Transcriptome Analysis Reveals Silver Nanoparticle-Decorated

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Transcriptome Analysis Reveals Silver Nanoparticledecorated Quercetin Antibacterial Molecular Mechanism Dongdong Sun, Weiwei Zhang, Zhipeng Mou, Ying Chen, Feng Guo, Endong Yang, and Weiyun Wang ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.7b02380 • Publication Date (Web): 27 Feb 2017 Downloaded from http://pubs.acs.org on March 3, 2017

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ACS Applied Materials & Interfaces

Transcriptome

Analysis

Nanoparticle-decorated

Reveals

Quercetin

Silver

Antibacterial

Molecular Mechanism Dongdong Sun1, Weiwei Zhang1, Zhipeng Mou, Ying Chen, Feng Guo, Endong Yang, Weiyun Wang* School of Life Sciences, Anhui Agricultural University, Hefei, 230036, China *Corresponding author. Tel.:086 551 65786703; fax: 086 551 65786703 E-mail addresses: [email protected] 1

Both authors contribute equally to this work.

ABSTRACT:

Facile and simple method is developed to synthesize silver-

nanoparticle-decorated quercetin nanoparticles (QA NPs). Modification suggests that synergistic quercetin (Qe) improve antibacterial effect of silver nanoparticles (Ag NPs). Characterization experiment indicates that QA NPs have diameter of approximately 10 nm. QA NPs show highly effective antibacterial activities against drug-resistant Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). We explore antibacterial mechanisms using S. aureus and E. coli treated with QA NPs. Through morphological changes in E. coli and S. aureus, mechanisms are examined for bacterial damage caused by particulate matter from local dissociation of silver ion and Qe from QA NPs trapped inside membranes. Moreover, we note that gene expression profiling methods, such as RNA sequencing, can be used to predict discover mechanisms of toxicity of QA NPs. Gene ontology (GO) assays analyses demonstrate molecular mechanism of antibacterial effect of QA NPs. Regarding cellular component ontology, “cell wall organization or biogenesis” (GO: 0071554) and “cell wall macromolecule metabolic process” (GO: 0044036) are most represented categories. Present study reports that transcriptome analysis of mechanism offers novel insights into molecular mechanism of antibacterial assays. Keywords: Quercetin, Silver nanoparticles, Antibacterial mechanism, RNASeq, Transcriptome

INTRODUCTION Bacteria are microorganisms that cause deadly infections1. Drug-resistant microorganisms are another major problem for current medicine. Although antibiotics are the frontline defense against bacterial infection, the emergence of pathogenic antibiotic resistance has prompted the development of highly effective, novel antimicrobial agents2. Antimicrobial resistances are a worldwide issue because it generates antibiotics-resistant and increases healthcare costs3. Thus, new efficient antibacterial material is significant and necessary in our life. Silver and its compounds exert strong inhibitory and bactericidal effects, as well as broad-spectrum antimicrobial activities against fungi and viruses4,5. Although silver is toxic to microorganisms, it is less dangerous to mammalian cells than other metals6. Silver NPs as a kind of nanosized silver particles can be used as bactericides7,8. Someone proposed possible antibacterial mechanisms indicate that Ag NPs release Ag+, which then binds to the thiol groups of

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bacterial enzymes to interfere with DNA replication. Another mechanism of bactericidal action was proposed; this mechanism explains that antibacterial activity is based on electrostatic attraction between negatively charged cell membrane of microorganisms and positively charged Ag+ ions9-11. Particle-specific interaction of Ag NPs with bacteria, their subsequent penetration, and local release of Ag+ ions, which all cause bacterial death, was also proposed to their antibacterial property12-14. Thereby, Ag NPs attracted great attention because of their effective bactericidal effect. In recent years, dietary flavonoids have gotten a lot of attention because their potential health benefits are associated with decreased risks of different chronic diseases, especially cardiovascular disease7,15,16. 3,3′,4′,5,7-Pentahydroxyflavone (quercetin, Qe) is a highly abundant flavonoid from fruits and vegetables17. Moreover, Qe can be extracted from the flowers and leaves of some plants. As an important component of numerous plant-based medicines, Qe has been used to treat several diseases18,19. Ag NPs connected with Qe was introduced as new nanomaterial for antibacterial assays. Furthermore, conventional toxicity assays may not suffice to fully capture complexities of cellular responses toward NPs. Antibacterial mechanisms remain unclear with regard to this specific effect of exposure to nanomaterial occurs. Thus, new and more comprehensive approaches are needed. Transcriptomics field speed development in recent years with introduction of next-generation sequencing technologies, such as RNA sequencing (RNASeq), which will possibly displace cDNA microarrays as favored method for gene expression profiling of cells and tissues20,21. RNASeq provides useful tool to identify differently in expression level of genes, following treatment with various compounds22. Compared with whole genome sequencing, main advantage of RNASeq is that it only analyzes transcribed regions of genomes. Compared with conventional method, less is known on antibacterial mechanisms of NPs at gene expression levels. Gene expression profiling can also be used as new tool to evaluate interaction between NPs and biological systems to reveal its molecular mechanism23. In a previous study, mechanisms were unclear regarding this specific effect of exposure to silver nanoparticle-decorated quercetin nanoparticles (QA NPs) occurs; damage of bacterial membrane was probably caused by presence of particulate matter and/or local dissociation of Ag+ and Qe from QA NPs trapped in mucus surrounding bacteria membrane23,24. Through this study, we hoped to identify set of complete mechanisms for QA NPs in antibacterial assays.

MATERIALS AND METHODS Materials. All chemicals were purchased from Sigma-Aldrich (Sigma) Chemical Co. Ultrapure Luria−Bertani (LB) agar powder was homemade or acquired from School of Life Sciences, Anhui Agricultural University. Pseudomonas aeruginosa ATCC 27853 (P. aeruginosa), Bacillus subtilis ATCC 6633 (B. subtilis), Escherichia coli ATCC 8739 (E. coli) cell and Staphyloccocus aureus ATCC 6538 (S. aureus), lines were acquired from Anhui Agricultural University. All other chemicals were of analytical grade. Ultrapure water was used throughout all experiments. Synthesis of QA NPs. QA NPs were synthesized based on the methods reported by Sun et al. The only difference between this study’s method and that of Sun et al. is


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that aqueous AgNO3 and Qe solutions with different molarities (1/0.75, 1/1.5, ½) were mixed under vigorous stirring for 5 min. Finally, NPs were collected via centrifugation at 8000 rpm for 10 min25,26. QA NP Characterization. We examined the morphology of the QA NPs with a transmission electron microscope (TEM, TJEOL 6300 F, Tokyo Japan, Philip) and a scanning electron microscope (SEMXL-20, Holland, Philips). The samples were prepared for viewing by dripping 20 µL QA NP solutions onto a carbon-coated copper grid. The samples were then air dried before imaging. The nanoparticle zeta potentials of the QA NPs were measured with Zetasizer Nano ZS (Malvern Instruments, UK)28. The infrared, UV–vis absorption, and fluorescence spectra of the QA NPs were obtained with a Bruker Tensor 27 FT-IR DTGS detector27,28, a spectrophotometer (JASCO, Japan), and a fluorescence spectrophotometer (JASCO FP-6300, Tokyo, Japan), respectively. All determinations were performed in triplicate25,29. Cell Culture. Four kinds of bacterial cells were cultured in LB medium at 37 °C. A solution of logarithmic-phase (log-phase) bacterial cells was acquired by reinoculating into fresh media for 12 h. The cell solution was incubated in a shaking incubator for 2−3 h until reaching a 0.5 optical density at 600 nm (OD600nm)30. Antibacterial Activity Test of QA NPs. Based on the antibacterial method developed by Sun et al., solutions of log-phase bacterial cells (P. aeruginosa, S. aureus, B. subtilis, and E. coli) were inoculated in a solution that contained 20 µg/mL QA NPs, Qe, or Ag NPs. Then, the solution was incubated for 12 h at 37 °C in a shaking incubator. The LB agar plate contained the same number of the four bacterial species. The bacterial cells that were cultured in a solution without QA NPs served as the control. The number of viable cells were statistically determined by counting colony-forming units (CFUs)31,32. This study used a concentration unit of µg/ml based on Qe. All tests were carried out in triplicate or quadruplicate. Log-phase S. aureus and E. coli were cultured with different QA NP concentrations (5, 10, and 15 µg/mL) under similar culture conditions. Exactly 5 µL of bacterial suspension was viewed with a FL microscope at 480 nm (IX-71, Olympus, Japan)33. Cellular Uptake Assay. The cellular uptake QA NP assay was conducted using a FL microscope. Log-phase cells (S. aureus and E. coli) were treated with QA NPs (5, 10, and 15 µg/mL). Cells were collected via centrifugation (3000 rpm, 15 min), washed twice with phosphate-buffered saline (PBS; pH 7.5, 0.1 M), and stained with 4’-6-diamidino-2-phenylindole (DAPI, 5 µg/mL, Life Technologies) for 30 min in the dark. Cell suspensions were also washed twice with PBS (pH 7.5, 0.1 M) to eradicate redundant DAPI. A total of 5 µL cell suspensions were observed under a FL microscope at red and blue channels to visualize QA NP uptake and DAPI staining, respectively30. Fluorescence Microscopic Observation (Live/Dead). Log-phase bacterial cells (E.



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coli and S. aureus) were treated with QA NPs (5, 10, and 15 µg/mL) under similar culture conditions. Bacterial cells were collected and washed using the same methods. Subsequently, bacteria were stained using the LIVE/DEAD BackLight Bacterial Viability Kit (SYTO9 and propidium iodide (PI), Life Technologies) for 30 min in the dark. Cell suspensions also were washed twice with PBS (pH 7.5, 0.1 M). Lastly, 5 µL bacterial suspension was observed under a FL microscope at the green and red channels for SYTO9 and PI (PI samples need to be observed within 1 h), respectively34,35. Membrane Integrity Studies. Membrane integrity assays were performed based on the methods reported by Sun et al. Log-phase cells (E. coli and S. aureus) were subjected to the same treatment with QA NPs (5, 10, and 15 µg/mL). The bacterial cells that were cultured without QA NPs were utilized as the blank group. The collected cells were dehydrated with a series of ethanol concentrations and subsequently postfixed with 2.5% glutaraldehyde and 2% paraformaldehyde for 12 h. Finally, the air-dried bacterial cells were observed via SEM36,37. β-galactosidase assays were performed using the methods established by Koepse and Russell. Log-phase E. coli were inoculated in fresh LB medium. Then, the assay was performed by adding 100 µL 80 mg/mL ortho-nitrophenyl-β-D-galactopyranoside (ONPG) to 1.5 mL of log-phase E. coli suspension. The optimum pH values to stimulate E. coli β-galactosidase activity in glycine buffer was 8.0 and 7.5 with lactose and ONPG as substrates, respectively40. Then, various concentrations of QA NPs (5, 10, and 15 µg/mL) were added to the suspension. The reaction proceeded until a visible yellow color was observed. To evaluate the effects of ortho-nitrophenol (ONP), the extent of the reaction was determined by measuring the OD of the suspension at 420 nm. Then, enzyme concentration was calculated. Bacterial cells that were cultured in solutions without Ag NPs (15 µg/mL) and with Milli-Q water served as the control groups38. Wall Destruction Assay. E. coli and S. aureus were exposed to QA NPs (5, 10, and 15 µg/mL). E. coli and S. aureus that were exposed without QA NPs were as the blank controls. Cells were collected and then fixed with 2% paraformaldehyde and 2.5% glutaraldehyde for 12 h. Subsequently, the bacterial cells were postfixed on a rotator with 2% osmium tetroxide (OsO4) for 1 h. The fixed bacterial cells were dehydrated in an acetone gradient series (35%, 50%, 70%, 80%, 95%, and 100%) for 20 min. The cells were treated with a series of processing (include embedded, sectioned, and mounted on 200-mesh copper grids). Then, the air-dried cells were observed with TEM39,40. RNA Extraction and Quantification. Log-phase E. coli cells were treated with QA NPs (10 µg/mL) for 12 h at 37 °C. Cells without treatment served as the blank group. Total cellular RNA was extracted using a Trizol kit (Life Technologies). RNA quantification was evaluated using the RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, CA, USA).


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cDNA Library Preparation, Clustering and Sequencing Analysis. cDNA library preparation is described in detail in the supporting information section. Index-coded samples were clustered based on the methods described by Zhang et al41. After cluster generation, Illumina Hiseq platform was used to prepared cDNA library sequenced. Raw RNA-seq data (raw reads) were processed using in-house Perl scripts with FastQC software. Raw reads that contained adapter and low-quality sequences were removed from the raw data to obtain clean RNA-seq data. Then, the Q20 and Q30 were counted. Downstream analyses were performed based on the high-quality clean data. Quantification of Gene Expression Level. Read numbers that were mapped to each gene were counted using HTSeq v0.6.1. Additionally, FPKM was calculated based on gene length and used to analyze transcript expression levels42-44. Differential Expression Gene Analysis. The control and QA NP groups were subjected to differential gene expression analysis using DEGSeq R package version 1.20.0, which identifies differentially expressed genes. P-values were calibrated for multiple tests as previously described (Benjamini and Hochberg method). For comparison, a P-value of 0.005 and log2 (fold change) of 1 were set as the threshold for significantly differential expression22. GO and KEGG Enrichment Analysis. Gene Ontology (GO) enrichment analysis and pathway enrichment analysis of KEGG (Kyoto Encyclopedia of Genes and Genome) were performed as previously described. Simple, GOseq R package was used to analyze the GO enrichment analysis of differentially expressed genes. The P-value denotes the significance of GO term enrichment in the differentially expressed genes (DEG). GO term with corrected P-values less than 0.05 is recommended. The statistical enrichment of differential expression genes was tested using KOBAS software in KEGG pathways45.

RESULTS AND DISCUSSION Characterization. In synthesis procedure of QA NPs, Qe was loaded on surfaces of Ag+ ions nanosheets. Figure 1 showed full list of characterizations. Featurse of QA NPs was strongly influenced by interaction charged Qe and Ag NPs (Ag). These experiments aimed to determine critical ratio for QA NPs. TEM images suggested that optimum ratio was 0.75:1 for QA NPs (Figure 1A). Under this condition, QA NPs, ranging from 5 nm to 10 nm, as revealed in Figure 1A. The intensity of fluorescence at the peak position of QA NPs had maximum value compare with other ratio. Ratio was used in succeeding experiments. Synthetic QA NPs was monitor by UV−vis spectroscopy (Figure 1B). Surface plasmon resonance peak of Ag NPs at approximately 400 nm suggested formation of QA NPs46,47. FTIR test analyze interactions between Qe and Ag NPs was carried out. The FTIR spectra showed in the



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Figure 1C. In the FTIR spectra of Qe, at 3416 cm-1, broad and intense peaks centered is OH groups, and strong peak corresponds to stretching vibrations of C=O carboxylic moieties at 1728 cm-1 48. Therefore, this result confirms modification of Qe plasmonic NPs, such as Ag NPs was easier49. For QA NPs, peak positions of functional groups remained on Qe, and their shapes were similar. Characteristic peaks of QA NPs were observed in spectrum; these peaks may be indicative of Qe interaction with Ag NPs. Regarding zeta potential measurements, as shown in Figure 1D, value of Ag NPs was +51.2 (±0.29) mV. But QA NPs decreased to +22.7 (±0.15) mV. Variation in zeta potential further confirmed the modification of Qe connect with Ag NPs. Synthesized QA NPs completely dissolved in water and showed fluorescent properties under UV light (Figure 1E). Raw Qe suspended in water was insoluble and did not show any fluorescence under UV light. Qe also showed difference under bright. SEM image showed better morphology of QA NPs compared with TEM image (Figure 1F). Left panel suggested distribution of NPs. But right panel showed Qe surrounding QA NPs. Qe released into the solutions was performed by testing absorbance using UV−visible spectrophotometer (OD260nm) from QA NPs. The initial rate of Qe release was high and the release rate reach equilibrium was at 12 h. The results suggested that the release rate of Qe from nanoparticles was up to 76% (Figure. S1). Insert Figure 1

Testing Antibacterial Activity of QA NPs. In this work, fabrication of QA NPs modified Qe property. Screening with QA NPs (20 µg/mL) against bacteria were performed using P. aeruginosa, B. subtilis, S. aureus and E. coli. All antibacterial experiments used log phase bacterial cells. CFU method was carried out in this study. Different antibacterial activities of QA NPs were observed against four kinds of bacteria (Figure 2C). New particle showed higher antibacterial activity than raw Qe and Ag NPs. QA NPs had more evident effect on activity of S. aureus and E. coli cells than P. aeruginosa and B. subtilis. Against S. aureus and E. coli, survival rates of QA NPs were 12.4% and 23.1%, respectively. Survival rates of other two bacteria were 43.7% and 56.3%, respectively. Inhibitory effect of QA NPs was highest against E. coli. Therefore, we used S. aureus and E. coli cells as our model bacteria for all drug delivery studies. CFU method was also adapted in this part, where bacterial cell was estimated in LB agar powder plate. Photographs of bacterial colonies (S. aureus and E. coli) formed on LB-agar plates were blank, Qe (20 µg/mL), Ag NPs (20 µg/mL) and QA NPs (20 µg/mL) groups. Corresponding images were graphed by origin software (Figure 2A). Antibacterial activity of QA NPs was compared with blank, Qe, and Ag NPs groups. Water was used as blank. CFU was also adapted in our study, where bacterial cell viability was estimated throughout. CFU values of blank for S. aureus and E. coli reached 6.7×108 and 8.5×108 CFU/mL, respectively. CFU values of Qe for E. coli and S. aureus were 9.1×107 and 7.3×107 CFU/mL, respectively. CFU values of Ag NPs for E. coli and S. aureus were 1.9×107 and 1.3×107 CFU/mL, respectively. Most optimum antibacterial activity was demonstrated by QA NPs, which had CFU value (CFU/mL) of 2.3×106 for E. coli and 1.7×106 for S. aureus. As shown in Figure 2A, survival rate of QA NPs was very much lower than three other groups. Results suggested that QA NPs had superior antibacterial activities compared with raw Qe and


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Ag NPs. As shown in Table S1, MIC of QA NPs is 2.8 µg/mL for S. aureus and 4.2 µg/mL for E. coli. The MIC of QA NPs against E. coli was lower than kanamycin (0.9 µg/mL), whereas the MIC of QA NPs against S. aureus was greater than kanamycin (0.3 µg/mL) compared with ampicillin and kanamycin. However, the MICs of QA NPs against S. aureus and E. coli were less than Qe and Ag NPs. The MIC of Qe is 10.5 µg/mL for S. aureus and 7.5 µg/mL for E. coli. QA NPs antibacterial activity is predominant. QA NPs may become new antibacterial nanoparticle for further research. To further investigate antibacterial activity and drug delivery of QA NPs, the work used fluorescent property of proposed nanoparticles. Results suggested that QA NPs could enter cells at low concentration (5 µg/mL); fluorescence intensity of nanoparticle in cells gradually decreased (Figure 2B) with increasing concentration of QA NPs. This part of the study showed that increasing concentration of QA NPs could effectively inhibit bacteria. The vitro experiment results suggested checked QA NPs as a new nanoparticle for antibacterial assay. Insert Figure 2

Fluorescence Assays about Cellular Uptake and Antibacterial Activity. To investigate drug delivery efficacy, fluorescence microscopy analysis experiment was carried out test cellular uptake of NPs. The present study used the DAPI, which is a nucleic acid dye that can act on all cells in fluorescence assays. QA NPs (5, 10, and 15 µg/mL) were used to treat E. coli and S. aureus cell cultures for 12 h. As shown in Figure 3, red cells were resulted from actions of QA NPs, and blue cells were dyed by DAPI. Fluorescence assays was performed at 210 nm laser excitation and 365 nm emission filters for QA NPs, at 358 nm laser excitation and 461 nm emission filters for DAPI. Pink cells were overlap images, which revealed that NPs exhibited high uptake rate at 100%. At low concentrations, QA NPs could enter cell. But inhibit effect was bad. After increasing concentration of QA NPs, pink cell decreased. Above all, results showed that QA NPs could be easily uptake by bacteria cells. Hence, QA NPs are possible antibacterial nanoparticles that can be transported cell in vitro. Results suggested QA NPs had a good inhibitory effect for E. coli and S. aureus. Insert Figure 3

In antibacterial assays, QA NPs either killed bacterial cells or incompletely destroyed bacteria but simply harm cells; bacteria were then cannot form visible colonies. In another fluorescence assay, LIVE/DEAD experiment, to verify and investigate antibacterial efficiency of QA NPs on E. coli and S. aureus, QA NPs (5, 10, and 15 µg/mL) treat bacterial cell were stained by LIVE/DEAD Kit; measured results are shown in Figure 4. Fluorescence assays were performed at 488 nm laser excitation and 530 nm emission filters for SYTO 9 (live stain). At 561 nm laser excitation and 640 nm emission filters for propidium iodide (dead stain) was performed. After brief stained with LIVE/DEAD kit, bacterial cells treated with QA NPs showed intensely red light, indicating dead cells (Figure 4). Green channel represented live cells. Through inhibitory assays results showed that QA NPs indeed killed bacteria cells, rather than harm cells. Moreover, there are large quantities of living cells and few dead cells in images (low concentration of QA NPs treated). However, in experiments,



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high concentration QA NPs yielded completely opposite result. These results further confirmed that QA NPs were bactericidal. But altered live or dead bacteria cells do not mean altered subsequent cell functions, such as protein synthesis and secretion. Insert Figure 4

Cell Integrity Study. Morphological changes of S. aureus and E. coli treated with QA NPs were observed using SEM and TEM. Damage on bacterial membrane is illustrated by SEM (Figure 5). E. coli and S. aureus without QA NPs maintained integrity of membrane structure after incubation for 12 h. Zoomed region (control) showed that bacterial cells were smooth and intact cell membrane. By contrast, cell integrity compromise when cells were treated with QA NPs for 12 h compared with untreated-cells. After treatment with QA NPs, quantity of S. aureus and E. coli cells decreased, cell membrane was wrinkled, and damaged and intracellular contents. At high concentration of QA NPs solution ( 15 µg/mL), damage was still observed in surface morphologies of most cells, whereas leaked intracellular contents were observed in most S. aureus and E. coli cells, as shown in Figure 5. Form and size of cells also changed significantly. Results showed that QA NPs exhibited evident antibacterial effects on cell and QA NPs changed morphology of bacteria cell; this effect might eventually result in cell death. Morphological changes of S. aureus and E. coli of mechanisms are indicative of bacterial cell membrane damage, which was caused by particulate matter from local dissociation of silver ion and Qe from QA NPs trapped in bacteria. Insert Figure 5

Enhanced antibacterial activity was attributed to synergy of Qe when combined with Ag NPs, as suggested by TEM results. Nanoparticle killed bacteria by penetrating bacterial cell membranes and wall. This penetration is possibly the primary antibacterial mechanism. We carried out TEM experiment on bacterial sections (E. coli and S. aureus) and studied distribution of QA NPs inside bacteria for proving the mechanism. Control images showed that bacteria without exposure to QA NPs showed intact cell morphology and clear cell wall. However, remarkable changes in the cell walls were observed after exposure to QA NPs. Cell wall were destroyed or disintegrated. As concentration increased, most bacteria lost cellular integrity after exposure to QA NPs solution for 12 h. Entire profiles became unclear, most cell walls were damaged, and the cytoplasm was leaking. Results were found in Figure 6. Red arrows indicate cell wall and yellow squares represent the QA NPs. Antibacterial activity of QA NPs can directly destroy bacterial cell walls, leading to bacterial death. Above results effectively suggested that high antibacterial activity of QA NPs because of compromised bacterial cell integrity. Meanwhile, cause of disruption of DNA structure should be investigated. Insert Figure 6

To further investigate antibacterial effects of QA NPs on bacterial cell membrane, we continue to carry out other experiment. E. coli has β-galactosidase enzyme which exist in the cytoplasm. When bacterial cell integrity was compromised by QA NPs, β-galactosidase would be released into solution. And β-galactosidase would produce ONP due to catalyzed hydrolysis of ONPG. It would be tested by UV-vis


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spectroscopy (OD420nm). Thus, we used ONPG analyzed β-galactosidase. As shown in Figure 7, the concentration of β-galactosidase increased with increasing nanoparticle concentration in E. coli suspensions. These results indicated that treatment with QA NPs compromised membrane integrity. Loss of membrane integrity caused cytoplasm released into liquid medium. In this study, QA NPs can penetrate cell and enhance introduction of β-galactosidase. Insert Figure 7

Some antibacterial agents can disrupt DNA, thus influencing synthesis of necessary enzymes and cell division, causing death of bacteria. As shown in Figure S2, we used concentration gradient (1, 3, 5, 10, and 15 µg/mL) of QA NPs solution to treat bacteria (E. coli and S. aureus). Bacterial cells exhibited prominent specific DNA degradation, which is typical of necrosis and degeneration, especially when cells were treated at high concentrations. By contrast, DNA (control) disappearance was not observed. We assumed that expression levels of DNA from both organisms gradually decreased with the concentrations of QA NPs (Figure S2). Result showed that QA NPs affected cells at gene expression level. In Vivo Study. In vitro testing by previous experiment showed apparent antibacterial effects of QA NPs on E. coli and S. aureus. However, few reports illustrated and examined in vivo operation model. Lack of characterization and evaluation of QA NPs in vivo greatly hinders their further development toward practical and routine biomedical applications. S. aureus is opportunistic pathogen. Owing to its drug resistance and high mortality rate, S. aureus-caused infections became widespread problem in global medical community. Therefore, we explored and established bacteremia model of mice infected by S. aureus. For antibacterial drugs and clinical applications, cytotoxicity to cells in vivo was unexplored. Histological analysis was used to reveal cytotoxicity of QA NPs in mice. As shown in Figure S3, H&E staining images of tissues of blank group exhibited normal morphology. Simultaneously, experimental group (QA NPs treated) showed no significant effects on mice organs. Hepatocytes were normal, and signs of destruction were not present in liver samples. Therefore, QA NPs were also nontoxic to mice at effective concentrations of antibacterial drug agents. Biodistribution of bacteria in mice infected by microorganisms at different time points (1 day, 3 day, and 5 day) were explored. Bacteria were monitored in major organ at different days (Figure S4A-S4C). Blank group had normal quantity of bacteria (100±10 ×102 CFU/mL or g), but infection and treatment groups showed almost similar number of bacteria (700±50 ×104 CFU/mL or g) after intravenous injection (Figure S4A). Bacteria gradually decreased from third to seventh day after QA NPs treated (Figure S4B-S4C) in vivo. However, bacterial number constantly caused organ inflammation, and number of bacteria reached 600±50×106 CFU/mL or g. When QA NPs were injected on infected mice, bacteria gradually decreased overtime and were almost similar with those of blank group on 5 day (Figure S4C). Bacteremia also led to death for mice. Figure S4D shows survival curves of mice. Infected group had become minimum survival rate compared with other two groups.



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Survival rate of treatment group obviously increased. Possibly, treatment group was cured by QA NPs. Three groups of mice (blank, infection, and treatment groups) were anesthesia and abdomen incision at the seventh day after infected and treatment. Toxicity in target organs was observed through result of H&E staining images of tissues; such observation was performed to decide whether S. aureus could cause inflammation or lesions. Five representative organs were fixed, stained, and analyzed. As shown in Figure S5, normal morphology was observed from H&E staining images of blank group tissues. There were observed to be normal such as hepatocytes in liver samples, pulmonary fibrosis in lung samples and glomerulus structure in kidney section. However, the result showed visual inflammation or lesions tissue caused by S. aureus from the infection group. There were distinct results appear in treatment groups. It is no apparent histopathological abnormalities. Red circle mean inflammation cell. Therefore, QA NPs could as a kind of antibacterial particle for S. aureus in vivo. E. coli Sequencing Data Results. Genomic DNA from E. coli (control and QA NPs groups) was sequenced in triplicate. The quality and length of the sequenced fragments were analyzed to select the most reliable target sequences. In total, control group generated 11.186574 million raw reads with Q30 over 96 %. After removing low-quality sequences (length < 35 bp, Q < 20), retained clean reads totaled 10.974774 million. QA NPs group yielded 10.385656 million raw reads and 9.942204 million clean reads (Table 1). All error rates were low. Statistical analysis revealed high total number of reads of sequencing samples and high ratio of high-quality reads. The results suggested good quality sequencing data. Insert Table 1 Gene Expression Analysis. To identify differentially expressed genes, the expression of each gene analysis by FPKM (the expected number of fragments per kilobase of transcript sequence per million base pairs sequenced). Gene expression levels were calculated based on universal reads. The differential gene expression was analyzed with the HTSeq program. The statistical analysis of gene expression identified genes that the QA NP and control groups differentially expressed. All uniquely mapped reads were transformed into FPKM by Cufflinks, and HTSeq passage was used to identify the DEGs (Figure 8A). It shows results for different FPKM interval gene expressions using statistical analysis by HTSeq in Table 2. FPKM had six intervals (0-1, 1-3, 3-15, 15-60, and >60). Two groups (control and QA NPs) exhibited different gene expression counts in each FPKM interval (Figure 8B, Table 2). These result suggested that E. coli treated with QA NPs had different gene expression compared with control group. Figure 8 presents images of FPKM and violin. Insert Figure 8

Relationship was assessed using Pearson’s correlation coefficient (r). Linear regression and heat map diagram analyses were performed to evaluate association between control and QA NPs (Figure 9). R2 value (0.687) 1) were discovered in two groups, 451 and 9 DEGs were identified in control and QA NPs, respectively (Figure 10A). Two groups of genes were discerned: 330 genes were up-regulated and 1294 genes were down-regulated in control and QA NPs, respectively (Figure 10B). We established differentially genes expressed between treatment (QA NPs) and control groups. Control and QA NP populations showed high numbers of specifically expressed genes, suggesting that QA NPs possibly played key roles in antibacterial effect. Through the FPKM values of two groups, we constructed heat map (Figure 10C). Figure 10C showed heat maps of the induced and suppressed transcripts of NPs-exposed samples relative to matched controls and QA NPs exposures; the figure illustrates agreement of results from different donors in terms of fold-change values. Interestingly, the study found that discovered that specifically expressed genes were higher than that of differentially expressed lncRNAs. Here, two gene groups manifested different expressions, and this result is consistent with that of previous antibacterial assays, showing high effect antibacterial activity of QA NPs. Insert Figure 10

Functional Classifications by GO. The GO project is a collaborative effort to provide reliable gene product descriptions from various databases. GO offers a set of dynamic, controlled, and structured terminologies to describe gene functions and products in any organism23,52. All transcripts were further functionally characterized into GO categories, such as molecular functions, biological processes and cellular components. GOseq was used for the GO functional classification of the assembled E. coli at the macro level. Enriched GO terms totaled 30 terms. As shown in Figure 11A, GO analysis identified a total of 10 terms related to cellular components, 15 terms for biological processes, and 5 terms for molecular functions (QA NPs versus Control). Regarding cellular component ontology, most represented categories were “cell adhesion” (GO: 0007155), “translation” (GO: 0006412), “cell wall organization or biogenesis” (GO: 0071554) and “cell wall macromolecule metabolic process” (GO: 0044036). Result showed wall of E. coli culture with QA NPs had been changed. This result also explained the mechanism of SEM and TEM. We estimated the expression of the 30 GO terms (Figure 11B). Results showed that gene expression of E. coli treated by QA NPs was up-regulated or down-regulated and indicated molecular mechanism for antibacterial effect of QA NPs. Insert Figure 11

Pathway Analysis by KEGG. Research on biological pathways is essential in understanding and advancing genomics research. The highly integrated database Kyoto Encyclopedia of Genes and Genome (KEGG) provides data on biological systems and their relationships at the molecular, cellular, and organism levels. KEGG pathway annotations were generated (Figure 12) from assembled E. coli transcriptome, and results were mapped with GO terms. KEGG analysis revealed 22 KEGG



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pathways. We selected the group related to microbial metabolic pathway for further analysis: microbial metabolism in diverse environments, bacterial secretion system, and bacterial chemotaxis (Figure S6). KEGG analyses of E. coli treated by QA NPs transcriptome sequences revealed presence of significant DEGs enrichment in three pathways compared with control group. Results showed that QA NPs affected bacterial metabolic pathway, thus inhibiting E. coli growth. Insert Figure 12

CONCULSION In this study, environment-friendly, facile, and simple method was developed to synthesize QA NPs. Nanomaterial was fully characterized by TEM, SEM, FTIR spectra, UV−vis absorption spectra, fluorescence spectrometry, and Zetasizer ZS Nano. QA NPs had diameter of approximately 10 nm. QA NPs showed highly effective antibacterial activities against drug-resistant E. coli and S. aureus. CFU assays suggested that QA NPs had more pronounced antibacterial effects than Qe and Ag NPs. Fluorescence microscopy assays demonstrated that individually dispersed QA NPs had high antibacterial activity and cellular uptake. SEM, TEM, and ONP experiments were used to investigate mechanisms of cell integrity study through changes in membrane and enzymes. Disruption of nucleic acids assay assumed that expression levels of DNA from both organisms gradually decreased with the concentrations of QA NPs. In vivo studies demonstrated that QA NPs could as a kind of antibacterial particle for S. aureus in vivo. Gene expression profiling such as RNASeq can be used to predict discover mechanisms of toxicity of QA NPs. E. coli sequencing data results revealed high total number of reads and high ratio of high-quality reads of sequencing samples, suggesting good quality and quantity of sequencing data. Gene expression analysis showed different expressions of two gene groups; this result is consistent with that of previous antibacterial assays, showing high effect antibacterial activity of QA NPs. Results showed that antibacterial mechanism of NPs at genes expression level. The results showed antibacterial mechanism of NPs at gene expression level. GO and KEGG pathway analysis reveal key pathways involved in biological pathway to E. coli treated by QA NPs. Present study reports that transcriptome analysis of mechanism offers novel insights into molecular mechanism of antibacterial assays.

ACKNOWLEDGMENTS This work was supported by the National Natural Science Foundation of China (21401002), the Natural Science Foundation of Anhui Province, China (1508085QB37), and Youth Science Fund Key Project of Anhui Agricultural University (2013ZR011) .

Supporting Information Qe release from QA NPs (Figure S1), the expression level of DNA gradually decreased with QA NPs exposure (Figure S2), cytotoxicity of QA NPs assay (Figure


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S3), preferentially distributed bacteria in blood and tissues (Figure S4), biodistribution of bacteria and histological analysis (Figure S5), microbial metabolic pathway study in E. coil transcriptome (Figure S6).



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Table 1 Summary for the RNA-seq outcomes of control and QA NPs samples Sample name

Raw reads

Clean reads

Clean bases

Error rate (%)

Q20 (%)

Q30 (%)

GC content (%)

Control QA NPs

11186574 10385656

10974774 9942204

1.65G 1.49G

0.01 0.01

98.7 98.86

96.19 96.59

51.47 52.31

Table 2 Summary for gene expression level of different FPKM interval FPKM interval

Control

QA NPs

0-1 1-3 3-15 15-60 >60

303(6.74%) 30(0.67%) 223(4.96%) 1810(40.25%) 2131(47.39%)

745(16.57%) 370(8.23%) 958(21.30%) 1194(26.55%) 1230(27.35%)



A 700

0.75:1

100nm

600

QA NPs Qe

1.5 1.0 0.5 0.0

C0.28

Qe QA NPs

2:1

100nm

200nm

0.24 0.20 0.16 0.12 0.08

200 300 400 500 600 700

50

4000 3500 3000 2500 2000 1500 1000 500 -1 Wavenumber(cm )

Wavelength/nm Bright Blank QA NPs

D 60 Zeta potential (mV)

300 400 500 Wavelength/nm Wavelengty/nm

2.0

E

1.5:1

QA NPs (Qe:AgNO3=2:1) QA NPs (Qe:AgNO3=1.5:1) QA NPs (Qe:AgNO3=0.75:1)

Absorbance

Intensity/A.U.

600 500 400 300 200 100 0 200

B2.5 Absorbance

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Uv-light Blank QA NPs

40 30 20 10 0 Ag NPs

QA NPs

F

Figure 1. Characterization of QA NPs. (A) TEM images of QA NPs under various Qe/AgNO3 mass ratios (0.75:1, 1.5:1, and 2:1; left to right) and fluorescence emission spectra of QA NPs. Optimum ratios remained dispersed. (B) UV–vis absorption spectra of Qe and QA NPs. (C) Infrared spectra of Qe and QA NPs. (D) Zeta-potential of Ag NPs and QA NPs. (E) Digital photographs of QA NPs under bright and UV light, blank (Milli-water), and QA NPs. (F) SEM images of QA NPs at Qe/AgNO3 w/w ratio of 0.75:1.


Blank

Qe

QA NPs

Ag NPs

S. aureus

A

120

S. aureus

100 80 60 40 20 0

Survival Rate (%)

Blank Qe Ag NPs QA NPs 120

E. coli

E. coli

100 80 60 40 20 0

Blank Qe Ag NPs QA NPs

QA NPs (μg/mL) 10

C

15

Blank Qe Ag NPs QA NPs

100 80 60 40 20

a gi no s

is

ae ru

su bt il

P.

B.

S. a

ur eu s

co

li

0

E

5

(%) Rate(%) Survival Rate Survival

S. aureus

B

E. coli

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Survival Rate (%)

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Figure 2. Testing antibacterial activity of QA NPs. (A) Photographs of bacterial colonies (E. coli and S. aureus) formed on LB-agar plates (blank, Qe, Ag NPs, and QA NPs groups). Corresponding images were graphed by Origin software. (B) Fluorescence images of bacterial cells (E. coli and S. aureus); two kinds of bacteria were incubated with the QA NPs solutions (5, 10, and 15 µg/mL) for 12 h. (C) Screening results for E. coli, S. aureus, B. subtilis, and P. aeruginosa by CFU method, survival rates of bacteria, including blank, Qe (15 µg/mL), Ag NPs (15 µg/mL), and QA NPs (15 µg/mL) groups. Values are expressed as mean standard deviation (triplicates).



15

S. aureus

QA NPs (μg/mL) 10

5

A

5

B

15

E. coli

QA NPs (μg/mL) 10

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Figure 3. Fluorescence microscopic images of S. aureus (A) and E. coli (B)cells treated with QA NPs (5, 10, and 15 µg/mL) for 12 h. Suspension were washed and subsequently stained (for 30 min) with DAPI (blue). Staining was carried out at 210 nm laser excitation and 365 nm emission filters for QA NPs, at 358 nm laser excitation and 461 nm emission filters for DAPI. Red cells were produced by QA NPs. Blue cells were stained by DAPI. Pink cells represent confocal images.


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LIVE

DEAD

Overlay

15

QA NPs (μg/mL) 10

S. aureus

5

Blank

A

E. coli

QA NPs (μg/mL) 10

5

Blank

B

15

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 4. Confocal fluorescence microscopic images of S. aureus (A) and E. coli (B) cells treated with QA NPs (5, 10, and 15 µg/mL) for 12 h. Cell were stained (for 30 min) with SYTO9 (green) and PI (red) for antibacterial activity. Staining was carried out at 488 nm laser excitation and 530 nm emission filters for Syto 9 (live stain), and at 561 nm laser excitation and 640 nm emission filters for propidium iodide (dead stain). Cells with green fluorescence represent live bacteria, whereas the red cells are representative of dead bacteria. Overlay images were compared for two kinds of cell. Assay without NPs is as blank.



QA NPs (μg/mL)

Blank

S. aureus

10

5

A

2 μm

2 μm

2 μm

1 μm

1 μm

1 μm

2 μm

2 μm

2 μm

1 μm

1 μm

1 μm

B

E. coli

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Figure 5. Morphological changes of E. coli and S. aureus treated with QA NPs (5 and 10 µg/mL). Sections in red circles are enlarged. Assay without NPs is as blank.


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Blank

S. aureus

A

10 μg/mL

B

Blank

E. coli

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


10 μg/mL

5 μg/mL

15 μg/mL

5 μg/mL

15 μg/mL

Figure 6. TEM images of S. aureus (A) and E. coli (B) treated with QA NPs in different concentrations (5, 10, and 15 µg/mL) for 12 h. Red arrows point to cell wall and yellow squares indicate QA NPs. Assay without NPs is as blank.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figure 7. Absorption of ONP treated with E. coli by Ag NPs (A) and QA NPs (B) at different times and concentrations.


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FPKM density distribution

A

FPKM distribution 6

0.9

Group

Group

Log 10(FPKM+1)

Control QA NPs

Density

0.6

0.3

0.0 0

2

4

6

Control 4

QA NPs

2

0

Control

Log 10(FPKM+1)

1.0

FPKM intervals >60 15-60 3-15 1-3 0-1

0.8 0.6 0.4 0.2

0.0 20 60 40 80 Mapped reads (%)

QA NPs

Saturation Curve (QA NPs)

Saturation Curve (Control)

100

Fraction of genes within 15% of final value

B

Fraction of genes within 15% of final value

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1.0 0.8 0.6 0.4 0.2 0.0 20 60 40 80 Mapped reads (%)

100

Figure 8. All of FPKM density distribution and saturation curve of different groups of E. coli (control and QA NPs groups). (A) Comparison of gene expression levels of control and QA NPs groups. (B) Quantitative saturation curve examination showed requirements of gene expression level for amount of data. Higher expression of genes indicates more accurate quantitative measurements. Large amount of sequencing data are required for low gene expressions.



A

B

Pearson correlation between samples

QA NPs-

Control-

Control vs QA NPs

6 Log 10(FPKM+1), (QA NPs)

QA NPs-

Control-

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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4

2

0

0

2

4

Log 10 (FPKM+1), (Control)

6

Figure 9. Pearson correlation coefficient checked between control and QA NPs groups. (A) Heat map diagram of Pearson correlation coefficient between samples. (B) Scatter diagram of Pearson correlation coefficient between control and QA NPs groups.


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A

B 300

QA NPs vs Control

-Log10 (qval)

DEGs (1624)

Control

100 2.3

D

Cluster analysis of differentially expressed genes

0

-4 -1 1 4 Log2 (fold change)

Subcluster_1, 89 genes


Log2(ratio)

5

Up: 330 Down : 1294

Log2(ratio)

C

200

QA NPs

-5 Control

QA NPs

Control

Control

QA NPs


Log2(ratio)

Log2(ratio)


Control QA NPs

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


QA NPs

Control

QA NPs

Figure 10. Differentially expressed genes analyzed in E. coli (QA NPs versus Control). (A) Venn-diagram showing overlapping sets of differentially expressed genes obtained for control and QA NPs treatment libraries after 24 hours of exposure. (B) Number of differentially expressed genes as result of QA NPs treatments compared with control. Percentages of up- and down-regulated genes for each group indicated on volcano plot. (C) Heat map diagrams used transcripts whose expression levels patterns are in virulent and fecund populations. Red cluster indicates up-regulated; blue cluster indicated down-regulated. (D) Log2 (ratio) line chart. Gray lines were relative expression of genes (clusters) in different groups. Blue lines were average value of relative expressions of genes (clusters) in different groups. Corrected P-value of 0.005 and log2 (fold change) =1 were set as threshold for significantly differential expression.



A GO term

Biological adhesion Cell adhesion translation locomotion Ciliary or bacteria-type flag… Bacterial-type flagellar cell… Cell wall organization or biog… Cell motility Localization of cell Carbohydrate transport Cell wall macromolecule metabo… Cellular component movement Taxis Chemotaxis Response to external stimulus Ribosome Ribonucleoprotein complex Non-membrane-bounded organelle Intracellular non-membrane-bou… Cell projection Pilus Cytoplasmic part Organelle Intracellular organelle Outer membrane-bounded peripla Structural constituent of ribo… Structural molecule activity Transferase activity, transfer… Hydrolase activity, acting on… Transition metal ion binding

B

Type Biological process Cellular component Molecular function

Number of genes

Biological process

100 80 60 40 20 0

Cellular component

Number of genes

The Most Enriched GO Terms (QA NPs Vs Control)

100 80 60 40 20

100 80 60 40 20

Number of genes

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Molecular function

0

Figure 11. Most enriched GO terms (QA NPs versus Control). (A) Genes were annotated in three main categories: biological process, cellular component, and molecular function. “*” point significantly enrich of GO term. We outlined important GO terms in red bubbles. (B) Percentages of up- and down-regulated genes for each of biological process, cellular component, and molecular function GO terms are indicated on the volcano plot.


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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 12. Statistical enrichment of differential expression genes in KEGG pathways. Important pathways were outlined in red bubbles.



TOC Graphics

Morphological change

E. coli

molecular mechanism Gene ontology Biological adhesion Cell adhesion translation locomotion Ciliary or bacteria-type flag… Bacterial-type flagellar cell… Cell wall organization or biog… Cell motility Localization of cell Carbohydrate transport Cell wall macromolecule metabo… Cellular component movement Taxis Chemotaxis Response to external stimulus

GO term

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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QA NPs

Type Biological process

0

10

20

30 40

50 60

Number of genes

Morphological changes to E. coli treated with QA NPs were observed. Gene Ontology analysis indicated that molecular mechanism for antibacterial effect of QA NPs.


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