843 gi|116515376 gi|116515376 gi|116515933 gi|116516184 gi|116516059 gi|116516184 gi|116515792 gi|116515578
Table 3 Intracellular copper levels in S. pneumoniae untreated and treated with 1.5 mM CuSO4 as determined by ICP-MS
ng (Cu per mg protein)
Control
Cu-treated
0.016 0.002
1.492 0.180
proteins stimulated by copper treatment form a large intact interaction network (Fig. 5B). In this functional association network, many proteins involved in aminoacyl-tRNA biosynthesis such as tyrosyl-tRNA synthetase (TyrS), threonyl-tRNA synthetase (ThrS), and lysyl-tRNA synthetase (LysS) that were up-regulated under excessive copper treatment indirectly interact with each other
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SPD0547 ccpA gdhA pepC pepA murA-2 ply ply divIVA SPD0310 fabF SPD0310 manL SPD1367
100 100 100 99.525 100 100 100
due to the functional association in tRNA synthesis, indicating that the bacterium improves many biological pathways by activating the translational level (Fig. 4B). It was worth noting that three proteins, glucosamine-1-phosphate acetyltransferase (GlmU), phosphomannomutase family protein (GlmM), and UDP-Nacetylmuramate-L-alanine ligase (MurC), interact with each other and form a close sub-network because they are jointly involved in peptidoglycan biosynthesis, implying that the cell wall may play a key role in the copper resistance. The bacterial cell wall is the principal stress-bearing element and peptidoglycan as a main component of the bacterial cell wall is important for bacteria to maintain the cell shape and
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Fig. 3 The relative expression of S. pneumonia D39 genes under copper treatment. The expressions of glmM, glnQ, pepQ, lysS, and tyrS were normalized with 16S rRNA. The mRNA level of glmM, glnQ, and pepQ were significantly down-regulated in comparison with the untreated group while lysS and tyrS were up-regulated.
structural integrity under conditions of osmotic stress and turgor stress.23,24 In this study, we found that three proteins playing chief roles in peptidoglycan biosynthesis including MurA,25 MurC, GlmU26 were up-regulated upon an excess of copper treatment. MurA is the dual-substrate enzyme catalyzing the reaction of phosphoenolpyruvate (PEP) and UDP-GlcNAc to yield enolpyruvated UDP-GlcNAc-EP while MurC is another enzyme synthesizing an essential intermediate in the cell wall peptidoglycan pathway.27 Another enzyme, GlmU, catalyzes a two-step reaction yielding UDP-N-acetylglucosamine (UDP-GlcNAc), which is one of the fundamental cytoplasmic precursors of the bacterial cell wall. These enzymes in the cell wall biosynthesis pathway have been used as drug targets because of their functional importance but absence in animals.28–30 Interestingly, those aminoacylated-transfer RNAs, such as ThrS, TyrS, and LysS, are not only involved in protein biosynthesis,31 but also in crosslinking with peptidoglycan and/or phospholipid modification.23 Facing the copper toxicity, S. pneumoniae may improve the expression levels of proteins directly or indirectly participated in cell wall biosynthesis and thereby increase the thickness of the cell wall, as a self-defense mechanism. Previous studies have reported several bacterial defense mechanisms against copper toxicity.32,33 Copper-transporting P-type copper export ATPases (such as Cop A) are the dominant copper homeostasis components across Gram-negative and Grampositive bacteria. Many bacteria utilize resistance-nodulation cell division (RND)-type efflux systems (for example, CusCFBA) and multicopper oxidases (MCOs, such as CueO) to cope with excess copper.7,32–36 Unexpectedly, these reported key proteins were not identified in our proteomic analysis, maybe due to their low abundance or high hydrophobicity. In addition to the above two mechanisms, a transcriptomic analysis of Staphylococcus aureus suggested other mechanisms for adapting to high levels of environmental copper as follows: (i) increased oxidative stress
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Fig. 4 The molecular functions classified by clusterProfiler (A) and protein– protein interaction networks inferred by STRING (B) of differentially expressed proteins. (A) Showed that these differentially expressed proteins were grouped as small molecule binding, organic cyclic compound binding, ion binding, transferase activity and hydrolase activity.
resistance; (ii) expression of the misfolded protein response; and (iii) repression of a number of transporters and global regulators such as Agr and Sae.37 Similarly, our study also found that some proteins involved in protein misfolding (such as ATP-dependent Clp protease, ClpE)38 and stress response such as recombinase A (RecA), which plays a central role in DNA repair and regulation of the SOS response.39 Another Cu-response protein Lactate Oxidase (LctO) found in Lactococcus lactis40 was also detected in this work. More importantly, our results suggest that the cell wall plays a vital role in copper resistance, providing a novel clue
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biosynthesis. Thus, bacteria can effectively protect itself from excessive copper disruption.
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Conclusion This study performs proteomic research to find out proteins involved in the copper resistance process in S. pneumoniae. The classification of the differentially expressed proteins induced by excessive copper indicates that bacteria can improve metabolic ability of many biological pathways under copper stress. The most important finding is that S. pneumoniae may increase cell wall biosynthesis to combat copper toxicity; this provides novel information for the deep investigation of the resistance mechanism against toxic metal ions in bacteria.
Acknowledgements This work was supported by the National Natural Science Foundation of China (21271086, to Q.-Y.H.; 31000373, to X.S.), Guangdong Natural Science Research Grant (32213027, to Q.-Y.H.; S2012010008685 to X.S.), the Fundamental Research Funds for the Central Universities (21610101 to Q.-Y.H.; 21611201, to X.S.), the Pearl River Rising Star of Science and Technology of Guangzhou City (2011J2200003, to X.S.) and National Program on Key Basic Research Project (973 Program, 2011CB910701, to X.S.)
References
Fig. 5 The biological processes of differentially expressed proteins classified and visualized by clusterProfiler according to the Gene Ontology (GO) database. (A) and (B) showed that these proteins mainly related to the cell wall biosynthesis, biosynthetic process, primary metabolic process, cellular metabolic process and nitrogen compound metabolic process.
for the deep understanding of the bacterial defense mechanism against toxic copper.
3.5
Cu-binding motifs in differentially expressed proteins
A previously published paper by our group has investigated the Cu-binding motifs in S. pneumoniae and proved their metal binding ability.41 Using the similar method, we checked the Cu-binding motifs in the sequences of the differentially expressed proteins after copper treatment. Interestingly, we found that most identified proteins possess Cu-binding motifs: H(X)nH, H(X)nM, M(X)nH, H(X)nC, and C(X)nH (n = 0–12) and over 90% of the proteins contain more than two motifs (ESI,† Table S2). Especially, MurA, MurC, GlmU, ThrS, and TyrS related to peptidoglycan biosynthesis contain more than ten motifs.42 This result implicates that excessive copper may function as co-enzyme factors to improve the activity of these enzymes and thus promote cell wall
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28 29 30 31 32 33 34 35
36 37 38 39 40 41 42
C. A. Smith, J. Mol. Biol., 2006, 362, 640–655. L. L. Silver, Curr. Opin. Microbiol., 2003, 6, 431–438. L. L. Silver, Biochem. Pharmacol., 2006, 71, 996–1005. H. Putzer, C. Condon, D. Brechemier-Baey, R. Brito and M. Grunberg-Manago, Nucleic Acids Res., 2002, 30, 3026–3033. C. Rademacher and B. Masepohl, Microbiology, 2012, 158, 2451–2464. M. I. Samanovic, C. Ding, D. J. Thiele and K. H. Darwin, Cell Host Microbe, 2012, 11, 106–115. N. A. Veldhuis, A. P. Gaeth, R. B. Pearson, K. Gabriel and J. Camakaris, BioMetals, 2009, 22, 177–190. F. Long, C. C. Su, M. T. Zimmermann, S. E. Boyken, K. R. Rajashankar, R. L. Jernigan and E. W. Yu, Nature, 2010, 467, 484–488. F. W. Outten, D. L. Huffman, J. A. Hale and T. V. O’Halloran, J. Biol. Chem., 2001, 276, 30670–30677. J. Baker, S. Sitthisak, M. Sengupta, M. Johnson, R. K. Jayaswal and J. A. Morrissey, Appl. Environ. Microbiol., 2010, 76, 150–160. D. Frees, A. Chastanet, S. Qazi, K. Sorensen, P. Hill, T. Msadek and H. Ingmer, Mol. Microbiol., 2004, 54, 1445–1462. V. Sharma, Y. Sakai, K. A. Smythe and Y. Yokobayashi, Biochem. Biophys. Res. Commun., 2013, 430, 256–259. O. Barre, F. Mourlane and M. Solioz, J. Bacteriol., 2007, 189, 5947–5954. X. Sun, G. Yu, Q. Xu, N. Li, C. Xiao, X. Yin, K. Cao, J. Han and Q. Y. He, Metallomics, 2013, 5, 928–935. X. Sun, C. L. Xiao, R. Ge, X. Yin, H. Li, N. Li, X. Yang, Y. Zhu, X. He and Q. Y. He, Proteomics, 2011, 11, 3288–3298.
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Cite this: DOI: 10.1039/c4mt00276h
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Proteomic analysis of the copper resistance of Streptococcus pneumoniae† Zhong Guo, Junlong Han, Xiao-Yan Yang, Kun Cao, Ke He, Gaofei Du, Guandi Zeng, Liang Zhang, Guangchuang Yu, Zhenghua Sun, Qing-Yu He* and Xuesong Sun* Streptococcus pneumoniae is a Gram-positive bacterial pathogen causing a variety of diseases, including otitis media, bacteraemia and meningitis. Although copper is an essential trace metal for bacterial growth, high intracellular levels of free-copper are toxic. Copper resistance has emerged as an important virulence determinant of microbial pathogens. In this study, we determined the minimum inhibition concentration of copper for the growth inhibition of S. pneumoniae. Two-dimensional-electrophoresis coupled with mass spectrometry was applied to identify proteins involved in copper resistance of S. pneumoniae. In total, forty-four proteins with more than 1.5-fold alteration in expression (p o 0.05) were identified.
Received 20th October 2014, Accepted 13th January 2015 DOI: 10.1039/c4mt00276h
Quantitative reverse transcription PCR was used to confirm the proteomic results. Bioinformatics analysis showed that the differentially expressed proteins were mainly involved in the cell wall biosynthesis, protein biosynthesis, purine biosynthesis, pyrimidine biosynthesis, primary metabolic process, and the nitrogen compound metabolic process. Many up-regulated proteins in response to the copper treatment directly or indirectly participated in the cell wall biosynthesis, indicating that the cell wall is a critical determinant in
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copper resistance of S. pneumoniae.
Introduction Streptococcus pneumoniae (S. pneumoniae) is a Gram-positive pathogenic bacterium, causing bacteraemia, bacterial meningitis and otitis media.1–4 To infect a wide range of the host cells, S. pneumoniae must be able to adapt to the change in the environmental conditions, including the various concentrations of metal ions.5 Copper is considered as an essential trace element for all organisms from bacterial cells to humans,6 which functions as a catalytic cofactor in the electron transfer reaction, aerobic respiration, photosynthesis, oxidative stress resistance and metabolic enzymes,7 but it is toxic at high concentrations. The Cu(II)/ Cu(I) redox couple results in a Fenton-like Haber–Weiss reaction: Cu(II) is reduced by a superoxide radical O2 to Cu(I), then Cu(I) is oxidized by H2O2 to Cu(II) and OH; in the meantime, the toxic ROS are generated in this process.8–10 Copper resistance in S. pneumoniae is mainly mediated by a single operon encoding a copper-dependent repressor protein (CopY),11 a copper transporting ATPase (CopA)12 and a functionunknown protein (CupA). The S. pneumoniae cop operon is induced Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, Institute of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China. E-mail: [email protected], [email protected]; Fax: +86-20-85227039; Tel: +86-20-85227039 † Electronic supplementary information (ESI) available. See DOI: 10.1039/ c4mt00276h
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by copper in vitro and is autoregulated by the CopY.1 The third gene is a non-conservative gene encoding a 123-amino acid protein, CupA, which may bind copper and play a role in copper resistance,1,12 with its molecular function being unknown. In addition to the above information, the detailed mechanism of copper resistance in S. pneumoniae is far from clear. To help understanding the molecular mechanism of copper resistance in S. pneumoniae, we performed a proteomics study to identify the differentially expressed proteins upon excessive copper treatment on the bacterium. Quantitative reverse transcription PCR (qRT-PCR) was carried out to confirm the proteomic alterations. Bioinformatics analysis showed the functional categorizations and metabolic processes of the identified proteins. This work provides informative clues for further investigations of the mechanism of copper resistance in S. pneumoniae.
Materials and methods 2.1
Bacterial strains and growth conditions
The S. pneumoniae D39 was routinely cultured in Todd-Hewitt broth supplemented with 0.5% yeast extract (THY) in the presence or absence of CuSO4 with various concentrations at 37 1C and 5% CO2. The OD600 were determined at different time to measure the MIC value of copper. Cells at OD600 of B0.6 (an exponential phase) were harvested by centrifugation at 5000 g for 10 min at
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4 1C and washed thrice with prechilled phosphate-buffered saline (PBS) for a proteomic study.
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2.2
Determination of intracellular copper content
The intracellular copper content was determined by inductively coupled plasma mass spectrometry (ICP-MS, Thermo Scientific) analysis as previously described.13 5 108 CFU of bacteria at OD600 of B0.6 were harvested by centrifugation at 3000g for 10 min and washed five times with PBS. The dry cell mass was resuspended with 1.5 mL of 14% HNO3, and boiled at 95 1C for 20 min. The samples were then centrifuged at 13 200g for 30 min, and the supernatant was collected for ICP-MS analysis. Three independent biological experiments were repeated. 2.3
Isolation of whole proteins
Pelleted cells were resuspended in an appropriate volume of the lysis buffer [7 M urea, 2 M thio-urea and 4% CHAPS, 40 mM Tris-base with 40 mM DTT, 1 mM PMSF, 2% IPG buffer (pH 4–7), a protease inhibitor and a nuclease mix], freeze–thawed three cycles, and then sonicated with 20% power, 5 s on/5 s off for 10 min on ice. The lysate was centrifuged at 13 200 g for 30 min at 4 1C. The resulting supernatants were stored in aliquots at 80 1C until further use. Protein concentrations were determined using Bradford assay. 2.4
Two-dimensional gel electrophoresis (2-DE)
2-DE was performed in accordance with our previously described protocol.14 Briefly, 100 mg of D39 whole cell proteins were mixed into 250 mL rehydration solution containing 7 M urea, 2 M thio-urea, 2% CHAPS, 20 mM DTT and 0.5% IPG buffer. Subsequently, the immobilized pH gradient strips were equilibrated for 15 min in reducing buffer, followed by equilibration for 15 min in alkylation buffer, and then transferred onto 12.5% SDS-PAGE. Gels were stained with silver using a previously described protocol compatible with mass spectrum analysis.15
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2.6
Protein categorization and network construction
The information on protein functions and their biological processes was analyzed by using a bioconductor (http://www.bioconductor.org/) package, clusterProfiler (v1.12.0),17 for statistical analysis of Gene Ontology (GO), which was operated by R (v3.0.2), based on the GO annotation of S. pneumoniae D39 according to their molecular function and the biological process.18 The GO annotation was obtained by querying the BioMart database (http://bacteria. ensembl.org/index.html). The interaction networks, which were inferred from STRING webserver,19 include direct interactions and functional associations. Functional associations were derived from the genomic context (homology and fusion events), co-expression, text-mining and biological knowledge (e.g. GO annotation). 2.7
RNA extraction and qRT-PCR
Total RNA was extracted from S. pneumoniae D39 using TRIzol (Invitrogen Life Technologies) according to the manufacturer’s protocol. The RNA concentration was determined using an NanoDrop 2000 spectrophotometer (Thermo Scientific) and the quality was assessed on SYBR Safe DNA gel stain (Invitrogen Life Technologies). Reverse transcription reactions were carried out by using the ThermoScript RT-PCR system (Invitrogen Life Technologies). The 20 mL RT-PCR reaction mixture contained 1 mg extracted total RNA, 4 mL 5 iscript reaction mix, 1 mL iscript reverse transcriptase, and nuclease-free ddH2O. qRT-PCRs were run using the Miniopticon Real-time PCR detection system (Bio-Rad) and reactions were carried out by using the EvaGreen Dye (Bio-Rad). The PCR reaction mixture of 20 mL contained 1 mL sample cDNA, 1 mL (500 nM) forward and reverse primer, respectively, 10 mL Eva mix, and 6 mL nuclease-free ddH2O. PCR specificity was verified by melt-curve analysis of products. The cycle threshold (Ct) value was measured, and the relative quantification of specific genes expression was determined using the 2DDCt method, with the 16S rRNA as the reference gene. The primer sequences used for qRT-PCR are shown in Table 1.
Results and discussion 2.5
In-gel digestion and protein identification
2-DE profiles were analyzed using Progenesis software, and differentially expressed protein spots with 41.5-fold change from three repeated experiments were selected. In-gel digestion of proteins was carried out using our previously described protocol.16 Peptides dissolved in 1.2 mL solution (50% ACN containing 0.1% TFA) were spotted on the MALDI-TOF target plates, and deposited with 0.5 mL matrix solution (5 mg mL1 CHCA, 70% ACN, and 0.1% TFA). Mass spectra of peptides were acquired on an ABI 4800 plus MALDI TOF/TOF mass spectrometer (Applied Biosystems, Foster city, CA.). Proteins were identified by using MASCOT 2.2.04 (Matrix Science, Boston, MA, USA) and searching against the NCBInr database of S. pneumoniae D39, the following parameters were used: fixed modification carbamidomethyl, variable modification oxidation, a maximum of two missed cleavages, MASCOT protein scores of greater than 65 were considered statistically significant ( p o 0.05). The false discovery rate (FDR) was below 1%.
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3.1
Excessive copper suppressed S. pneumoniae growth
To determine the minimum inhibition concentration (MIC) of copper, a series of concentrations of CuSO4 were used to treat S. pneumoniae D39. We found that the bacterial growth was inhibited
Table 1
The primer sequences used for qRT-PCR experiments
Primer
Sequence (5 0 –3 0 )
16SrRNA-F 16SrRNA-R glmM-F glmM-R GlnQ-F GlnQ-R pepQ-F pepQ-R lysS-F lysS-R tyrS-F tyrS-R
5 0 -CTGCGTTGTATTAGCTAGTTGGTG-3 0 5 0 -TCCGTCCATTGCCGAAGATTC-3 0 5 0 -TCCGTGGAGAAGCTAACCTA-3 0 5 0 -AATCCCTACTGAAAGGAGACC-3 0 5 0 -GTGAAAGAAGGCTTGGTTGT-3 0 5 0 -ATAAATGGCGAGGATAATGG-3 0 5 0 -AGTGGGCTATGTCGATTCTG-3 0 5 0 -ATGCGTTGGATACGAGGAGT-3 0 5 0 -GCTGTATCTCCACTCGCTAA-3 0 5 0 -CTGTCGCTTCATCATCACCA-3 0 5 0 -ACGGAGAAGAAGCCTACAAA-3 0 5 0 -GAGACGAGCAGTTCCACGAT-3 0
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cultured in THY and in THY plus 1.5 mM CuSO4 (Fig. 2). Forty-four proteins were differentially expressed between the untreated and copper-treated groups with more than 1.5-fold change ( p o 0.05). Nine proteins were down-regulated upon addition of CuSO4 while 35 proteins were up-regulated. The detailed information on the identified proteins is shown in Table 2 and ESI,† Table S1. MASCOT searching showed that four spots corresponded to the same protein possibly due to protein modifications or fragmentation, thus the number of unique proteins was 40. As compared with the untreated group, a large number of proteins in copper-treated bacteria exhibited obvious up-regulation (Table 2), implying that excessive intracellular copper may result in a high rate of the biosynthetic process and the cellular metabolic process. 3.3 Fig. 1 The effect of copper with different concentrations on the growth of S. pneumoniae D39. The OD600nm of D39 were determined for statistical analysis.
with the increasing concentrations of copper (Fig. 1). The MIC for S. pneumoniae D39 was determined to be 3.0 mM, close to the MIC values of Cu for Geobacillus thermoleovorans (1.37 mM), Geobacillus toebii (1.918 mM),20 Escherichia coli (1.0 mM),21 and Bacillus EB4 (2.5 mM),22 implying that most Gram-positive and Gram-negative bacteria have similar copper resistance ability. Thereafter, a sub-MIC concentration of 1.5 mM was used in the subsequent cell cultures. To find out whether the growth inhibition was induced by excessive intracellular copper, the copper concentration in cells was determined by ICP-MS. As shown in Table 3, the copper concentration in the copper-treated bacterium was almost 100 times higher than that in the untreated bacterium. Therefore, the high abundance of the intracellular copper was toxic to S. pneumoniae and can suppress the bacterial growth. 3.2 A large number of proteins were up-regulated upon copper treament Using the gel image analysis software, Progenesis, we compared the 2DE maps of whole cell proteins extracted from S. pneumoniae D39
Validation of differentially expressed proteins by qRT-PCR
To verify the reliability of the proteomic data, five differentially expressed proteins, GlmM, glutamine transport ATP-binding protein (GlnQ), proline dipeptidase PepQ, LysS, and TyrS, were randomly selected and subjected to qRT-PCR (Fig. 3). The mRNA levels of glmM, glnQ, and pepQ were significantly down-regulated in comparison with the untreated group while lysS and tyrS were up-regulated. These change in tendencies of the mRNA expression level of the five genes were consistent with that of the protein level. 3.4
Cell wall played a vital role in copper resistance
The bioinformatics analysis showed that these diffrentially expressed proteins identified in this study belong to over 10 functional clusters including small molecule binding, organic cyclic compound binding, ion binding, transferase activity and hydrolase activity (Fig. 4). Further investigation of biological processes showed that these proteins are mainly related to the cell wall biosynthesis, primary metabolic process, cellular metabolic process and nitrogen compound metabolic process, indicating that S. pneumoniae executes resistance to copper toxicity by activating several biological pathways (Fig. 5). Moreover, string analysis showed that most differently expressed
Fig. 2 Comparison of 2-DE maps of whole cell lysate (100 mg) from S. pneumoniae cultured in THY (A) and THY plus 1.5 mM Cu2+ (B). Arrows indicate protein spots with differential expression.
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Table 2
Metallomics Differentially expressed proteins identified by MALDI-TOF MS
No. Protein name
Accession no.
Gene name
Protein MW
Protein Protein score Total ion PI C. I. (%) C. I. (%) F.D.
Small molecule binding 1 Tyrosyl-tRNA synthetase 5 Aromatic amino acid aminotransferase 7 Lactate oxidase 8 Rrecombinase A 11 Acetyl-CoA carboxylase biotin carboxylase subunit 14 GTP-binding protein EngA 20 Tyrosyl-tRNA synthetase 21 UDP-N-acetylmuramate-L-alanine ligase 27 Thiamine biosynthesis protein Thi 28 Capsular polysaccharide biosynthesis protein, putative 32 Sugar ABC transporter, ATP-binding protein 37 ATP-dependent Clp protease ATP-binding subunit ClpE 38 Ribonucleotide-diphosphate reductase subunit alpha 39 ATP-dependent Clp protease ATP-binding subunit ClpE 46 Amino acid ABC transporter, ATP-binding protein
gi|116516055 gi|116516139 gi|116517149 gi|116516275 gi|116515928 gi|116515879 gi|116516055 gi|116515384 gi|116516659 gi|116516120 gi|116515854 gi|116516310 gi|116516073 gi|116516310 gi|116516709
tyrS araT lctO recA accC engA tyrS murC thiI SPD1619 SPD0740 clpE nrdE clpE SPD1289
47451.2 43259.4 41577.1 41923.9 49862.3 49051.3 47451.2 49842.7 45232.3 45833.4 55029.2 84016.3 81825.9 84016.3 27350.4
5.46 5.16 5.67 5.13 5.16 5.27 5.46 5.43 5.37 5.33 5.47 5.48 5.32 5.48 6.01
100 100 100 100 100 100 97.102 100 100 100 100 100 100 100 100
99.995 97.43 99.998 100 74.009 100
2.2 1.7 1.7 2.0 1.8 2.4 2.5 2.4 1.7 2.5 2.9 2.6 3.6 2.2 2.4
Ion binding 6 Inositol-5-monophosphate dehydrogenase gi|116515965 guaB 10 UDP-N-acetylglucosamine pyrophosphorylase gi|116516172 glmU 13 Threonyl-tRNA synthetase gi|116515338 thrS 24 Metallo-beta-lactamase domain-containing protein gi|116516160 SPD0130 25 Adenylosuccinate synthetase gi|116515772 purA 34 Lysyl-tRNA synthetase gi|116517090 lysS 40 Phosphoglucomutase/phosphomannomutase family protein gi|116516422 glmM 42 Ribose-phosphate pyrophosphokinase gi|116517035 prs2 43 Putative manganese-dependent inorganic gi|116516825 ppaC 45 Proline dipeptidase PepQ gi|116516123 pepQ
52525.9 49454.4 74831.5 61195 47711.6 56702.9 48092.6 35331.5 33457.9 40347.3
5.18 5.3 5.26 5.67 5.49 5.32 4.65 5.93 4.57 4.73
100 100 100 100 100 100 100 100 100 100
100 100 97.519 100 100 100 100 100 100 100
1.6 2.3 1.7 1.9 2.6 2.5 1.8 2.0 1.2 1.2
38188.1 37020.2 48936.7 50281.2 38166.4 45922.9 52923.9 52923.9 30223.4 55087.5 44075.1 55087.5 35421.6 52160.3
5.26 5.47 5.43 5.09 5.46 5.38 5.14 5.14 4.63 5.51 5.44 5.51 5.15 4.82
100 100 100 100 100 99.336 100 100 99.618 100 100 100 100 100
100 100 100 100 100 99.732 100 99.997 97.652 99.97 100 97.594 100 100
2.6 1.8 2.1 1.9 2.7 2.5 1.7 2.4 1.5 3.9 1.6 2.6 2.3 1.6
gi|116515581 pyrG 59504.5 5.45 gi|116516619 SPD0378 28831.2 5.84 gi|116516523 gapN 51101.9 5.2
100 100 100
100 100 100
2.6 3.0 2.2
gi|116516084 SPD0533 61128 5.38 gi|116516293 rpoA 34242.8 4.64
100 100
100 100
3.1 1.2
Others 2 Hypothetical protein SPD_0547 3 Catabolite control protein A 4 Glutamate dehydrogenase 9 Aminopeptidase C 12 Glutamyl aminopeptidase PepA 15 UDP-N-acetylglucosamine 1-carboxyvinyltransferase 16 Pneumolysin 17 Pneumolysin 18 Cell division protein DivIVA 19 Hypothetical protein SPD_0310 22 3-Oxoacyl-(acyl carrier protein) synthase II 23 Hypothetical protein SPD_0310 26 PTS system, mannose-specific IIAB components 29 Cof family protein/peptidyl-prolyl cis–trans isomerase,cyclophilin type 31 CTP synthetase 33 Enoyl-CoA hydratase 36 Glyceraldehyde-3-phosphate dehydrogenase, NADP-dependent 41 Metallo-beta-lactamase superfamily protein 44 DNA-directed RNA polymerase subunit alpha
gi|116516393 gi|116517109 gi|116516965 gi|116516913 gi|116516201 gi|116516843 gi|116515376 gi|116515376 gi|116515933 gi|116516184 gi|116516059 gi|116516184 gi|116515792 gi|116515578
Table 3 Intracellular copper levels in S. pneumoniae untreated and treated with 1.5 mM CuSO4 as determined by ICP-MS
ng (Cu per mg protein)
Control
Cu-treated
0.016 0.002
1.492 0.180
proteins stimulated by copper treatment form a large intact interaction network (Fig. 5B). In this functional association network, many proteins involved in aminoacyl-tRNA biosynthesis such as tyrosyl-tRNA synthetase (TyrS), threonyl-tRNA synthetase (ThrS), and lysyl-tRNA synthetase (LysS) that were up-regulated under excessive copper treatment indirectly interact with each other
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SPD0547 ccpA gdhA pepC pepA murA-2 ply ply divIVA SPD0310 fabF SPD0310 manL SPD1367
100 100 100 99.525 100 100 100
due to the functional association in tRNA synthesis, indicating that the bacterium improves many biological pathways by activating the translational level (Fig. 4B). It was worth noting that three proteins, glucosamine-1-phosphate acetyltransferase (GlmU), phosphomannomutase family protein (GlmM), and UDP-Nacetylmuramate-L-alanine ligase (MurC), interact with each other and form a close sub-network because they are jointly involved in peptidoglycan biosynthesis, implying that the cell wall may play a key role in the copper resistance. The bacterial cell wall is the principal stress-bearing element and peptidoglycan as a main component of the bacterial cell wall is important for bacteria to maintain the cell shape and
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Fig. 3 The relative expression of S. pneumonia D39 genes under copper treatment. The expressions of glmM, glnQ, pepQ, lysS, and tyrS were normalized with 16S rRNA. The mRNA level of glmM, glnQ, and pepQ were significantly down-regulated in comparison with the untreated group while lysS and tyrS were up-regulated.
structural integrity under conditions of osmotic stress and turgor stress.23,24 In this study, we found that three proteins playing chief roles in peptidoglycan biosynthesis including MurA,25 MurC, GlmU26 were up-regulated upon an excess of copper treatment. MurA is the dual-substrate enzyme catalyzing the reaction of phosphoenolpyruvate (PEP) and UDP-GlcNAc to yield enolpyruvated UDP-GlcNAc-EP while MurC is another enzyme synthesizing an essential intermediate in the cell wall peptidoglycan pathway.27 Another enzyme, GlmU, catalyzes a two-step reaction yielding UDP-N-acetylglucosamine (UDP-GlcNAc), which is one of the fundamental cytoplasmic precursors of the bacterial cell wall. These enzymes in the cell wall biosynthesis pathway have been used as drug targets because of their functional importance but absence in animals.28–30 Interestingly, those aminoacylated-transfer RNAs, such as ThrS, TyrS, and LysS, are not only involved in protein biosynthesis,31 but also in crosslinking with peptidoglycan and/or phospholipid modification.23 Facing the copper toxicity, S. pneumoniae may improve the expression levels of proteins directly or indirectly participated in cell wall biosynthesis and thereby increase the thickness of the cell wall, as a self-defense mechanism. Previous studies have reported several bacterial defense mechanisms against copper toxicity.32,33 Copper-transporting P-type copper export ATPases (such as Cop A) are the dominant copper homeostasis components across Gram-negative and Grampositive bacteria. Many bacteria utilize resistance-nodulation cell division (RND)-type efflux systems (for example, CusCFBA) and multicopper oxidases (MCOs, such as CueO) to cope with excess copper.7,32–36 Unexpectedly, these reported key proteins were not identified in our proteomic analysis, maybe due to their low abundance or high hydrophobicity. In addition to the above two mechanisms, a transcriptomic analysis of Staphylococcus aureus suggested other mechanisms for adapting to high levels of environmental copper as follows: (i) increased oxidative stress
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Fig. 4 The molecular functions classified by clusterProfiler (A) and protein– protein interaction networks inferred by STRING (B) of differentially expressed proteins. (A) Showed that these differentially expressed proteins were grouped as small molecule binding, organic cyclic compound binding, ion binding, transferase activity and hydrolase activity.
resistance; (ii) expression of the misfolded protein response; and (iii) repression of a number of transporters and global regulators such as Agr and Sae.37 Similarly, our study also found that some proteins involved in protein misfolding (such as ATP-dependent Clp protease, ClpE)38 and stress response such as recombinase A (RecA), which plays a central role in DNA repair and regulation of the SOS response.39 Another Cu-response protein Lactate Oxidase (LctO) found in Lactococcus lactis40 was also detected in this work. More importantly, our results suggest that the cell wall plays a vital role in copper resistance, providing a novel clue
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biosynthesis. Thus, bacteria can effectively protect itself from excessive copper disruption.
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Conclusion This study performs proteomic research to find out proteins involved in the copper resistance process in S. pneumoniae. The classification of the differentially expressed proteins induced by excessive copper indicates that bacteria can improve metabolic ability of many biological pathways under copper stress. The most important finding is that S. pneumoniae may increase cell wall biosynthesis to combat copper toxicity; this provides novel information for the deep investigation of the resistance mechanism against toxic metal ions in bacteria.
Acknowledgements This work was supported by the National Natural Science Foundation of China (21271086, to Q.-Y.H.; 31000373, to X.S.), Guangdong Natural Science Research Grant (32213027, to Q.-Y.H.; S2012010008685 to X.S.), the Fundamental Research Funds for the Central Universities (21610101 to Q.-Y.H.; 21611201, to X.S.), the Pearl River Rising Star of Science and Technology of Guangzhou City (2011J2200003, to X.S.) and National Program on Key Basic Research Project (973 Program, 2011CB910701, to X.S.)
References
Fig. 5 The biological processes of differentially expressed proteins classified and visualized by clusterProfiler according to the Gene Ontology (GO) database. (A) and (B) showed that these proteins mainly related to the cell wall biosynthesis, biosynthetic process, primary metabolic process, cellular metabolic process and nitrogen compound metabolic process.
for the deep understanding of the bacterial defense mechanism against toxic copper.
3.5
Cu-binding motifs in differentially expressed proteins
A previously published paper by our group has investigated the Cu-binding motifs in S. pneumoniae and proved their metal binding ability.41 Using the similar method, we checked the Cu-binding motifs in the sequences of the differentially expressed proteins after copper treatment. Interestingly, we found that most identified proteins possess Cu-binding motifs: H(X)nH, H(X)nM, M(X)nH, H(X)nC, and C(X)nH (n = 0–12) and over 90% of the proteins contain more than two motifs (ESI,† Table S2). Especially, MurA, MurC, GlmU, ThrS, and TyrS related to peptidoglycan biosynthesis contain more than ten motifs.42 This result implicates that excessive copper may function as co-enzyme factors to improve the activity of these enzymes and thus promote cell wall
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