© Copyright by Hang Ngoc Nguyen 2017

All Rights Reserved

GRAPHENE AND GRAPHENE OXIDE TOXICITY AND IMPACT TO ENVIRONMENTAL MICROORGANISMS

A Dissertation

Presented To

the Faculty of the Department of Civil and Environmental Engineering

University of Houston

In Partial Fulfillment

of the Requirements for the Degree

Doctor of Philosophy

in Environmental Engineering

by Hang Ngoc Nguyen August 2017

GRAPHENE AND GRAPHENE OXIDE TOXICITY AND THE IMPACT TO ENVIRONMENTAL MICROORGANISMS

______Hang Ngoc Nguyen

Approved: ______Chair of Committee Debora F. Rodrigues, Associate Professor, Civil and Environmental Engineering University of Houston

Committee Members: ______Yandi Hu, Assistant Professor, Civil and Environmental Engineering University of Houston

______Stacey Louie, Assistant Professor, Civil and Environmental Engineering University of Houston

______Francisco C. Robles Hernandez, Associate Professor Department of Engineering Technology College of Technology Building University of Houston

______Sarah L. Wallace, Aerospace Technologist, Life Science Research National Aeronautics Space Administration NASA Johnson Space Center, Houston

______Megan L. Robertson, Assistant Professor Chemical and Biomolecular Engineering University of Houston

______Suresh K. Khator, Associate Dean Roberto Ballarini, Department Chair Cullen College of Engineering Civil and Environmental Engineering

Acknowledgements

First of all, I am extremely grateful to my advisor, Dr. Debora F. Rodrigues, for her guidance, useful discussions, and brainstorming sessions, especially during difficult conceptual development stages of my Ph.D. work. Her deep insights helped me at various stages of my studies and experiments. I also remain in debt for her understanding and supporting during the times when I was really depressed or distracted due to personal problems. The skills and knowledge I acquired during my doctoral studies certainly made me a better researcher and future educator. I also would like to especially thank her for always trusting me and being supportive and patient with me. I will carry all teachings and knowledge I was able to obtain through her advising during my doctoral studies to the next steps in my career. She has always trusted and supported me unconditionally. I am thankful for having her as my advisor in my

Ph.D. journey. She made my time at the University of Houston more than just an educational experience, but also an adventure to make me become a better person and future role model for female scientists.

I am also grateful to my thesis committee for taking the time to give me constructive and valuable suggestions on my research project to enhance its quality and impact.

I also would like to extend my gratitude to my laboratory group mates who always supported me during my work in the laboratory. Special thanks to: Dr. Catherine M. Santos, Dr.

Charisma Lattao, Dr. Enrico Nadres, Dr. Felipe Ferrera, and Dr. Tugba Onal Okay who were always helpful and supportive in many different ways. Our research group has been a source of friendship as well as an excellent environment for interaction and collaboration. I want to take a chance to thank all my collaborators, especially Dr. Sarah L. Wallace, Dr. Clemencia Chaves

Lopez, and Dr. Rodrigo Cardoso Oliveira, which I worked extensively during my journey at UH.

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I also would like to thank all UH staff member who helped me academically and personally. I specially acknowledge the financial support from the National Science Foundation Career Award

(NSF Award # 1150255) for supporting me in my research. I also extend my thanks to the authority of Sims South Bayou Treatment Plant for providing wastewater samples used in my studies. Additionally, I would like to send a special thanks to Dr. Alison M McDermott, College of

Optometry at UH, for permitting me to use her laboratory and get help from her senior assistant at the human culture laboratory.

I would like to thank my family (my Mom, Dad, sister, brother-in-law, and all relatives) for their unconditional love and support during my education even though we are far apart from each other. Special thanks to my uncle and aunt who brought me to the United States to get a better life and without whom I would not have been able to start my educational journey in US.

I would like to acknowledge the most important person in my life – my husband Jimmy. He has been a constant source of strength to me. There were times during the past five years when everything seemed hopeless due to problems in my research project and family health issues.

Although he did not know what and how to help me, he constantly encouraged me and was always by my side.

Finally, I wish to express my sincere appreciation to those who have contributed to this work and supported me in one way or the other during my amazing journey.

Hang Ngoc Nguyen

University of Houston

August 2017

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GRAPHENE AND GRAPHENE OXIDE TOXICITY AND THE IMPACT TO ENVIRONMENTAL MICROORGANISMS

An Abstract

of a

Dissertation

Presented To

the Faculty of the Department of Civil and Environmental Engineering

University of Houston

In Partial Fulfillment

of the Requirements for the Degree

Doctor of Philosophy

in Environmental Engineering

by Hang Ngoc Nguyen August 2017

vii

Abstract

In natural and engineered environments, such as landfills and wastewater treatment plants, microorganisms are responsible for cleaning the environment by digesting and biodegrading contaminants. Antimicrobial pollutants can seriously hinder the functionality of native microbial populations leading to ineffective removals of biological and chemical wastes. Additionally, microorganisms can have deleterious effects to society through diseases and food spoilage.

Therefore, it is essential to understand the effect of these nanomaterials on microbial populations as well as their role in hindering microbial activities, such as biological wastewater treatment and antimicrobial properties, to keep the environment balanced and to develop safe antimicrobial applications. This study presents the effects of graphene (G) and graphene oxide

(GO) to fungi and bacteria to identify their impact to the environment and antimicrobial properties for potential applications. These nanomaterials were shown to inhibit significantly fungal growth and their mechanisms of inactivation involved apoptosis of the fungal hyphae.

Acute and chronic toxicity to bacterial communities was also investigated in wastewater. The presence of high concentrations of these nanomaterials in the acute assays affected the carbon, nitrogen and phosphorus biogeochemical cycles significantly. While the chronic assay, showed that the bacterial population shifted differently in the presence of G or GO. Overall, GO was shown to have a more pronounced toxicity than G to the microbial communities in activated sludge.

The antimicrobial properties of these nanomaterials were further explored for application as antimicrobial coatings with polymeric adhesives. The coatings with polymeric adhesives were effective against a wide range of bacteria and did not present cytotoxicity to human corneal epithelial cells, which implied these coatings are promising for biomedical applications.

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Table of Contents

Acknowledgements ...... v

Abstract ...... viii

Table of Contents ...... ix

List of Figures ...... xiii

List of Tables ...... xviii

List of abbreviations used in the thesis ...... xix

CHAPTER 1 RESEARCH HYPOTHESIS AND LITERATURE REVIEW ...... 1

1.1 RATIONALE AND HYPOTHESES DEVELOPMENT ...... 1

1.2 GRAPHENE–BASED NANOPARTICLES ...... 4

1.3 SYNTHESIS METHODS OF G AND GO ...... 5

1.4 ANTIMICROBIAL PROPERTIES OF GRAPHENE – BASED NANOPARTICLES ...... 7

1.4.1 Graphene ...... 7 1.4.2 Graphene oxide ...... 8 1.4.3 Graphene polymer nanocomposites ...... 10 1.4.4 Physicochemical properties of graphene – based nanoparticles that dictate the biological activity ...... 12 1.5 MECHANISMS OF ANTIMICROBIAL ACTIVITY ...... 19

1.5.1 Physical mechanism of antimicrobial property ...... 19 1.5.2 Chemical mechanisms of antimicrobial property ...... 22 1.6 ENVIRONMENTAL APPLICATIONS OF GRAPHENE – BASED NANOPARTICLES ...... 27

1.6.1 Removal of microorganisms by GNPs ...... 27 1.6.2 Removal of organics contaminants by adsorption and photodegradation ..... 29 1.6.3 Removal of cationic heavy metal contaminants ...... 31 1.7 POTENTIAL ENVIRONMENTAL IMPACTS OF GRAPHENE – BASED NANOPARTCILES .. 33

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CHAPTER 2 GRAPHENE AND GRAPHENE OXIDE MORPHOLOGICAL, ENZYMETIC AND METABOLIC EFFECTS IN THE FUNGI: Aspergillus flavus and Aspergillus niger: A HOLISTIC APPROACH FOR FUNGI ANTIMICROBIAL INVESTIGATION ...... 36

2.1 RATIONALE AND OBJECTIVES ...... 36

2.2 MATERIALS AND METHODS ...... 38

2.2.1 Graphene and graphene oxide preparations ...... 38 2.2.2 Fungal strains and growth conditions ...... 39 2.2.3 Mycelial growth inhibition assay ...... 39 2.2.4 Fungal morphological changes in the presence of G and GO ...... 40 2.2.5 Apoptotic-like cell death ...... 41 2.2.6 Thiol oxidation assay for reactive oxygen species (ROS) ...... 43 2.2.7 Superoxide radical anion (퐎ퟐ −.) ...... 43 2.2.8 Fungi enzymatic production in the presence of G and GO ...... 44 2.2.9 Production of volatile organic compounds (VOCs) ...... 44 2.3 RESULTS AND DISCUSSIONS ...... 45

2.3.1 Characterizations of GO ...... 45 2.3.2 Effect of nanoparticles to morphological changes and growth inhibition of A. niger and A. flavus ...... 48 2.3.3 Apoptotic-like cell death responses in the presence of G or GO: mechanism of toxicity ...... 52 2.3.4 Metabolic changes of A. niger and A. flavus in the presence of G and GO ..... 57 2.4 CONCLUSIONS ...... 65

CHAPTER 3 POLYMERIC ADHESIVE NANOCOMPOSITES OF GRAPHENE AND GRAPHENE OXIDE FOR BIOMEDICAL APPLICATION ...... 66

3.1 RATIONALE AND OBJECTIVES ...... 66

3.2 MATERIALS AND METHODS ...... 68

3.2.1 Dopamine methacrylamide ...... 68 3.2.2 Synthesis of adhesive polymers ...... 69 3.2.3 Fabrication and characterization of the coated slides ...... 70 3.2.3 Leaching test of the adhesive coatings ...... 72 3.2.4 Bacterial suspension preparation ...... 72 x

3.2.5 Live/dead assay ...... 73 3.2.6 Fixation of bacterial samples for Scanning Electron Microscopy images ...... 73 3.2.7 Biofilm assay using confocal images ...... 74 3.3 RESULTS AND DISCUSSION ...... 76

3.3.1 Synthesis and characterization of the polymers...... 76 3.3.2 Selection of the best polymer ...... 78 3.3.3 Characterizations of the best coatings for each antimicrobial ...... 80 3.3.4 Stability of the coatings through leaching test ...... 82 3.3.5 Antimicrobial effects and human toxicity of the coatings ...... 84 3.3.6 Mechanism of toxicity ...... 92 3.4 CONCLUSIONS ...... 94

CHAPTER 4 THE ACUTE TOXICITY OF GRAPHENE TO THE BIOLOGICAL WASTEWATER TREATMENT PROCESS ...... 95

4.1 RATIONALE AND OBJECTIVES ...... 95

4.2 MATERIALS AND METHODS ...... 96

4.2.1 Source of activated sludge ...... 96 4.2.2 Experimental design of batch reactors ...... 97 4.2.4 Determination of microbial metabolic activity ...... 99 4.2.5 Microscopic observation of the interaction of G with sludge ...... 100 4.2.6 Polymerase chain reaction (PCR) and cloning ...... 100 4.2.7 Sludge DNA extraction and real time PCR (RT-PCR) ...... 101 4.2.8 16S rRNA gene amplification and deep sequencing ...... 103 4.3 RESULTS AND DISCUSSION ...... 104

4.3.1 Impact of G on chemical parameters of the wastewater treatment ...... 104 4.3.2 Acute toxicity of G on the wastewater biological processes ...... 107 4.3.3 Changes in the sludge Microbial community exposed to G ...... 111 4.4 CONCLUSIONS ...... 115

CHAPTER 5 TOXICITY OF GRAPHENE AND GRAPHENE OXIDE IN SEQUENCING BATCH BIOREACTORS: A COMPARATIVE INVESIGATION...... 117

5.1 RATIONALE AND OBJECTIVES ...... 117

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5.2 MATERIALS AND METHODS ...... 118

5.2.1 Activated sludge batch reactors with continuous feeding of nanomaterials 118 5.2.2 Analysis of chemical parameters ...... 120 5.2.3 DNA extraction and real time PCR (RT-PCR) ...... 121 5.2.4 16S rRNA metagenomics sequencing ...... 122 5.2.5 Approximated Quantification of the amount of G or GO (GO) in activated sludge ...... 122 5.3 RESULTS AND DISCUSSIONS ...... 125

5.3.1 Impact of G and GO on chemical parameters of the wastewater treatment 125 5.3.2 Impact of chronic toxicity of G and GO on the wastewater biological process ...... 130 5.3.3 Changes in the sludge microbial community exposed to G or GO ...... 139 5.4 CONCLUSIONS ...... 143

REFERENCES ...... 145

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List of Figures

Figure 1-1 Catechol ...... 2 Figure 1-2 Typical structure of G and GO...... 4 Figure 1-3 Synthesis of GO from graphite ...... 6 Figure 1-4 Epoxide and vicinal idol ...... 7 Figure 1-5 Mechanisms of cellular interactions of G nanomaterials with bacteria10 ...... 20 Figure 1-6 Morphology of E. coli that exposed to GO with the observation of mechanism132 ..... 21 Figure 1-7 SEM images GO and B. subtilis after interacting (a) B. subtilis without GO and (b) B. subtilis exposed to GO5 ...... 22 Figure 1-8 ROS generation, interconversion and elimination134 ...... 23 Figure 1-9 Sources of Reactive Oxygen Species137 ...... 23 Figure 1-10 Defense mechanisms against oxidative stress ...... 25 Figure 2-1 (a) XRD, (b) Raman spectra of graphite and GO, (c) FTIR, (d) XPS wide scan and (e) C1s XPS of GO ...... 47 Figure 2-2 Biomass reduction (%) of (a) A. niger and (b) A. flavus after growing with and without nanomaterials in Czapek medium. The control is the sample without G or GO. Error bars correspond to standard deviations...... 49 Figure 2-3 Zeta sizer of Czapek medium only (control) and different concentrations of G or GO in Czapek medium (Malvern Zetasizer, Nano ZSP, Malvern, U.S.A.). Error bars correspond to standard deviations...... 50 Figure 2-4 SEM images showing changes in morphology of hyphae: (a) A. niger control, (b) A. niger with G, (c) A. niger with GO, (d) A. flavus control, (e) A. flavus with G and (f) A. flavus with GO at 200 mg/L. Red arrow indicated the G attachment to the hyphae. Scale bar at 5 µm...... 51 Figure 2-5 (a) Aspergillus flavus control, (b) Aspergillus flavus treated with G, (c) Aspergillus flavus treated with GO and (d) Aspergillus niger control, (e) Aspergillus niger treated with G, (f) Aspergillus niger treated with GO at 200 mg/L. The coverslips were stained with Hoechst 33258 and analyzed for early apoptosis. Scale bars, 10 µm and red arrow indicated the nuclear of the control and of the samples with nuclear condensed ...... 54 Figure 2-6 (a) Aspergillus flavus control, (b) Aspergillus flavus treated with graphene, (c) Aspergillus flavus treated with GO and (d) Aspergillus niger control, (e) Aspergillus niger treated with graphene, (f) Aspergillus niger treated with GO at 200 mg/L. The coverslips were stained with Evans Blue and analyzed by bright-field microscopy (late apoptosis). Scale bars, 10 µm...... 55

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Figure 2-7 Aspergillus niger: reactive oxygen species productions (a) H2O2 express in term of loss of glutathione and (b) O2 −. expressed in term of absorbance 470 nm (Ellman’s assay) from the filtrate of the growth fungi under the presence of graphene or graphene oxide. These results were showing the responses of fungi under stress condition. Error bars correspond to standard deviations...... 56

Figure 2-8 Aspergillus flavus: reactive oxygen species productions (a) hydrogen peroxide (H2O2) express in term of loss of glutathione and (b) superoxide anion (O2−. ) expressed in term of absorbance (470 nm) from the filtrate of the growth fungi under the presence of graphene or graphene oxide. These results were showing the responses of fungi under stress condition. Error bars correspond to standard deviations...... 57 Figure 2-9 Enzymatic productions of secreted enzymes by (a) A. niger and (b) A. flavus after growth with G and GO at 200 mg/L. The (*) meaning that no enzymatic production was observed. Standard deviations are presented, but they were negligible in the figure since the results of the replicates were identical...... 59 Figure 3-1 Synthesis of polymeric adhesives ...... 77 Figure 3-2 Live and Dead assessment to select the best adhesives (A, B, C, D) for G and GO...... 80 Figure 3-3 Selection of the best ratio of G and GO with their respective adhesives. The coatings contained 25, 50, 75 and 85% of antimicrobial materials...... 80 Figure 3-4 Scanning electron microscope (SEM) images of the coatings. Scale bar 1µm...... 81 Figure 3-5 Contact angle results of the best coatings: adhesive B with graphene 50% (B-G50) and adhesive D with GO 75% (D-GO75)...... 82 Figure 3-6 Investigation of bacterial survival after the leaching experiment (tested against E. coli K12). The microbial survival was determined using the plate count method...... 83 Figure 3-7 Cytotoxicity of leaching solution against hTCEpi cell line (human corneal epithelial). The negative control with untreated cells and positive control using benzalkonium chloride (BAC) 0.02% are also presented in the figure...... 83 Figure 3-8 SEM images of the antimicrobial coatings after leaching. Scale bar 1 µm ...... 84 Figure 3-9 Live and dead assays of the coatings expressed as percentage of dead cells of E. coli (a), B. subtilis (b), Pseudomonas aeruginosa (c) and Staphylococcus epidermidis (d). (*) indicates statistically significant results between the control (slides coated with the adhesive only) and the adhesive composites ...... 86 Figure 3-10 Microscopic images of live and dead assay for antimicrobial properties of the coatings showing total cells (green) and dead cells (red). The images showed B. subtilis with B, B-G50 and the control. Scale bar at 100 µm ...... 87 Figure 3-11 Scanning Electron Microscope (SEM) images showing the damaged microbial cells after interacting with the coating surface for 2h interaction with B. subtilis (control (a), B and BG (b, c), D and D-GO (d, e). Scale bar at 1 µm ...... 88 xiv

Figure 3-12 Biomass volume of the biofilm (a) E. coli; (b) B. subtilis; (c) P. aeruginosa and (d) S. epidermidis ...... 90 Figure 3-13 Thickness of the biofilm (a) E. coli; (b) B. subtilis; (c) P. aeruginosa and (d) S. epidermidis ...... 91 Figure 3-14 Representative confocal images of biolfilm of B. subtilis: control (glass slide) and adhesive B with 50% G ...... 91 Figure 3-15 Cytotoxicity of coated slides against the hTCEpi cell line (human corneal epithelial) expressed in terms of percentage of dead cells. The uncoated glass slide represents the negative control and BAC (benzalkonium chloride, 0.02%) represents positive control . 92 Figure 3-16 Reactive oxygen species production from the coatings when in contact with glutathione (GSH). The results are expressed in terms of percentage of GSH loss in comparison to the negative control. The symbol (*) indicates the sample results are statistically different from the negative control ...... 93 Figure 4-1 Diagram of the flow of the wastewater at the Sims South Bayou Wastewater Treatment Plant. Red arrow indicates where the activated sludge was collected for this study ...... 97 Figure 4-2 Sample-size-based rarefaction curves of activated sludge from reactors exposed to different concentrations of G ...... 104 Figure 4-3 a) Chemical oxygen demand concentration before and after 5 and 10 h; b) Biological oxygen demand before and after 5 and 10 h run under exposure to different concentrations of G. * Statistically significant different results compared to control samples (0 mg/L) for each time-period (p ≤ 0.05)...... 106 Figure 4-4 Metabolic activity assay of activated sludge with different concentrations of G. *Statistically significant different results compared to control samples (0 mg/L) (p ≤ 0.05)...... 107 Figure 4-5 Microscopic images of interactions between activated sludge and G (100 mg/L). Scale bar at 20µm ...... 107 Figure 4-6 a) Ammonia concentration and b) nitrate concentration produced before and after 5 and 10 h in the presence of different concentrations of G. * Statistically significant different results compared to control samples (0 mg/L) (p ≤ 0.05)...... 108 Figure 4-7 Abundance of AOB and amoA gene in the activated sludge containing different concentrations of G at initial exposure (before addition of G) and after 10 h. * Statistically significant different compared to control samples (0 mg/L) (p ≤ 0.05) ...... 110 Figure 4-8 a) Phosphate concentrations in the reactors before and after 5 and 10 h exposure to different concentrations of G; b) Abundance of PAO under different G concentrations. * Statistically significant different compared to control samples (0 mg/L) respectively for each time-period (p ≤ 0.05)...... 111

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Figure 4-9 Change in the total microbial community abundance in the reactors with different concentrations of G at initial exposure (before addition of G) and after 10 h ...... 112 Figure 4-10 The top 10 phylum (a) and top 20 classes (b) with the highest abundance in the reactors with different concentration of G. Results are presented at 0 h and 10 h. The abundance was expressed in terms of percentage of total effective sequences in each sample (excluding unclassified phyla/ classes). Less abundant phyla/ classes were presented as others...... 113 Figure 4-11 Percentage changes of abundance of the most abundant genera identified in the reactors. The abundance was expressed in term of percentage of total effective sequences of each sample (excluding unclassified number of genera) ...... 115 Figure 5-1 Ammonia removal efficiency (mg/L) during the acclimation of the reactor for 21 cycles (10.5 days). The reactor became acclimated after 16 cycles (8 days)...... 120 Figure 5-2 Spectra of G and GO after subtracting the background of effluent control without nanomaterials showing the increasing in absorbance when G and GO increased (scanning from 200 to 800 nm using UV 2600)...... 123 Figure 5-3 Calibration curves to estimate concentrations of nanomaterials (from 0 mg/L to 50 mg/L (a) and from 0 to 10 mg/L (b)) in effluent using effluent of the control as the dilution media. Standard deviation expressed the triplicate preparation of standard. The wavelengths were used in this experiment: 300 nm (GO) and 400 nm (G)...... 124 Figure 5-4 The accumulation concentrations of G and GO in the reactor at beginning of each cycle (0.5 day)...... 125 Figure 5-5 Chemical oxygen demand in influent, effluent of the control (without nanomaterials) and effluent of reactors treated with G and GO at different concentrations. The errors bar represented the standard deviation COD results from triplicate of the reactors (n = 3)...... 126

Figure 5-6 Biological oxygen demand (BOD5) of the sludge mixture after 10 days running the reactors. Analyses correspond to the control (without nanomaterials) reactors and reactors with G or GO. (*) Shows that the samples were statistically significant different (t-test with P ≤ 0.05) ...... 128 Figure 5-7 Metabolic activity of the reactors containing G and GO at the end of 10 days. The results are expressed as percentage metabolic activity. (*) Shows that the samples were statistically significant different (t-test with P ≤ 0.05) ...... 128 Figure 5-8 Activated sludge staining with SYTO9 for control (no nanomaterials), G 5 mg/L and GO 5 mg/L under the fluorescence microscope at 40X magnification showing that there were more dead cell (red) in the sludge with G or GO comparing to the control...... 129 Figure 5-9 Nitrogen residual as ammonia in influent and effluent for the control and reactors treated with G and GO at different concentrations. The results are expressed as

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concentration versus time in days. The errors bar represented the standard deviation ammonia results from triplicate of the reactors (n = 3)...... 131 Figure 5-10 Nitrogen residual as nitrate in influent and effluent for the control and effluent of reactors treated with G and GO at different concentrations. The results are expressed as concentration versus time in days. The errors bar represented the standard deviation of nitrate results from triplicate of the reactors (n = 3)...... 131 Figure 5-11 Phosphorus residual as phosphate in influent and effluent for the control and effluent of reactors treated with G and GO at different concentrations. The results are expressed as concentration versus time in days. The errors bar represented the standard deviation of phosphate results from triplicate reactors (n = 3)...... 132 Figure 5-12 Images of G and GO stained with Syto 9 only showing the nanomaterial suspensions in SWW (a), in the sludge (c) and the control images of the sludge without the nanomaterials (b). Larger aggregates of nanomaterials are observed in the sludge with G than GO. Images are in 10 m scale ...... 133 Figure 5-13 a) Abundance ammonia oxidizing bacteria gene (AOB) and b) ammonia monooxygenase genes (amoA) in activated sludge, expressed as gene copy number per µL which were normalized to per nanogram of DNA...... 135 Figure 5-14 Abundance phosphate accumulating bacterial (PAO) genes in activated sludge, expressed as gene copy number per µL which were normalized to per nanogram of DNA...... 136 Figure 5-15 Relative abundances of different phyla in activated sludge in 5 reactors with G or GO and control, expressed in term of percentage of the total readings. The top abundances from 0.1% or greater was selected to show along with all the other reactors with G or GO...... 140 Figure 5-16 Heatmap of relative abundances of different genera in the reactors with and without G or GO. Color scale from Red (lowest abundance) to Green (highest abundance)...... 144

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List of Tables Table 1-1 Removal of organic contaminants from water using GNPs...... 31 Table 1-2 Removal of heavy contaminants from water using GNPs...... 33 Table 2-1 Volatile compounds (area relative x 106) detected in the head space of the Aspergillus sp. cultures grown in liquid Czapek medium at 28°C for 10 days...... 62 Table 2-2 Principal chemical groups of volatile compounds (area relative x 106) detected in the head space of the Aspergillus sp. cultures grown in liquid Czapek medium at 28°C for 10 days ...... 64 Table 3-1 Table of NMR/GPC for characterization of the adhesives polymer used in this study .. 78 Table 3-2 Thickness of the coatings before and after leaching for 7 days at 37 oC ...... 84 Table 4-1 Characteristics of synthetic wastewater and Sims South Wastewater Treatment activated sludge ...... 98 Table 4-2 Target gene, concentration of primers and thermal cycle ...... 102 Table 5-1 Characteristics of synthetic wastewater and Sims South Wastewater Treatment activated sludge mixture ...... 119 Table 5-2 Abundance analysis of the 16S metagenomics sequencing of the samples with and without G or GO at the end of 10 days ...... 140

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List of abbreviations used in the thesis G Graphene GO Graphene oxide GNPs Graphene-based nanomaterials ROS Reactive oxygen species PVK Poly (N-vinyl-carbazole) PEI Polyethylenimine PVA Polyvinyl alcohol Psf Polysulfone MIC Minimum inhibitory concentration GSH glutathione (γ-L-glutamyl-L-cysteinyl-glycine) SOD scavenger superoxide dismutase XTT (2,3-Bis-(2-Methoxy-4-Nitro-5-Sulfophenyl)-2H-Tetrazolium-5-Carboxanilide EDTA Ethylenediaminetetraacetic acid rpm Revolutions per minute FTIR Fourier transform infrared analysis XRD X-ray diffraction XPS X-ray photoelectron spectroscopy SEM Scanning Electron Microscopy PBS Phosphate buffer solution −. O2 Superoxide radical anion VOCs Volatile organic compounds SPME Solid phase microextraction GC Gas chromatography MS Mass spectrometry DMA Dopamine methacrylamide TSA Tryptic soy agar TSB Tryptic soy broth hTCEpi Human corneal epithelial cell line PCR Polymerase chain reaction RT-PCR Real time polymerase chain reaction AOB Ammonia oxidizing bacteria amoA Ammonia monooxygenase gene PAO Phosphate accumulating organisms COD Chemical oxygen demand BOD Biochemical oxygen demand MWCNT Multi-walled carbon nanotubes

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CHAPTER 1 RESEARCH HYPOTHESIS AND LITERATURE REVIEW

1.1 RATIONALE AND HYPOTHESES DEVELOPMENT

In recent years, nanoparticles have been attracting a lot of attention, not only for industrial, but also for medical and environmental applications. Among all the nanoparticles currently synthesized, graphene-based nanomaterials (GNPs) gained a lot of attention due to their unique properties.1, 2 The most popular forms of GNPs for diverse applications are graphene (G) and graphene oxide (GO). G, which is a single carbon sheet layer, has been known as the building block for many others carbon-based nanomaterials, this nanomaterial can be better dispersed in nonpolar solvents.3 GO is made of G with oxygen functional groups on its surface. These functional groups make GO more dispersed and less prone to agglomeration in different kinds of polar solvents, such as water.1 The unique properties of these materials made them intensively studied and utilized in industries. Among all the properties of these nanomaterials, their antimicrobial properties have attracted the most attention in biomedical and environmental studies. In several occasions, G and GO demonstrated to have strong antimicrobial property against pure pathogenic bacteria.4-6 These antimicrobial studies have been done mostly with bacteria. Other groups of microorganisms of interests have been largely neglected, such as fungi. In recent years, there were only three studies showing that GO and reduced graphene oxide can inhibit the growth and germination of conidia.7-9 The complete mechanisms of fungal toxicity of G and GO have not been studied. Fungi show strong responses to hazardous pollutants. Based on these other toxicological investigations of fungi with different environmental chemical contaminants, I hypothesized that the presence of G and GO will impact the morphology, enzymatic and metabolic activities of fungi. These parameters have been investigated and presented later on in this study.

1

After investigating the antimicrobial properties of GO and G with fungi, we have investigated the antimicrobial properties in bacteria of these nanomaterials when incorporated into polymers. The antimicrobial properties of these nanomaterials in pristine forms toward bacteria have been extensively demonstrated.10 The rationale for this investigation was that some preliminary studies of graphene-based nanocomposites showed that nanocomposites can have promising properties as anti-microbial agents for safer applications in biomedical fields.6, 11,

12 Studies showed that when G and GO are combined with biologically compatible polymers

(e.g., PEGylation, poly-N-vinyl carbazole (PVK)) the toxicity of the nanocomposites to animal cell lines was negligible.6, 12-15 These results suggest that it is possible to produce antimicrobial surfaces of graphene-based polymer nanocomposites that are non-toxic to humans and animals, but still present anti-microbial properties. Most of these studies, however, developed polymers that did not present any adhesive properties to coat surfaces. Recently, many researchers have shown the possibility of synthesizing bio-inspired adhesives polymers containing catechol groups (Figure 1-1) to simulate the sticky byssus of the freshwater zebra mussels.16, 17 In this present study based on the current research knowledge, we hypothesized that the synthesis of composite adhesives containing antimicrobial G or GO will generate coatings that could act as antimicrobial and anti-biofouling with little or no toxicity to humans. This aspect has been presented in CHAPTER 3.

Figure 1-1 Catechol

2

In addition to the investigation of the antimicrobial properties and potential applications of nanomaterials, it is also important to determine the fate of these nanomaterials in the environment. It is expected that at the end of life of these nanomaterials, they will be released to the environment. In natural and engineered environments, such as landfills and wastewater treatment plants, microorganisms are responsible for cleaning the environment by digesting organic materials and biodegrading contaminants. Antimicrobial pollutants can seriously hinder the functionality of native microbial populations in different environments. This leads to ineffective removals of biological and chemical wastes in the environment. Earlier studies showed that G or GO present antimicrobial properties toward different microorganisms in pure cultures.5, 18 Our hypotheses are that G and GO to the environment may potentially hinder the functionality of microbes.19-21 In this study, we investigate the impact of these carbon based nanomaterials in the wastewater treatment process and in the microbial community. We take into consideration in this study the concentration of the nanomaterials, as well as their long and short term exposure to the microbial community. As described in detail in CHAPTERS 4 and 5.

In summary, in this dissertation, the work is divided into five chapters. Chapter one contains the literature review presenting the important properties and applications of GNPs, as well as the current state of knowledge of toxic mechanisms and potential environmental impacts of these nanomaterials. Chapter two presents the toxicity of G and GO to Aspergillus niger and

Aspergillus flavus, as model fungi. Chapter three presents the synthesis of nanocomposite polymeric adhesives and their antimicrobial, anti-biofouling properties and cytotoxicity to human cells. Chapter four and five presents the acute toxicity of G nanoparticle to the biological wastewater treatment and the comparison chronic toxicity of G and GO to microbial communities in activated sludge, respectively. This investigation will be valuable to understand

3

the fate of these nanomaterials in the environment, as well as how to prepare safer nanocomposites for different antimicrobial applications in biomedical and environmental fields.

1.2 GRAPHENE–BASED NANOPARTICLES

G sheets have a 2D layer carbon atom structure. These carbon atoms are arranged in hexagonal structure, one-atom thick with all the carbons sp2 hybridized.22-24 The pristine form of

G has outstanding mechanical properties, thermal conductivity and relatively large surface area of about 2600 m2/g.25-28 Besides pure G, graphene-derived nanoparticles might contain other atoms such as oxygen, nitrogen, halogens, metals and other elements. The electronic properties of G are limited by the imperfections compared to pristine G. Yet this may result in nanomaterials with different and novel properties. Furthermore, many types of graphene- derived nanoparticles such as GO,29 G with copper and nickel,30 G with chloride or bromide,31 are cheaper to obtain than pristine graphene, making them more available for future scale up operations. Some applications of G derivatives include semiconductor,32 medical,33 environmental,34 antimicrobial,35 and catalysis.36 One of the most important derivatives of G is GO. GO is the functionalized version of G with a variety of oxygen functional groups. GO has higher dispersion ability in polar solvents and due to their abundant functional groups, they have many diverse applications in industry.24, 37 In this study, I will focus on G, GO and their nanocomposites with synthetic adhesives. Figure 1-2 exhibits typical simple structure of G and

GO.

Figure 1-2 Typical structure of G and GO

4

1.3 SYNTHESIS METHODS OF G AND GO

Early rudimentary technique to obtain single layers of G involved peeling G off from solid graphite using an adhesive tape.38 This method was useful to better understand G properties. In fact, the superior G conductive properties raised the interest of many other scientists for different applications.3 The scotch tape method, however, was not amenable to scale up, which led countless researchers to device methods for large scale synthesis of G.39 Another method of preparation, more recently explored, involves high frequency sound to induce vibration in the solid graphite, which unravel into G sheets.40, 41 The exfoliation is usually done in a solvent, such as N-methylpyrrolidine 42 or dimethylformamide 43, which matches the surface energy of graphite and results in the enthalpy of mixing close to zero.44 Re-association of G sheets is prevented by addition of intercalating agents, such as tetrabutylammonium hydroxide 45, cholate 46, permanganate 47, and even hydrogen.48 High shear mixing can also induce exfoliation of graphite to form G sheets.49 These mechanical process – ultrasonication and high shear mixing – can be done in large scales.50

One drawback of mechanical processes, is that it can induce defects on G’s structure and produce G with small lateral sizes.51 For applications that needs perfect lattice and covers large area, direct synthesis of G is achieved by chemical vapor deposition (CVD) of hydrocarbons on surface of transition metals, such as Ni and Cu.52-54 After the chemical growth process, the G is then transferred to another surface such as plastic or glass.55 Large-scale synthesis of large-area

G (30 in. width) for electronic use has been accomplished using the CVD process.56 G materials have also been derived from decomposition of silicon carbide.57-59

In the case of GO, this nanomaterial is the most dispersible form of G in aqueous solutions, due to its hydrophilic nature. The most common route to obtain GO is from conversion of graphite to graphite oxide followed by exfoliation.60 In this process, graphite is exposed to a

5

highly oxidizing permanganate-sulfuric acid mixture,61 which produces defects in natural graphite to allow easy oxidation.62 Changing the amounts of the oxidants control the carbon– oxygen ratio of the product.63 Another step for the synthesis is to expose graphite to a mixture that has phosphoric, nitric or perchloric ions, which will intercalate between the layers and assist in the penetration of the oxidants inside the graphite layers.64 The oxidation is then completed using hydrogen peroxide. After the oxidation, removal of the reactants is done by washing with HCl or NaOH solution followed by water.65 Single to few layers of GO is obtained by exfoliation via thermal66 or sonication methods. Synthetic yields of GO was reported to be as high as 70 %.67 Figure 1-3 shows the schematic of GO synthesis with random distribution of functional groups.68

Figure 1-3 Synthesis of GO from graphite

The GO product has a more random mix of functional groups present in the edge and in the basal plane of the nanoparticle.62 The carbons are present in different oxidation states (Figure 1-

2). Found at the edge of the 2D structures, there are carboxylic acid functionalities. Carboxylic

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acids are weak acids that dissociate in aqueous conditions and impart negative charge to the GO structure. Hydroxyl groups are found at the edges and inside the basal planes, randomly distributed on both faces of the planes. Hydroxyls are hydrophilic functional groups that aids in the dispersion and hydration of GO nanoparticles in aqueous environments. Epoxides are also hydrophilic, but its presence in the basal planes prevents the GO planes from stacking together, making easier for GO to exist in single or in few layers. At acidic pH, formation of epoxide ring is favorable, while at basic pH, the epoxide ring opens into vicinal diol.69 The different of these two molecules are showed in Figure 1-4.

Epoxide A vicinal diol Figure 1-4 Epoxide and vicinal idol

1.4 ANTIMICROBIAL PROPERTIES OF GRAPHENE – BASED NANOPARTICLES

1.4.1 Graphene

The property of G as an antibacterial agent against bacterial proliferation has recently received significant attention. For instance, pure graphene in water at 1000 mg/L is toxic to both

Escherichia coli and Bacillus subtilis.70 G also inhibits Salmonella enterica and Listeria monocytogenes growth at 250 mg/L.71 Several studies have shown that some microorganisms are more resistant than others.72 Typically microorganisms with outer membranes (Gram- negative), such as E. coli, tend to be more resistant than microorganisms lacking the outer membrane (Gram-positive), such as Staphylococcus aureus.73 However, under aqueous conditions, such as growth cultures, G tend to aggregate overtime, exerting less toxicity.74 On the other hand, smaller G, termed as G quantum dots, whose lateral size is 20–67 nm and less

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than 3 nm thickness, can be dispersed really well and exhibit good antibacterial capacity.75

When photoexcited at 470 nm (1W), this GNP generates reactive oxygen species (ROS), including singlet oxygen, hence becomes lethal to different types of cells.75

Besides planktonic (free-swimming) bacteria, biofilm toxicity of G has also been evaluated.

Studies of toxicity of G on biofilms have been very conflicting. For instance, comparison of the biofilm thickness, on graphene-coated surfaces and control surfaces without G, showed significant biofilm inhibition on the coated surfaces.70 The inhibition is attributed to the direct contact of the cells with the sharp edges of G, which would inactivate them by acting like a blade.70 It is also possible that the bacteria could sense the presence of G on the coated surface and by chemotaxis would avoid attaching to it.70

On the other hand, other studies showed increasing biofilm thickness on increasing concentrations of G coated on anodes of microbial fuel cells.76 The enhanced biofilm thickness could be attributed to the excellent electrochemical activity of G, which allows sufficient electron transfer via c-type cytochromes associated with the bacteria outer membranes. These electron transfers could have promoted bacterial metabolism and biofilm growth.77 Another explanation for biofilm resistance to G is that mature biofilms can be formed on top of an initial layer of dead cells on G coated surfaces and the large amounts of extracellular polymeric substance produced by the biofilms could protect the cells from the antibacterial activity of G.

These conflicting findings on the G toxicity towards biofilms suggest that more investigations with different types of microorganisms are necessary to allow a comprehensive understanding of G toxicity on biofilms.

1.4.2 Graphene oxide

Among all GNPs, GO has been one of the most widely investigated antimicrobial agents. GO is easily dispersed in water and has been reported to inactive 50% of E. coli with 40 mg/L GO

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within one hour.35 The plate counting method revealed that GO is able to inactivate 91% of E. coli with a concentration of 80 mg/L.35 Other microorganisms such as S. enterica and L. monocytogenes are inhibited by 100% at a concentration of 25 mg/L.71 Additionally,

Pseudomonas aeruginosa showed 92 % growth inhibition after incubation for 4 hours with GO.78

These results showed the GNPs are potent antimicrobials on pure cultures.

Besides pure cultures, GO has also a detrimental effect in wastewater borne microbial communities. In wastewater, where there are different types of microbial communities present, the toxicity is attenuated, but is still present. Significant reduction (~20–70%) of metabolic activity in wastewater is observed in the presence of 10 mg/L GO.79 The presence of organic matter and ions are responsible for reducing the toxicity of GNPs in wastewater. Hence, higher concentrations are necessary to significantly affect microbial communities in wastewater. For instance, concentrations at 100–300 mg/L GO results in ~35 % bacterial growth inhibition, which affects degradation of organic carbon and nutrient removal in the wastewater treatment.79

Similar to G, the toxicity of GO towards biofilms was also evaluated in several studies. A GO concentration of 1000 μg/mL was shown to inhibit 67% biofilm growth of E. coli. For B. subtilis and Rhodococcus opacus, GO showed biofilm inhibition of up to 60.9% and 42.8%, respectively.5

Furthermore, GO modified membrane filters also showed high antibacterial and antifouling properties. Through confocal laser scanning microscopy, it was observed that the amount of P. aeruginosa attached on the membrane was reduced by more than 80%, as the GO content increased from 1% to 3.5%.80 The anti-biofouling property of GO could be attributed to the permanent inactivation effects on planktonic microorganisms, and therefore bacterial growth and subsequent biofilm formation on the surface.

In conclusion, most studies based on the antimicrobial properties of GO were done using model microorganisms, like E. coli and B. subtilis, in pure cultures under controlled laboratory

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conditions. However, natural and engineered aquatic systems are more complex than simplified systems in terms of microbial community. Therefore, more thorough studies on possible mechanisms behind different kinds of bacteria on complex environments are needed to fully understand the toxicity of GO.

1.4.3 Graphene polymer nanocomposites

Noncovalent methods of functionalization employ hydrophobic interactions, π-π interactions, van der Waals forces and electrostatic binding.77 Reports of antibacterial capacity for noncovalent modification of GNPs include poly (N-vinyl-carbazole) (PVK), chitosan, sulphonated polyaniline, poly(ethylene oxide) poly(propylene oxide) and others. Taking PVK as an example, this polymer has exceptional electronic and mechanical properties, as well as anti- corrosion capability. Dispersing G nanoplatelets into the PVK matrix can create a PVK-G solution for fabrication of PVK-G thin films though electrodeposition.6 Studies with this polymer showed that the presence of PVK enhances more than 10% of the bactericidal capacity of G towards E. coli and B. subtilis than pristine G.6 The authors demonstrated that better dispersion of G in the presence of PVK could be the reason for the higher toxicity of the PVK-G nanocomposite. In addition, synergistic effect caused by electronic interactions or morphological interactions between PVK and G could have also contributed to the antibacterial effect. Comparing with pure

G, PVK-G shows similar biofilm inhibition capacity, but lower cytotoxicity to human cells. This property makes PVK-G a better candidate for biomedical and environmental applications involving human contact.

Another toxicity study with PVK and GO demonstrated that PVK-GO with only 3% GO in the nanocomposite presented 30% and 57% higher antimicrobial effects than GO alone towards planktonic cells and biofilms. This property of PVK-GO, suggests that this nanocomposite can be

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cost effective against biofouling, due to the low cost and high manufacturing yield of this nanocomposite.70

In addition to the non-covalent modifications of GNPs, it is possible to modify GNPs through covalent modifications. Covalent modification of GNPs can include many types of aliphatic and aromatic amines, amino acids, amine terminated biomolecules, and enzymes. In this study, we will focus on the polymers, since many antimicrobial investigations and environmental applications employ polymer nanocomposites. Examples of G based nanomaterial modified by covalent reactions include polyethylenimine (PEI),81 polyvinyl alcohol (PVA) , plasticized poly(lactic acid) and others. In the study of Cao and collaborators, G was embedded in a PVA matrix with a polymer biocide (quaternary ammonium modified polyvinyl benzyl chloride to improve the mechanical strength of the polymer and enhance the antibacterial property of G. As a result, PVA-G with 10% loading of polymer biocide was able to inactive 97.1% of E. coli and

99.7% of S. aureus without exhibiting human cell toxicity.82 They also demonstrated that PVA-G- biocide nanocomposite is able to improve the antibacterial toxicity by 92%, when comparing with pure G. The enhanced toxicity was explained by the increasing number of functional groups in the nanocomposite.82 The efficient antibacterial capacity and mechanical reinforcement of

PVA-G-biocide nanocomposite produced an advanced functional material suitable for hygiene and food packaging.

Alternatively, incorporation of the GNPs into polymers could also assist in the development of membrane systems with less biofouling due to higher antimicrobial properties. For example, the ability to embed GO in polysulfone (Psf) membranes to mitigate biofouling was evaluated with P. aeruginosa biofilms. The results indicated that 1% of GO added to the Psf membrane showed 47% biofilm reduction compared to pure Psf membranes. These results were explained by the increasing hydrophilicity and electrostatic repulsion characteristics of the membranes

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containing GO.80 The anti-biofouling property of the membranes suggests that they can potentially be used in wastewater treatment and water filtration systems.

Overall, different types of GNP nanocomposites have been investigated to achieve high antibacterial toxicity and low human cell cytotoxicity. These properties make them very attractive for water treatment applications, especially in the development of anti-biofouling coatings or membrane systems for water filtration. So far, most of the studies exposing GNPs to microorganisms were done for a short period and in controlled environments. However, the effectiveness of these nanocomposites after long exposure time to bacteria needs to be investigated with various environmental conditions and water chemistries. More importantly, the chronic exposure effects of these nanocomposites need to be further investigated before such material can be widely used for water treatment or other applications.

1.4.4 Physicochemical properties of graphene – based nanoparticles that dictate the biological activity

1.4.4.1 Size effects

The size of GNPs varies from 10 nm, which is the same size of some proteins, to >20 µm, which is larger than most cells.83 Different size ranges of GNPs were shown to exert toxicity in different ways.84 The size of the GNPs determines the dispersion and cellular uptake kinetics, as well as interaction with cells.

In the case of prokaryotic microorganisms the mechanism of toxicity is dictated by the size of GNPs. Smaller GO sheets (<0.127 µm) were shown to interact with E. coli cell membranes.85

The mechanism of toxicity, in this case, is cell damage due to oxidative stress and leakage of intracellular material.84 On the other hand, larger GO sheets (>0.4 µm) cannot enter E. coli cells but are still found to be toxic to the bacteria. Larger GO exert their toxicity by wrapping cells more efficiently, which could lead to cell isolation from the environment and subsequent

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prevention of cell proliferation by lack of nutrients.85 The effect is only bacteriostatic, as E. coli cells can be reactivated by removing the GO sheets wrapped around the cells through sonication.86

GNPs on the smaller size range (<100 nm) can be engulfed by eukaryotic cells through endocytosis.87, 88 The entry of smaller GNPs inside the cell will lead to direct interaction with cellular contents and potential cellular damage. In the case of algae Chlorella vulgaris, exposure to smaller GO (20-50 nm) leads to uptake of the material and shows significant changes in its metabolism.89 Metabolomics analyses showed that there are: 1) an increase in isoleucine level, which results in plasma membrane shrinkage; 2) an increase in linolenic acid, which correlates to increase in oxidative stress; and 3) a decrease of biosynthesis of aspartic acid and serine, which results in decreasing production of chlorophyll.89 Larger GO nanosheets (1-5 µm), which cannot enter the cells, interact with the membrane, eventually encroaching the whole cells and reducing the permeability of the cell wall for nutrients.89

In animal studies, smaller GO with lateral size of 200 nm was found to be capable of inducing more inflammation response in mice compared to significantly larger 350 µm GO.90 In contrast, mice injected with a suspension of small-sized GO (260 nm) could easily eliminate the

GNPs through renal route 91 The GO did not show appreciable toxicity in organs such as liver, lungs, spleen and kidney.92 Meanwhile, large GO particles are intercepted and accumulated in the lungs and kidneys, which showed that at low dose (1 mg/Kg) GO was showing no adverse effect, but some effects were observed at 10 mg/kg such as inflammation cell infiltration, or pulmonary edema. 91, 92

Human cells seem to have a tolerance for very small GNPs, such as GO. GO sheets with the size less than 50 nm, exhibits lower cytotoxicity towards HeLa cells.93 However, same trend as

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the prokaryotes, GO around 160 nm is more toxic to human lung carcinoma cells A549 than larger GO (780 nm).94

In summary, the toxicity of GNPs can be regulated by controlling its size, but it is difficult to provide conclusions related to which size the GNPs are more effective against microorganisms and safe for human use. While it is clear that smaller GO (nm sized) exerts its effects by chemical mechanisms and larger GO (µm sized) by physical means, the limits between these two extremes are not clearly defined.

At the moment, the GNPs that are used in most of the studies have undefined polydispersity95 and the sizes of GNPs are mostly given as averages. Although the average are different from one another, the absence of small-sized GO on so-called “large GO” samples are not guaranteed, and vice versa. Unless, the used GNPs are somewhat homogeneous in size, and size does not change appreciably throughout the incubation period, the effect of size can never be truly isolated. The lower toxicity of large GO might due to the small fractions of small GO.

With these observations, there should be an effort to use homogenized samples96, 97 on these experiments to avoid these pitfalls.

1.4.4.2 Surface chemistry

The surface chemistry of GNPs arises largely due to different functional groups located on the basal plane. These functional groups control whether a GNP is hydrophobic or hydrophilic.83

This fundamental surface property, in turn, dictates many of the interaction patterns of GNPs with biological systems.

G is devoid of surface functional groups and is classified as a hydrophobic material (water contact angle is around 90°).98 In cellular culture, hydrophobic G seeks other hydrophobic surfaces or particles to interact. G was shown to interact preferentially with monolayers of hydrophobic components.99 Computer models suggest that G gains access to cell walls by

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interacting with the hydrophobic tail of phospholipids embedded in the membrane.100 Another surface chemical property of G is the presence of π electrons, which can be utilized for π-π interactions. For example, the surface of both sides of G sheets can bind to the aromatic part of the DNA molecule via π-π stacking.101

The electrostatic surface charge of the G can be modified by adding particles and linkers that control the interaction with cells.102, 103 Addition of negatively charged carboxylic groups makes the G hydrophilic enough to resist hydrophobic attraction with cell membrane of monkey renal cells, allowing them to be smoothly internalized.104 In human cell studies, G coated with negatively-charged polyacrylic acid did not induce oxidative stress and showed no toxicity to

HeLa cells.105

Meanwhile, GO is mainly hydrophilic due to larger proportion of functional groups present on its surface (contact angle of 40–50°).102 The overall surface potential of GO at physiological pH is negative.106 This explains why GO has better interaction with monolayer of positively charged lipids, but not with neutral or negatively charged lipids.107 This includes positively- charged quaternary ammonium groups of choline embedded in the cell membrane.108

The surface chemistry of GNPs can be altered by modifying functional groups present or attaching different groups by covalent or noncovalent means. Biocompatibility and toxicity can also be tailored by modification of the surface of GNPs. Inactivation of the toxicity was done by grafting GO with the non-toxic and hydrophilic polymer poly(ethylene glycol). Attaching dextran to GO resulted to a new GO derivative that is more stable under biological condition and less toxic to HeLa cells.91

The surface chemistry of GNPs should be taken into consideration to determine GNPs’ overall properties. But unlike other properties such as size, shape and number of layers, surface

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chemistry can be customized. The literature is replete with methods of modification of GNPs to suit a particular need.

1.4.4.3 Concentration effects

In this section we will try to analyze the effect of different concentrations of GNPs on microorganisms, mammalian and human cells. Studies have shown that the concentration can be one of the deciding factors on the safety of GNP products for general use.

Studies have shown that lower concentrations of GNPs will inhibit overnight growth of microorganisms. This was determined using the MIC (minimum inhibitory concentration) test.109

The lower the MIC, the more effective the antibiotic, the MIC of well-known antibiotics

Amoxicillin and Penicillin G against various strains of E. coli are 1–8 mg/L and 4–64 mg/L, respectively.110 In animal studies, developing chicken embryos treated with G (thickness, 1-5 nm, size 4μm) presented smaller survival rates when treated with G concentrations starting at 50

μg/L.111

Other GNP, such as GO, has even lower MIC for E. coli, which is 0.25 mg/L.112 This could be due to better interaction of GO with the bacterial membrane.35 These results showed the GNPs are potent antimicrobials on pure cultures. In wastewater, where there are different types of microbial communities present, the toxicity is attenuated, but is still present. Significant reduction (~20–70%) of metabolic activity in wastewater is observed when the GO concentration of 10 mg/L GO is present.79 The presence of organic matter and ions accounts for the lower toxicity of GNPs in wastewater. Concentrations at 100–300 mg/L GO resulted in ~35 % bacterial growth inhibition, affecting degradation of organic carbon and nutrient removal in the wastewater treatment.79

The effect of GNPs on different human cells shows different trends. In some studies, GNPs seem to be very toxic. The loss in viability of human lung carcinoma epithelial cells (A549)

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started at around 2 mg/L in the presence of GO. The viability for these same cells was around

50% at GO concentrations of 125 μg/L.113 Human cells lines, such as bronchial epithelial (BEAS

2B), showed signs of apoptosis and cell viability decrease when exposed to as little as 10 mg/L.114 In another study, GO (>5 μm) showed moderate toxicity toward zebrafish (Danio rerio), inhibiting 20% the cell growth and slightly delaying hatching at 50 mg/L.115

On the other hand, some cells are only moderately affected by GO. Human neural stem cell lines (HBI F3) had a decreased cell viability when incubated with GO at 25 mg/L.116 GO is toxic to human lungs fibroblast cells at 50 mg/L.117 Significant lysis of human red blood cells are observed at 25 μg/L GO (size 324 nm).118 The higher activity of GO is most likely due to aggregation of hydrophobic G in aqueous solution as seen with other carbon-based nanoparticles.119 In another study, at 20 mg/L GO reduced the viability of A549 cells by 20%.120

From these results we can generalize that GNPs are more toxic to bacterial cells, where the toxicity levels start at as low as 1 mg/L. In the case of human cells, the tolerance to GNPs is higher; however, the toxicity depends on specific cell groups and type of GNP. GO seems to be the least toxic to human cells, with a concentration above 25 mg/L. However, due to the variation in the GNPs properties (e.g. size, shape, number of layers, etc. discussed above) can generate conflicting results in the literature.118 Among the GNP properties affecting toxicity, concentration is the easiest to control. It is therefore important to nail the effect of concentration on the toxicity of different GNPs. This would serve as a guide for the safe use of

GNPs, as well as in the formulation of environmental safety standards.

1.4.4.4 Effects of time

The effect of time on toxicity of GNPs to biological systems dictates the severity of cellular damage. Physical contact between cells and GNPs is important in order to trigger physiological responses on organisms. The mechanism of action of GNPs seems to be time dependent.

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Instantaneous cell killing is due to membrane disruption that happens shortly (<1 s) after exposure to GNP. Longer exposure (>2 h) allow GNPs to have more intimate contact with cells and generate ROS damage to cell components. In special cases, G can act as a pump that siphon off the electrons from the electron transport chain affecting the cellular energy process.121 In animal studies, effect of toxicity on exposure depends on the GNP entry to the body. Oral administration did not show toxicity and almost all GNPs passed through the digestive system after 48 h. However, intra-tracheal entry showed that half of the GNP is still present in the lungs after a month, showing toxicity to lung cells as well as spreading via the blood stream to other organs. These examples show that toxicity of GNPs could be managed based on contact time and exposure pathways. The longer the cells are exposed to GNPs, the more toxic they become due to activation of different mechanism of killing pathways.122, 123

The long-term toxic effect of G can be also seen in in vivo studies. The journey of a few layers of G (0.97–3.4 nm thickness) with 14C label in the body of mice was mapped.124 G delivered in mice orally did not show any detectable digestive system adsorption, and 98 % was out in the feces after 48 h.124 The digestive flora changed slightly, where the relative abundance of Firmicutes decrease and Bacteriodetes increased .124 On the other hand, intra-tracheal delivery of G caused lung edema and inflammation after seven days of exposure.124 After 28 days, 47 % of G was still in the lungs and the rest were detected in the intestines, liver and spleen, suggesting that G can pass the blood-air barrier.124 G conjugated with PEG and labeled with 125I did not shown appreciable toxicity in mice at 20 µg/g intravenous dosage after three months.125

Experimentally, time studies are usually obtained for GO because of its easy dispersion in bacterial growth medium. On the first hour of incubation of E.coli with 40 mg/L GO, half of the cells are killed.35 The cells are flattened and cell membranes are damaged. During this this time,

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and up to 2 h, the glutathione (GSH) activity (oxidative damage) of GO is too small and cannot be accounted as the primary mechanism of cellular inactivation action.35 Authors explained that the operating mechanism for the first few hours is physical disruption of cell membranes.

In human cells, such as A549 cells, it is observed that the cells are killed moments after initial interaction with GO.126 The metabolic activity of A549 cells was almost identical whether the incubation time was 2 h or 24 h.126 Oxidative stress have been ruled as possible inactivation mechanism and long term presence of GO in the medium typically leads to protein adsorption to

GO and reduced toxicity.126 In other cell types, such as human retinal cells (ARPE-19), the GO seems to be non-toxic even at high concentrations (100 mg/L) after 72 h of exposure. Cells that are in direct contact with GO showed necrosis after 7 days.127

1.5 MECHANISMS OF ANTIMICROBIAL ACTIVITY

1.5.1 Physical mechanism of antimicrobial property

According to recent studies, the physical interaction of GNPs with microorganisms is the primary antimicrobial activity of these nanostructures.4 Researchers describe that bacterial cell membrane damage caused by direct contact of the bacteria with sharp edges of the nanomaterials is the most effective mechanism in bacterial inactivation.5 By taking G as an example, researchers demonstrated that the corners of G sheets are very sharp and able to penetrate the membrane lipid bilayer. The membrane damage leads to leakage of intracellular materials (e.g. cytoplasm, ribosomes, and nucleic acids), which will eventually lead to cellular death.128 G can interact with the cellular contents and become trapped in the lipid bilayer causing cell leakage and inactivation.129 Figure 1-5 shows the few mechanisms of cellular interactions of G with bacteria such as puncturing of cell membrane, generation of ROS, extraction of phospholipids and adhesion of G sheets on the cell surface. 10

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Figure 1-5 Mechanisms of cellular interactions of G nanomaterials with bacteria10

In the case of GO, which contains carboxyl, hydroxyl, and epoxy groups, it can form more stable dispersions in aqueous solutions than G.4 Hence, the stable dispersion of GO offers more opportunities for cellular interactions than G. Studies have suggested that GO disturbs primarily the cell membrane and enhance cell permeability.130 Through TEM analyses, three stages of cell damage caused by GO were observed for E. coli. In stage I: the cells tolerated GO; after a certain contact time, the cell membranes partially lose integrity (Stage II). In stage III: the cell membranes are severely damaged and some lose completely the intracellular material.131 TEM images showed the stages of E. coli broken down over time (Figure 1-6). 131 The cell was in normal morphology, which indicated the tolerance to GO for short time exposure (Figure 1-5a, stage I). The cell did not have an clear cut on cell membrane, but showing some partial damage with the low phospholipid density as stage II (Figure 1-5 b,c). This was the result of phospholipid

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extracted from the cell. Figure 1-5d, e, f were showing the severe damage of the cell, where the integrity completely lost and some empty parts of the cell were observed.131

a b c

d e f

Figure 1-6 Morphology of E. coli that exposed to GO with the observation of mechanism132

However, the direct contact between the sharp edges of GO and microorganisms is not the only mechanism responsible for cell death. Through SEM observation, it was determined that large GO sheets can wrap bacterial cells, isolating them from the growth medium, where the nutrients are found (Figure 1-7).5, 133 Hence, cells can neither consume the nutrients nor proliferate because GO forms a physical barrier.85

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b

Figure 1-7 SEM images GO and B. subtilis after interacting (a) B. subtilis without GO and (b) B. subtilis exposed to GO5

Overall, it is evident that physical membrane damage is one of the main mechanisms behind toxicity of all the graphene-based nanomaterials. This mechanism will be affected greatly by the specific properties of the nanomaterial, such as size, contact time, concentration, and functionalization among others.

1.5.2 Chemical mechanisms of antimicrobial property

1.5.2.1 Reactive oxygen species

GNPs have been frequently described to produce ROS, which can ultimately lead to cell death. By definition, superoxide anion (•O2¯), hydrogen peroxide (H2O2), and hydroxyl radical

(•OH) collectively are called ROS.134 These ROS are natural byproducts of the metabolism of respiring organisms. The generation, interconversion, and elimination of ROS are presented in

134 Figure 1-8. Briefly, •O2¯ is generated by losing one electron from oxygen. After •O2¯ is generated, it can accept two protons to yield hydrogen peroxide. Hydrogen peroxide is not a free radical, but is more active chemically than molecular oxygen; hence it is included in the ROS group. Hydrogen peroxide molecule can be split up to produce hydroxyl radical and hydroxyl anion by accepting an electron. Finally, hydroxyl radical can interact with an electron and proton resulting in formation of a water molecule.

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Figure 1-8 ROS generation, interconversion and elimination134

ROS are generated intrinsically or extrinsically within the cell. Inside the cells, nicotinamide adenine dinucleotide phosphate (NADPH) oxidase will reduce the molecular oxygen into •O2¯.

Further reduction of oxygen may either lead to H2O2 and •OH via dismutation and metal- catalyzed Fenton reaction, respectively.135, 136 Some of the endogenous sources of ROS include mitochondrial respiration, inflammatory response, and peroxisome, while engineered nanomaterials and environmental pollutants act as exogenous ROS inducers. The sources of ROS are shown in Figure 1-9.137

Figure 1-9 Sources of Reactive Oxygen Species137

In biological systems, during cellular homeostasis, the cells maintain the balance between the levels of ROS generated and eliminated. Excess ROS will damage the cellular components

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and alter cellular functions. Among the biological damages, the most vulnerable targets are proteins, lipid membranes, and nucleic acids.136

To overcome the excess of ROS, cells have developed defense mechanisms. These mechanisms are illustrated in Figure 1-10 that can be both indirect and direct. 137 Physical defense of biological systems could enhance the stability of cellular membranes, and is an indirect method to prevent ROS to approach target macromolecules.137 Another indirect defense mechanism includes the cell repair system, which consists of enzymes and molecules that can efficiently repair the oxidative damage on macromolecules.137 Aerobic cells also possess direct antioxidant defense systems that include the enzymatic scavenger superoxide dismutase

(SOD), catalase and glutathione peroxidase. SOD speeds up the conversion of superoxide to hydrogen peroxide, whereas catalase and glutathione peroxidase convert hydrogen peroxide to water. At the same time, low-molecular-weight antioxidants work as another group of direct defense mechanism, which include ascorbate, pyruvate, flavonoids and the most important one, glutathione (γ-L-glutamyl-L-cysteinyl-glycine, GSH).138 Overall, through these defense mechanisms, cells are able to prevent oxidative damage when interacting with ROS.

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Figure 1-10 Defense mechanisms against oxidative stress

1.5.2.2 Reactive oxygen species generated by graphene – based nanoparticles

GNPs generate ROS through different pathways. G acts as a semimetal or a semiconductor with remarkably high electron mobility at room temperature. This property provides good electron transfer capacity. Therefore, conductive G nanosheets can act as a conductive bridge over the insulating lipid bilayer to mediate electron transfer from bacterial intracellular components to the external environmental to generate ROS (Figure 1-3).4

In the case of GO, it is believed that GO can generate ROS from aerial oxygen. The plausible mechanism is that the unpaired electrons of GO reduce molecular oxygen to form •O2¯. The

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139 •O2¯ can interact with a hydrogen atom to produce H2O2. Since hydroxyl groups are abundant in GO, hydroxyl groups can be directly detached from GO to form •OH. Furthermore, GO can

140 catalyze the formation of •OH from H2O2. The large numbers of oxygen-containing functional groups (e.g., carboxyl) in the surface of GO can facilitate the production of ROS and increase its antibacterial properties.141

1.5.2.3 Oxidative stress and ROS measurement

Changing the balance toward an increase in pro-oxidant over the capacity of the antioxidant is defined as oxidative stress.137 In order to determine conditions of oxidative stress to biological systems, few methods are used to quantify the ROS generation. The measurement of ROS can be done with instrumental analysis, biological and chemical analyses.

In the case of instrumental analysis, the unpaired electron of free radicals can be directly observed using Electron spin resonance spectroscopy. For free radicals, in which the lifetime is

10-9 - 10-6 sec,142 a technique called spin trapping is employed. In spin trapping, the reactive free radical is reacted with a diamagnetic molecule to form a more stable free radical, which can be detected by Electron spin resonance spectroscopy.143

The high reactivity and relative instability of ROS make them extremely difficult to be detected and measured in biological systems. Thus, the assessment of ROS and free radical generation has been extensively investigated by indirect measurements of biological cellular components, such as lipids, protein and DNA. Lipid damage will alter and modify cellular membranes. Therefore, lipid peroxidation could be a signature of ROS damage. To determine

ROS production, it is possible to quantify malondiadehyde production, an oxidized product of polyunsaturated fatty acids. In such ROS assay, melondiadehyde forms an adduct with thiobarbituric acid resulting in a pink product with increasing absorbance at 535 nm.144

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Chemical analysis methods to identify specific ROS are based on reactions with various molecules that are modified to elicit luminescent or fluorescent signals. GSH is a key endogenous antioxidant, whose depletion is proportional to the generation of ROS, such as hydrogen peroxide. Therefore, the consumption of GSH is widely used as a measure of oxidative

78 stress in biological systems. Briefly, glutathione peroxidase will reduced H2O2 into H2O, while the GSH will be oxidized into GSSH at the same time. Total loss of glutathione can be determined colorimetrically by reaction of GSH with 5,5'-dithiobis-(2-nitrobenzoic acid) DTNB

(Ellman’s reagent).145

Besides hydrogen peroxide, superoxide can also be quantified based on the interaction of superoxide with tetrazolium dye (2,3-Bis-(2-Methoxy-4-Nitro-5-Sulfophenyl)-2H-Tetrazolium-5-

Carboxanilide (XTT). XTT can be reduced by •O2¯ to a soluble formazan, which is detected at 470 nm.146 The GO in a concentration of 100 mg/L induces two fold production of superoxide radical anions when compared to the control. This remarkable amount of ROS generated in the presence of GO is one of the reasons for cellular death.147

In conclusion, both physical and chemical mechanisms contribute greatly to the toxicity of

GNPs. Understanding the mechanisms of GNP toxicity is important for the design and fabrication of nanomaterials and their related applications.

1.6 ENVIRONMENTAL APPLICATIONS OF GRAPHENE – BASED NANOPARTICLES

1.6.1 Removal of microorganisms by GNPs

GNPs can be utilized in different ways as antimicrobial agents in environmental applications.

Pure GNPs, as well as polymer nanocomposites, can be used directly as coatings on different types of surfaces, such as metals and plastics. GNPs can also serve as scaffolds for nanometals for more efficient antimicrobial action. In addition, GNPs are also utilized as part of photocatalytic and electrocatalytic systems for water treatment to inactivate microorganisms.

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On surfaces, the antimicrobial properties of GNPs make them very attractive to prevent microbial colonization. For instance, biofilm formation studies showed that G can prevent microbial growth and subsequent biocorrosion.148 Similar antimicrobial action against S. aureus and E. coli is seen for copper and germanium surfaces when a G monolayer is deposited on their surfaces.149 Pure GO deposited on poly(ethylene terephthalate) also showed antimicrobial activities, even on single layered GO Langmuir-Blodgett films.150 These properties make GNPs very attractive to prevent corrosion and for coatings of medical devices in biomedical applications.

Alternatively, GNPs can also be used to change the surface to favorably enhance bacterial adhesion, as investigated in microbial fuel cells applications.151 The rGO formed from electrodeposition of GO on the surface of graphite blocks are shown to enhance the formation of Shewanella oneidensis biofilms on the anode of microbial fuel cells.76 The thick biofilm on the anode could be attributed to the excellent electrochemical activity of GNP, which allows sufficient electron transfer from cells to the electrode to promote bacterial metabolism and biofilm growth.152 E. coli was also shown to proliferate on GO deposited on filters.151 For these microorganisms, the matured biofilm contained a large amount of extracellular polymeric substance, which may have protected the cells from the antibacterial activity of GNPs by preventing direct contact.152

Another important application of GNPs is in water treatment. For instance, G can effectively coat filters without affecting the porosity and resulting in a product with superior antimicrobial activity.141 Alternatively, GNPs can produce composites, containing lower concentrations of these nanoparticles, which can be very effective in preventing biofilm formation. For instance, nanocomposite coatings made by blending GO with PVK showed higher antimicrobial activity than pure GO films, owing to a better dispersion of GO in the polymer matrix because of π–π

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interaction with the side chains of PVK.153 This nanocomposite also showed strong antimicrobial activity against E. coli, B. subtilis, Rhodococcus opacus, and Cupriavidus metallidurans but low toxicity towards mammalian fibroblast cells.5 The PVK-GO nanocomposite was also successfully applied as coating on membrane filters and was able to remove E. coli and B. subtilis by 4 and 3 logs, respectively.141

Another example of application of GNPs for water treatment is a porous hydrogel made from Ag-GO. This hydrogel was able to inactivate 99 % of coliforms from natural water samples from a lake and a creek 154. The inactivation of the microorganisms is thought to be due to the slow release of Au or Ag ions, which complexes with the thiol group in the active site of bacterial enzymes, while GNPs accelerates the ions’ action by disrupting the cell membranes 155, 156.

Aside from the use of GNPs as semiconductor in photocatalytic systems, GNPs is also useful in electrochemical redox systems. The boron-doped diamond and rGO electrochemical oxidation system was found to generate hydroxyl radicals that inactivates 4.5 log of E. coli after only 5 min exposure 157. These two examples show the potential use of GNPs in water disinfection.

In summary, the antimicrobial properties of GNPs can be utilized in three ways –– the first is by directly using GNPs as antimicrobial agents, the second is by using GNPs as a nanometal scaffold, and the third is by using GNPs as electron conductors in photo- and electrocatalytic systems. The varieties of these applications show the versatility of GNPs in environmental antimicrobial applications.

1.6.2 Removal of organic contaminants by adsorption and photodegradation

In addition to the unique antimicrobial properties of GNPs, these nanomaterials can also be used for the removal of organic contaminants. GNPs have been described to remove organic contaminants by adsorption and by photocatalytic activity. In the case of adsorption, the large surface areas of GNPs make them effective adsorbents for aromatic organic contaminants.2

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Aromatic hydrophobic compounds have extensive sp2 structure, which allow π–π interactions with the hydrophobic G. For instance, aromatic organic contaminants, such as trichlorophenol, trichlorobenzene and naphthalene can be captured by G from water.158 Other hydrophobic polyaromatic hydrocarbon compounds, such as phenanthrene and biphenyl, have also been described to adsorb more efficiently to G than to multiwall carbon nanotubes.159 G exhibits three times higher adsorption capacity for these organic contaminants from water compared to multiwall carbon nanotubes.159 Even when present as a coating, G is still effective in extracting hydrophobic organics from water. For instance, a silica gel coated with G is very effective in adsorbing organic pollutants, such as phenanthrene.160 In a more extreme case of environmental chemical contamination, such as oil spill, a foam made of nickel coated with G has also been described to effectively separate oil from water.161

Dyes are another class of aromatic organics that usually contain several fused aromatic rings and polar groups in their structure, which increase their water solubility. Given GO hydrophilicity, GO has been demonstrated to adsorb cationic dyes (methylene blue, methyl violet and Rhodamine B) and anionic dye (Orange G) from water through electrostatic and hydrogen bonds, in addition to π–π interactions.162 Acrydine orange, a powerful DNA intercalating agent,163 can be adsorbed by GO at a maximum adsorption capacity of 3300 mg/g.164 Another highly hydrophilic environmental contaminant, the tetracycline antibiotic, is adsorbed effectively from water (adsorption capacity 313 mg/g) using GO.165 GO functionalized with magnetic particles are also effective in the removal of other organic pollutants, such as phthalate esters, estriol and the aromatic compound fluorine.166

In general, the effective removal of organic materials by GNPs is directly related to the surface properties of the particular GNP. The more hydrophobic GNPs are, such as G, more suitable for removing more hydrophobic organic compounds, i.e., polyaromatic hydrocarbons.

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The GO, with the presence of carbons in different oxidation states, is more effective in removing charged and hydrophilic organic compounds, which includes different antibiotics and dyes. GO offers H-bonding sites to these groups of organic compounds in addition to π–π interactions.

The summary of adsorption of organic contaminants from water is presented in Table 1-1.

Table 1-1 Removal of organic contaminants from water using GNPs.

Organic compound GNPs Adsorption Capacity (mg/g) Ref. Aromatic compounds aniline GO 115.1 167 chlorobenzene GO 67.2 167 Polyaromatic hydrocarbons biphenyl G 54.6-61.4 159 biphenyl GO 44.8 159 naphthalene G 127.7 159, 168 phenanthrene G 143.7-156.6 159, 168 phenanthrene GO 163.9 159 phenanthrene G-coated silica 0.775 159, 160 pyrene G 170.2 160, 168 Pesticide residues diethylphthalate GO-magnetic 8.71 166 Endocrine disrupting chemicals diethylphthalate GO-magnetic 8.71 166 Dyes Acridine orange GO 3300 163 Methyl violet GO 2.47 162, 163 Methylene blue GO 17.3 162 Rhodamine B GO 1.24 162 Antibiotics doxytetracycline GO 398.4 165 oxyteracycline GO 212.3 165 tetracycline GO 313.5 165

1.6.3 Removal of cationic heavy metal contaminants

Besides the removal of organic compounds, GNPs are extremely effective in the removal of cationic heavy metal contaminants. The removal of heavy metals can be easily achieved by GO nanoparticles, since the presence of functional groups on GO surfaces, such as carboxyl and

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hydroxyl groups, enhances its affinity for many types of metal ions.169 On the other hand, the absence of functional groups in G nanoparticles makes G less attractive for heavy metal removal. Among all GNPs, GO is typically the most effective. For instance, divalent ions of copper, zinc, cadmium and lead can be removed by GO with adsorption capacities as high as

300, 350, 530 and 1100 mg/g, respectively.170

The excellent adsorbent property of GO can be further enhanced by surface modifications.

For instance, composites of β-cyclodextrin and GO can remove chromium(VI) from water, and at the same time, convert chromium(VI) into less toxic chromium(III).171 A chitosan-GO composite can recover gold(II) from aqueous solutions with adsorption capacity exceeding 1000 mg/g.172

The attachment of ethylenediaminetetraacetic acid (EDTA) chelator on GO provides another mechanism for heavy metal removal, which now includes superior lead(II) and mercury(II) removal in its capabilities.173 To recover these nanoparticles from water, it is possible to attach magnetite to GO and obtain a reusable EDTA-GO adsorbent.174 Recoverable magnetite-GO composites can also be applied for the removal of cadmium(II) 175, cobalt(II) 175 and arsenic(III) and (V).176 Addition of thiol groups on the surface of GO increases the adsorption capacity of mercury(II) from 30 mg/g to 200 mg/g.177

Besides using the nanoparticles for contaminant removal, other studies have conjugated

GNPs to membranes or filters for water filtration and simultaneous removal of heavy metal contaminants, such as arsenic(III), arsenic(V) and lead(II), and pathogenic E. coli.178 For instance,

PVK-GO nanocomposites membrane filters (10% GO content) can remove lead (II) from aqueous solutions179 and show antimicrobial activities against E. coli and B. subtilis with 3 and 4 log removals, respectively.141 Another filter that was successfully modified with GO is a polylysulfone (Psf) membrane geared for arsenic removal. Addition of 1% GO to Psf while casting resulted into a Psf-GO membrane that is capable of rejecting twice the amount of

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arsenic compared to Psf-only membrane during filtration. In both cases, only a relatively small amount of GO was required in order to see enhancement of metal removal.

Hence, these studies have shown that GO by itself or associated with polymers can effectively remove cationic heavy metals. The effective removal of heavy metals is linked to the presence of functional groups in GNPs, which serves as sites for metal adsorption. In addition, the same functional groups allow GNPs to be easily modifiable to enhance chemical removal and, in some cases, produce a more selective metal adsorbent. Representative studies on the removal of different metals by GNPs and composites are listed in Table 1-2.

Table 1-2 Removal of heavy contaminants from water using GNPs.

Adsorption Capacity Metals GNP Ref. (mg g-1) Ag(I) G-carbon nanotube 64 180 Au(II) GO-chitosan 1000 172 Cd(II) GO 530 170 Co(II) GO 68.2 175 Co(II) GO-magnetite 12.98 35 Cr(VI) GO-cyclodextrin 120 171 Cu(II) GO 300 170 Eu(II) GO 175 181 Fe(III) GO foam 587.6 182 Hg(II) GO-thiol 200 177 Pb(II) GO 1100 170 Pb(II) GO-EDTA 479 173 U(VI) GO 300 181 Zn(II) GO 350 170

1.7 POTENTIAL ENVIRONMENTAL IMPACTS OF GRAPHENE – BASED NANOPARTCILES

GNPs are promising materials for many industrial applications, ranging from medical, optics, electronics and environmental applications. Like for many new materials and chemicals, caution on their utilization is necessary, since over the years, we have developed very important chemicals and materials that turned out to be extremely hazardous. For instance, the discovery of radioactive elements has led many creative and enterprising individuals to sell them to the

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general public as wonder substances capable of healing most maladies. As a result, elements like radium-226 was added from toothpaste to chocolates.183 Soon enough, we learned that the use of radioactive materials could have lethal consequences. This was not an isolated incident in history. Another example is the pesticide DDT. This pesticide was the wonder chemical in the

1940s, until researchers figured out that this pesticide was responsible for making birds to lay soft egg shells, eventually thinning their population.184

The burgeoning applications of GNPs and the unknown environmental and health effects of

GNPs could lead to serious environmental impacts.185 In the last few years, industries across the globe have revved up their engines in producing GNPs in massive scales.186 Eventually GNPs will be leashed into the environment as by-products and wastes from the manufacture of devices and materials containing them. The slow release from polymeric matrices or weathering of materials containing GNPs will also be a valid concern. Ultimately, the final disposal and resting place of GNPs will be landfills, wastewater treatment plants and the environment.

Contamination of the environment will be easily spread through water systems and runoff, as for example, GO has been shown to be very mobile in water when in the presence of naturally occurring ions and organic matter.187

Once in the environment, GNPs might wreak havoc natural microbial populations. The GNPs have a broad-spectrum antimicrobial activity that is sometimes even broader than traditional antibiotics.188 Experiments on the effects of GNPs on environmental microbial population are slowly beginning to appear and indicate that the natural microbial populations are affected.

Studies have also shown that microorganisms are eventually able to cope with environmental stressors, however, it is unknown their tolerance and long term exposure effects of GNPs.

Nanomaterials in general have negative impact on microbial communities on activated

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sludge.189 Carbon-based nanoparticles are no exception. For instance, structurally similar carbon nanotubes and GO were proven to be toxic to microbes in activated sludge.79, 190

Cytotoxicity of GNPs against animal cells and plants is evident and should be investigated carefully.5, 191, 192 There are many other variables that affect the toxicity of GNPs in the environment. For instance, humic acids and potential biodegradation of GNPs have been shown to play major roles on the toxic effects of GNPs. The presence of humic acid could neutralize the effect of oxidative stress. This toxicity neutralization was observed with zebrafish.193

Biodegradation is also potentially another mechanism to reduce the toxicity of GNPs. Although biodegradation studies of GNPs is still in its infancy, preliminary studies showed that biodegradation of more soluble and highly oxidized GNPs seems to occur.194 More hydrophobic, less oxidized G, on the other hand, would probably persist in the environment, and settle at the bottom of bodies of water. In this case, benthic organisms could consume and lead to accumulation of GNPs in the food chain.195

In soil, the effects of GNP are controversial. When G was mixed with soil containing coriander and garlic, it enhanced their growth.196 Different results were observed for cabbage, tomato, spinach and lettuce. In the latter plants, soil contaminated with GO decreased plant growth and damaged plant tissues due to oxidative stress.197

We are on the dawn of GNP devices era. It will not take longer until GNPs show up in water and soil ecosystems. Therefore, further research needs to be done to guide and help lawmakers and governmental agencies developing fair laws and guidelines in GNP utilization, transport, treatment and disposal.

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CHAPTER 2 GRAPHENE AND GRAPHENE OXIDE MORPHOLOGICAL, ENZYMETIC AND METABOLIC EFFECTS IN THE FUNGI: Aspergillus flavus and Aspergillus niger: A HOLISTIC APPROACH FOR FUNGI ANTIMICROBIAL INVESTIGATION

2.1 RATIONALE AND OBJECTIVES

Fungi are considered cosmopolitan microorganisms due to their complex genetic make-up and metabolism.198, 199 Furthermore, this group of microorganisms possesses important roles in ecology, agriculture, forestry and human health. In ecology, fungi play a role as decomposer since they can degrade complex nutrients and contaminants in the environment to balance the biosphere.200 In addition, fungi are one of the major contributors to diseases in different

Kingdoms. For instance, there are several fungi that are plant pathogens, which can cost billions of dollars per year in crop damage.201 Fungi also impact humans by causing diseases as well as by contaminating and spoiling food.202, 203 Besides the adverse effects of fungi, some of these organisms can also be beneficial to medicine, biotechnology and fundamental research.204 For instance, Fungi are the main producers of antibiotics used in our modern medicine.205, 206 Among the different species of fungi extensively investigated, Aspergillus spp. has attracted a lot of attention. This genus is extremely cosmopolitan since it can be found in the environment, hospitals, ventilation systems, contaminated dust, water, foods and ornamental plants.205

Additionally, many species of Aspergillus spp., especially Aspergillus niger and Aspergillus flavus have been reported to cause human diseases.198, 206 Aspergillus spp. can release trillions of spores per day, which can cause chronic diseases to human through inhalation and to plants through direct contact.207 These fungal spores can survive long periods of time until the conditions are favorable for growth; hence, the spread of these spores have ability to create

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pandemics.200 Therefore, to prevent fungal growth, several synthetic antifungal compounds have been investigated and developed.

In the past years, G and GO have been gaining interest due to its promising antibacterial properties.4, 153, 208 Little is known, however, about their properties as antifungal. So far, there are only three studies that investigated the antimicrobial properties of graphene-based nanomaterials as potential anti-fungal. In these studies, only reduced graphene oxide (rGO) and

GO nanoparticles were explored and they looked only into the effects on fungal germination and growth of Fusarium sp. In these studies, they reported that germination of Fusarium sp. was reduced by 13.70% to 77.55% in comparison to the control at concentrations between 10 mg/L and 500 mg/L GO, respectively.7 In another study, also with Fusarium sp., at the highest tested concentration (500 mg/L), there was 50% reduction in growth on solid media.9 In another study, in the presence of rGO, the ability of Aspergillus sp. to grow on solid media was investigated. All these studies determined only the impact of these nanomaterials on fungi growth, however, the impact and mechanisms of action of these nanomaterials in the metabolism of these microorganisms has not been previously investigated.8, 9

In the present study, we investigate the antifugal mechanisms of graphene and graphene oxide toward Aspergillus niger and Aspergillus flavus. In our investigation, we employed several approachs, which involves a combination of different metabolic and cellular fungal analyses to better understand the impact of G and GO in these microorganisms, as well as their potential antifungal mechanisms. Through these approachews, we take into consideration growth inhibition, enzymatic activity, morphological and metabolic changes as well as cell apotosis responses and fungal reactive oxygen species production as responses to adverse conditions.209,

210

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2.2 MATERIALS AND METHODS

2.2.1 Graphene and graphene oxide preparations

G was purchased from XG science. The material was characterized using X-ray diffraction

(XRD), Raman Spectroscopy and Transmission Electron Microscope (TEM), which were provided by XG science.

GO was synthesized from graphite using the modified Hummer’s method.60 Graphite was purchased from Sigma Aldrich, U.S.A. The synthesis of GO is described in detail in our recent published study.211 Briefly, 2.0 g of graphite powder was placed in a round bottom flask and 92 ml of H2SO4 was added and stirred continuously at 150 rpm (revolutions per minute) for 20 min at 0°C. While the mixture was continuously stirred at 0°C, 2.0 g NaNO3 was added and stirred for

1 h. Then 12.0 g KMnO4 was slowly added for further oxidation of the nanomaterial. The temperature was subsequently raised and maintained at 35 °C for 16 h to allow complete oxidation of graphite. Then, 160 ml of distilled water was added and the temperature was further raised to 90°C. The mixture was stirred at this temperature for 30 min. Another 400 mL of distilled water was added to the mixture, then 40 mL of 30% H2O2 solution was slowly added to reduce the excess of permanganate. The mixture was cooled down, and then centrifuged at

14,500 rpm for 5 min. The collected brown precipitate was then mixed with distilled water and centrifuged again under the same conditions. The washing process was repeated until the pH of the resulting supernatant became neutral. The precipitate was re-suspended in 2 L distilled water then sonicated for 8 h for exfoliation of graphite oxide. The sonicated solution was settled overnight, then decanted and freeze-dried to obtain GO powder.

The transformation of graphite to GO was monitored using Fourier transform infrared analysis (FTIR). The functional groups of the synthesized GO were analyzed using a Nicolet iS10

Mid Infrared FTIR Spectrometer (Thermo Fisher Scientific, USA) in the range of 800 to 4000 cm-1

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with air as background. Data acquired were processed and analyzed using Omnic 8 Software

(Thermo Fisher Scientific, USA). The X-ray diffraction pattern of GO was obtained using a

PANalytical X-ray Diffractometer with Cu Kα radiation (λ=1.5418 Å). The Raman spectra was obtained using an in-house built Raman spectrophotometer.212 The X-ray photoelectron spectroscopy (XPS) analyses were determined using a PHI 5700 X-ray photoelectron spectrometer. High and low resolutions with pass energies of 23.5 and 187.85 eV, respectively, were both performed. High-resolution spectra were acquired for photoelectrons emitted from C

1s and N 1s. All data processing was done using a PHI Multipak software (version 5.0A).

2.2.2 Fungal strains and growth conditions

The strains used in this study were Aspergillus niger GM31 and Aspergillus flavus DSM

62065. The strain GM31 was obtained from the University of Teramo, Italy and the DSM 62065 strain was obtained from the German Culture Collection. The culture was initially inoculated in

Czapek agar plates (HiMedia Laboratories, LLC, VWR, U.S.A.) from stock culture tubes stored in sterile distilled water at room temperature. The plates were incubated at 28 oC for 5 days in the dark. Prior to starting each experiment, the strains were transferred to fresh Czapek agar plates at 28 oC to grow for 5 days. The Czapek medium contained sucrose (30g), sodium nitrate (2g), dipotassium phosphate (1g), magnesium sulphate (0.5g), potassium chloride (0.5g) and ferrous sulphate (0.01g) in 1L with pH 7.3 ± 0.2.

2.2.3 Mycelial growth inhibition assay

Powders of both G and GO were sterilized for 20 min using ultraviolet radiation at 254 nm wavelength (Nuaire Labgard biological safety cabinet, Nuaire Inc. U.S.A.). Stock suspensions of

1000 mg/L were prepared with sterile distilled water (DI). In order to evaluate the effects of G and GO on mycelial growth of A. flavus and A. niger, concentrations between 10 mg/L and 200 mg/L were prepared from stock solutions in flasks containing 60 mL of Czapek medium (HiMedia

39

Laboratories). The control samples without nanomaterials were prepared at the same time, but instead of nanomaterials sterile DI water was added. The mycelium was grown in Czapek liquid media from a fresh fungal plate. After five days, the culture was centrifuged at 13,000 rpm for

15 min (Thermo Scientific) and the supernatant was discarded to collect the fungal mycelium. A mycelium weight of 0.18 g was placed in each flask and then incubated at 28°C on a rotary shaker (130 rpm) for ten days. After incubation, the culture medium was filtered through a pre- weighted paper filter (Whatman number 5), and the biomass was completely dried at 70°C for 8 h and weighted. The mycelium growth was estimated from the dry biomass of the samples collected in triplicate and compared to the control samples that were not exposed to the nanomaterials. All experiments were conducted in triplicate. The results were averaged out and standard deviations were calculated. The results were expressed in terms of mycelial reduction percentage, which was obtained from equation 2-1 as described below:

dried mass of the sample Mycelial reduction (%) = 100 − × 100. (Equation 2-1) dried mass of the control

2.2.4 Fungal morphological changes in the presence of G and GO

Morphological changes of the hyphae were observed using Scanning Electron Microscopy

(SEM) after interaction of the fungi with the nanomaterials. The mycelia of A. flavus and A. niger were grown in the same conditions and procedures as the growth inhibition experiment described earlier. After growth, the fungi were filtered from the growth culture and fixed with a

2.5% solution of glutaraldehyde prior to imaging. A solution of 2.5% glutaraldehyde was added immediately to a 2 mL Eppendorf tube containing the fungus to start the fixation. For fixation, 2 mL Eppendorf containing the fungi and the glutaraldehyde solution were incubated at 4oC for 24 h in the dark.213, 214 After 24 h, the fungal samples were washed for 15 min twice with a phosphate buffer solution (PBS, 0.2M, pH = 7.4, Sigma Aldrich, U.S.A.). The post-fixation was carried out by using 1% osmium tetra oxide (Sigma Aldrich) for 2 h at room temperature;

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followed by two washes with PBS. After washing, serial dehydration steps with ethanol/water

(v/v%) were carried out with 50% for 10 min, 70% for 10 min, 95% for 5 min and 100% ethanol for 1 min. Additional dehydration steps, with different ratios of acetone and ethanol, were conducted. The ratios were 1:2, 1:1 and 2:0 with 30s dehydration for each ratio repeated twice.

After fixation, the samples were allowed to dry and sputter coated with gold (Denton V, U.S.A) before SEM imaging at 15 kV voltage (JSM 6010LA, Jeol U.S.A.). The coating was performed in

40s at 45 mAmps, which produced a coating with a thickness of approximately 10 nm.

2.2.5 Apoptotic-like cell death

To determine the changes associated with apoptotic cell death in A. flavus and A. niger after treatment with G or GO, nuclear condensation and plasma membrane integrity were investigated as early and late apoptotic markers, respectively. The assays were performed based on the method described by Sharon.215 Briefly, staining solutions were prepared using Hoechst

33258 (Sigma-Aldrich, U.S.A.), for nuclear condensation as early apoptosis. The stock Hoechst

33258 is a nuclear staining solution, which was prepared at 1 g/L as a stock solution. The stock solution was freshly diluted to 0.5 g/L prior to use. In addition to the staining solutions, a fixation solution was also prepared freshly. The fixation solution contained 5% dimethyl sulfoxide (DMSO) and 3.7% formaldehyde in 1x PBS. The mounting solution was prepared with

50% glycerol and 0.1% n-propyl-gallate (Sigma) in 1x PBS then was divided into aliquots and stored at −20°C.

A suspension with a concentration of 3.5 x 105 spores/mL in Czapek growth medium was prepared using a hemocytometer from a 5 day-old-culture grown on a Czapek plate. A 100 µL volume of spores suspended in Czapek medium was then added in triplicate to sterile 22 mm x

22 mm glass cover slips and placed at the bottom of petri plate and incubated at 28° C for 5 h.

After 5 h, 100 µL solution of nanomaterials at a concentration of 200 mg/L was added to each

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cover slip. As control, 100 µL of sterile DI water was added to the control cover slips. The cover slips were further incubated at 28 oC for another 5 h before staining, washing and mounting the slides.215 After a total of 10h growth, for the nuclear condensation, a 500 µL fixation solution was gently added to the coverslips and then incubated at room temperature for 15 min to determine nuclear condensation. After that, the amount of 10 mL of 1x PBS was added to the plate and incubated for 5 min. Then, PBS was drained from the plate to wash out the fixation solution. This step was repeated twice. The coverslips were fixed with a fixation solution, then the nuclear staining solution (500 µL) was added to the coverslips and incubated for 5 min. After that, the coverslips were rinsed briefly with sterile water and dried by blotting the edge of the coverslips with Kimwipe. Finally, on the microscopic glass slide, 10 µL of mounting solution was added. The coverslips were placed on the mounting solution with the fungus facing down. The slides were then sealed with transparent nail polish for microscopic visualization. The slides were then observed under the fluorescence microscope to observe the changes in the nuclei. All images were acquired using BX 51 Olympus Fluorescence Microscope (Leeds Instrument Inc.) equipped with a DP72 digital camera and DAPI (4',6-diamidino-2-phenylindole) filter for the fluorescence images.

In the case of late apoptosis, Evan Blue (Sigma-Aldrich, U.S.A.) was used for investigation of the plasma integrity. A solution of 1% Evan Blue in 1x PBS was prepared prior the experiment.

The cover slip with the spore was prepared using the same procedure described above. After 10 h growth, the cover slips were stained with 1 mL of 1% Evan Blue and incubated for 5 min. After the incubation time, the washing and mounting process followed the same procedure as described in the early apoptosis procedure. The slides were then observed microscopically in bright field. Bright field images were taken to observe color changes of the hyphae related to

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late apoptosis. A total of 12 images for each sample were taken to observe the changes in the nuclei (early apoptosis) and hyphae (late apoptosis).

2.2.6 Thiol oxidation assay for reactive oxygen species (ROS)

The mechanism of toxicity by ROS was investigated using the Ellman’s assay. This experiment was conducted to investigate the ROS production released from the fungal hyphae.

The loss of thiols glutathione (GSH) was measured in this method to quantify ROS generation.35,

216 In 2mL tubes, the volume of 225 L of filtrate, which filtered through a 0.22 µm syringe filter

and 225 L of GSH were added (0.4 mM in 50 mM bicarbonate buffer (NaHCO3, pH = 8.6) and shaken at room temperature and 150 rpm for 2 h. The positive controls consisted of a solution of 30% hydrogen peroxide (H2O2) and the negative controls consisted of a bicarbonate buffer solution that does not produce any ROS. All the experiments were prepared in triplicate. The loss of GSH analysis was done following the procedure described in previous study.35

−. 2.2.7 Superoxide radical anion (퐎ퟐ )

The filtrate of the grown fungi in the presence and absence of G or GO was further

−. investigated for the release of O2 . The tetrazolium dye XTT (2,3-Bis(2-methoxy-4-nitro-5- sulfophenyl)-2H-tetrazolium-5-carboxanilide inner salt, Biotium, U.S.A.) was employed for the

−. measurement of O2 in the filtrate. To activate the XTT dye, 25 µL of phenazine methylsulfate was added to 5mL of XTT (Biotium provided protocol). XTT has been commonly used in studies of cellular responses due to stresses by producing superoxide anion.217, 218 In a 96-well plate, 25

µL of activated XTT and 75 µL of the fungi growth medium filtrate were mixed and the plates were kept in the dark for the total of 300 min. At the same time, wells of XTT without filtrate and the filtrate without XTT were prepared as negative controls. The positive controls with titanium dioxide (TiO2) were also prepared. They were placed in a dark box equipped with UV light (UV light activated, BLE-480B, Spectroline, U.S.A) to activate the oxygen species from TiO2

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during the experiment. The samples were taken every 30 min to read at the same time with all other samples. All the samples were read at 470 nm (Synergy MX Microtiter, Biotek, U.S.A) every 30 min for 300 min. The results of the absorbance were subtracted from the background noise of negative controls.

2.2.8 Fungi enzymatic production in the presence of G and GO

The effects of G and GO on extracellular enzymatic production were evaluated by API-ZYM® system (Bio-Mèrieux, Marcy l’Etoile, France). The filtrate from the mycelial growth inhibition assay was further filtered through a sterile 0.22 µm syringe filter (VWR, U.S.A.) and investigated immediately for enzymatic activity. Briefly, 65 μl of filtrate was added to each well of the API-

ZYM® system and incubated for 4 h in the dark at 30°C. Thereafter, a drop of ZYM A reagent (25 g of Tris–hydroxymethyl aminomethane + 11 ml of hydrochloric acid 37% + 10 g of sodium lauryl sulphate + 100 ml of H2O) and ZYM B reagent (0.12 g ‘Fast Blue BB’ + 40 ml of methanol + 60 ml dimethyl sulphoxide) were added to each well. The results were determined in nanomoles

(nmol) of hydrolyzed substrate according to the intensity of the color reaction on a scale of 1–5, i.e., 1 = 5 nmol, 2 = 10 nmol, 3 = 20 nmol, 4 = 30 nmol and 5 ≥ 40 nmol.219 All of the measurements were taken at least in duplicate, and sterile Czapek liquid medium was used as a negative control as suggested by the manufacturer Bio-Me´rieux, Marcy l’Etoile, France.

2.2.9 Production of volatile organic compounds (VOCs)

After following the same incubation procedure described in the mycelial growth section, the growth medium was collected and processed as previously reported by Pedrosa Costa et al

2016.205 The VOCs in the head space of the vials were analyzed using a solid phase microextraction (SPME) coupled with gas chromatography tandem mass spectrometry (MS) analysis according to the method described previously.220 The samples were initially held at 45

°C for 50 min followed by exposure to a SPME fiber (75 mm, carboxen/polydimethylsiloxane,

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CAR/PDMS) in the vial headspace. This procedure was optimized based on our preliminary investigations using different temperature and holding times.

The peak separation and detection was obtained using Agilent Hewlett-Packard 6890 GC gas-chromatograph equipped with a MS detector 5970 MSD (Hewlett-Packard, Geneva,

Switzerland). A fused silica capillary column CP-Wax 52 CB (50 m x 0.32 mm, Chrompack,

Middelburg, The Netherlands) coated with polyethylene glycol (film thickness 1.2 µm) was used as stationary phase. The injector and Flame Ionization Detector (FID) temperature were at 250

°C and the detector temperature was 220 °C. Helium was used as a carrier gas at flow rate of 1 mL/min. The GC oven temperature program began when the fiber was inserted and held at 40

°C for 2 min, then ramped to 200 °C at 10 °C per min and 200 °C to 250 °C at 15 °C per min and finally held at 250 °C for 5 min.

Volatile peak identification was carried out by computer identification of mass spectral data with those of the compounds contained in the Agilent Hewlett-Packard NIST 98 and Wiley version 6 mass spectral database (probability set at >90%). Positive identification of each chemical constituent was performed whenever possible by comparison with that of standard chemicals (Sigma Aldrich, Taufkirchen, Germany). The VOC quantities were expressed as relative area concentrations, and corrected taking into consideration the area of the compounds detected in non-inoculated controls.

2.3 RESULTS AND DISCUSSIONS

2.3.1 Characterizations of GO

To confirm the successful synthesis of GO, several characterization analyses were performed. X-ray diffraction patterns of GO and graphite are shown in Figure 2-1a. A sharp diffraction peak at 2Ɵ = 26.84° is observed for graphite, which corresponds to a d-spacing of

0.332 nm. On the other hand, GO exhibits a relatively broader diffraction peak at a lower angle

45

of 2Ɵ = 11.25°, with a corresponding d-spacing of 0.786 nm. The observed GO peak is due to graphite oxidation and is consistent with the known characteristic peak of GO,221 indicating that

GO was successfully synthesized. Also, the absence of peak is observed for GO at about 26°, suggesting full oxidation of the synthesized product.222 Furthermore, the observed increase in the d-spacing of GO compared to that of graphite can be attributed to the presence of oxygen- containing functional groups.221, 223 Because of these functional groups, water easily intercalates the layers of oxidized graphite, which also contributes to the increased d-spacing of GO.223

Raman spectroscopy was used to study the structural changes and configurations of graphite and GO, as shown in Figure 2-1b. The G band is assigned to first-order scattering of the

2 E2g from the sp hybridized carbon while the D bands is due to the defects or structural imperfections present on the graphite plane222, 223, both are used to characterize graphene- based materials. Characteristic G peak at 1580 cm-1 is observed for graphite, with an almost absent D peak suggesting no defects on the carbon basal plane. On the other hand, G and D peaks at 1602 and 1350 cm-1, respectively, are observed for GO, which are consistent with the well-known GO Raman peaks. The large D peak of GO denotes the significant presence of many functional groups formed.223

To investigate the functional groups present on the synthesized GO, FTIR analyses were performed. As shown in Figure 2-1c, graphite was successfully oxidized as indicated by the characteristic peaks at 3385, 1728, 1628, and 1053 cm-1 present in the IR spectrum of GO. These peaks are assigned to the O-H stretching of the hydroxyl groups, C=O stretching of the carboxyl groups, C=C on the hexagonal plane, and C-O of the epoxide groups, respectively.221, 222 The presence of these functional groups confirms that GO was synthesized successfully.

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a) b) G D

GO

GO (a.u.) Intensity Intensity (a.u.) Intensity Graphite Graphite

500 1000 1500 2000 2500 5 10 15 20 25 30 35 -1  Raman Shift (cm ) c)

Graphite

GO

% Transmittance % 3385 1628 1728 1053

4000 3500 3000 2500 2000 1500 1000 Wavenumbers (cm-1) d) O 1s e) GO C-C or C=C C 1s C 1s (284.8) O KLL C KLL GO C-O

(286.9)

C=O (288.5)

Graphite

1400 1200 1000 800 600 400 200 0 292 290 288 286 284 282 Binding Energy (eV) Binding Energy (eV)

Figure 2-1 (a) XRD, (b) Raman spectra of graphite and GO, (c) FTIR, (d) XPS wide scan and (e) C1s XPS of GO

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Finally, XPS analysis was also performed to investigate surface composition and to further confirm the FTIR results. Figure 2-1d shows wide scan spectra of graphite and GO, where a significant increase in the O1s peak of GO is observed. Calculated C/O atomic concentration ratios of 43.4 and 1.6 for graphite and GO, respectively, confirms the successful oxidation of graphite. Furthermore, figure 2-1e shows the deconvolution of the C1s core spectrum of GO.

Three peaks can be observed at binding energies of 284.8 eV (C-C/C=C), 286.9 eV (C-O), and

288.5 eV (C=O)224, which are in good agreement with the functional groups observed from the

FTIR analysis.

2.3.2 Effect of nanoparticles to morphological changes and growth inhibition of A. niger and A. flavus

The effects of concentrations of G and GO nanoparticles on the mycelial growth of the A. niger GM31 and A. flavus DSMZ62065 investigated after ten days of incubation are presented in

Figure 2-2. The results showed that the inhibitory effect of these nanomaterials depends on the type of nanoparticles and fungal species. Although the treatment of A. niger with G was statistically different from the control, 10 mg/L G was more toxic than 200 mg/L (Figure 2-2).

This lower toxicity at 200 mg/L G in growth media was probably due to the fact that G tends to aggregate and form large particles. The formation of large aggregates of G in the media was confirmed through particle size analysis (Figure 2-3). In higher concentrations of G, aggregation and precipitation of the nanoparticles are more pronounced (Figure 2-3). This could have led to reduced interaction of the nanoparticles with the hyphae and reduced toxicity. In the case of

GO, a significant inhibition (p < 0.05) of A. niger biomass was also observed in the presence of

GO, with an inhibition of 57% and 61% for 10 and 200 mg/L, respectively. The reduction in biomass was not significant between 10 and 200 mg/L of GO, meaning that the change in GO concentration did not affect the toxicity toward A. niger (Figure 2-2).

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A. flavus biomass was also reduced in the presence of both G and GO. The reduction of biomass at 10 and 200 mg/L was 11% and 62% for G and 41% and 50% for GO, respectively

(Figure 2-2). In the case of G, growth inhibition was dependent on the nanomaterial concentration, where higher G concentration had higher growth inhibition effect. Even though the two fungi are from the same genus, the results showed that A. niger was more sensitive to

GO and A. flavus was more sensitive to G. In the case of A. flavus, the aggregation of G in Czapek medium did not affect the G toxicity; it is possible that A. flavus hyphae interacted more strongly and faster with G than the rate of aggregation in the growth medium. This could be due to the different hyphae surface properties (e.g. hydrophobicity and functional groups) between the two organisms, which would generate different types of nanoparticle-hyphae interactions.

A. niger and A. flavus were previously reported to have different hyphae sizes, surface structures (hyphae and conidia) and shapes that could have led to different interactions to G or

GO.225.

b) 60 a) 60

40 40

20 20

0 0 10 200 10 200 Control Biomassreduction (% dried mass) 10 200 10 200 Control Graphene Graphene oxide Graphene Graphene oxide Concentrations (mg/L) Concentrations (mg/L) Figure 2-2 Biomass reduction (%) of (a) A. niger and (b) A. flavus after growing with and without nanomaterials in Czapek medium. The control is the sample without G or GO. Error bars correspond to standard deviations.

49

Czapek 10 Czapek 200 Graphene 10 mg/L 4x103 Graphene 200 mg/L Graphene oxide 10 mg/L 3x103 Graphene oxide 200 mg/L 3 b) 2x10 1x103

2 3x10 2 2x10 2 Zaverage (d. nm) 1x10

0 0h 2h 4h 6h 8h

Time (h) Figure 2-3 Zeta sizer of Czapek medium only (control) and different concentrations of G or GO in Czapek medium (Malvern Zetasizer, Nano ZSP, Malvern, U.S.A.). Error bars correspond to standard deviations.

The results show (Figure 2-2) that the toxicity behavior observed with A. flavus was very similar to Fusarium sp.9 In the Fusarium sp. study, it was suggested that the toxic mechanism was caused by the direct contact of the nanomaterial with the hyphae, as well as the attachment and wrapping of the nanoparticles to hyphae. In Figure 2-4, we clearly observe that

G attached to the A. flavus hyphae at 200 mg/L G. This phenomenon was not observed with 10 mg/L G and GO. The authors investigating Fusarium explained that this interaction could have caused lower oxygen uptaking by the fungi, which resulted in lower growth at higher nanomaterial concentrations. On the other hand, there was no observation of GO particles attached to the A. flavus hyphae (Figure 2-4), which suggested that the mechanism of GO toxicity could be different from G. In the case of A. niger, when treated with 200 mg/L of nanoparticles, the hyphae appeared abnormal, distorted, and many collapsed probably because of the outflow of intracellular components (Figure 2-4), inducing cell plasmolysis, but no direct attachment of the nanoparticles were observed like for A. flavus (Figure 2-4e). Therefore, the

50

growth inhibition observed for G to A. niger could have been caused by a different mechanism.

Based on these results, it is clear that G and GO have different toxicity mechanisms toward the two fungi and that the interactions of these nanomaterials with these microorganisms are also not similar. To further analyze the toxicity mechanisms, the fungal responses to stress factors were investigated using apoptosis responses of the hyphae.

a) d)

b) e)

c) f)

Figure 2-4 SEM images showing changes in morphology of hyphae: (a) A. niger control, (b) A. niger with G, (c) A. niger with GO, (d) A. flavus control, (e) A. flavus with G and (f) A. flavus with GO at 200 mg/L. Red arrow indicated the G attachment to the hyphae. Scale bar at 5 µm

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2.3.3 Apoptotic-like cell death responses in the presence of G or GO: mechanism of toxicity

Apoptosis is a well-defined process of programmed cell death activated in response to intrinsic and extrinsic factors including chemicals.206 One of the first morphological changes associated with apoptosis (also known as early apoptosis) is chromatin condensation that can be easily detected by Hoechst 33258 dye that labels nuclear material, followed by microscopic analysis. After treatment of G and GO to A. niger and A. flavus, both fungi exhibited apoptotic characteristics, such as nuclear and chromatin condensation as well as cell shrinkage (Figure 2-

5). In the control groups, the cells presented normal morphologies with intact nuclei (Figure 2-

5). These results suggest that G and GO induced apoptosis of the cells leading to cell death. It is well known that fungi undergo programmed cell death as part of the normal development and stress adaptation.226 Recent studies have shown that some compounds, such as polyenes, actually induce apoptotic cell death of pathogens, these results suggested that the antifungal materials could have conciliated by inducing apoptosis.210

In order to test whether the reduced growth of mycelia was due to cell death, the hyphae of both strains were stained with Evans blue and microscopically examined (as late apoptosis). As shown in Figure 2-6, the majority of the mycelia section was intensely stained in the presence of

G for both fungi, after 5 h exposure, which indicated the membrane was compromised. On the other hand, when A. niger grew in the presence of GO, the hyphae were stained in light blue, which means that membranes were not compromised (or were very little compromised) after 5 h (Figure 2-6). In the case of A. flavus with GO, the hyphae were stained with a deeper blue color than the control, which indicated damaged membrane after interacting with GO. These results suggested that the response of A. flavus was more severe than A. niger in the presence of the nanomaterials.

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Hence, these results showed that the treatment of G and GO resulted in accelerated cell death of some hyphae but not autolysis, probably due to direct contact of certain parts of the hyphae with these nanomaterials. Fungal autolysis is described as the process of self-digestion, happening on the very aged hyphae, where the active growth has stopped and organelle and cell wall structure are disrupted.227 Previous study presented evidence that apoptotic-like cell death and autolysis are separate biological processes regulated independently.228 The results showed that there were significant changes in the nuclei of the hyphae in early apoptosis of A. niger and A. flavus with G and GO. However, membrane damaged was only observed in the majority of the A niger hyphae while A. flavus was showing significant apoptosis on entire hyphae in late apoptosis for G and GO. Therefore, the apoptosis was dependent on the fungal strain. The different surface characteristics of A. niger and A. flavus could have been responsible for the different responses to G and GO even though they were exposed to the same conditions.225

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a) b) c)

d) e) f)

Figure 2-5 (a) Aspergillus flavus control, (b) Aspergillus flavus treated with G, (c) Aspergillus flavus treated with GO and (d) Aspergillus niger control, (e) Aspergillus niger treated with G, (f) Aspergillus niger treated with GO at 200 mg/L. The coverslips were stained with Hoechst 33258 and analyzed for early apoptosis. Scale bars, 10 µm and red arrow indicated the nuclear of the control and of the samples with nuclear condensed

54

a) b) c)

d) e) f)

Figure 2-6 (a) Aspergillus flavus control, (b) Aspergillus flavus treated with graphene, (c) Aspergillus flavus treated with GO and (d) Aspergillus niger control, (e) Aspergillus niger treated with graphene, (f) Aspergillus niger treated with GO at 200 mg/L. The coverslips were stained with Evans Blue and analyzed by bright-field microscopy (late apoptosis). Scale bars, 10 µm.

To further understand the responses of fungi in the presence of G and GO, the amount of reactive oxygen species (ROS) released by the hyphae as a sign of cellular stress was also investigated. When fungal cells are under stress or exposed to adverse conditions, such as

55

antibiotics or any kind of toxins, fungi tended to produce ROS as a defense mechanism to destroy and inhibit toxic chemicals or materials.229 This ROS production by the hyphae was also previously described to be involved in the apoptotic process of the cells, also known as cellular

210, 230 −. oxidative stress. Therefore, two kinds of ROS (H2O2 and O2 ) were measured using the filtrate from the media after fungal growth to investigate the potential release of these ROS by the hyphae. A. niger produced a significant amount of ROS as H2O2 in the filtrate of the samples exposed to 200 mg/L G, 10 and 200 mg/L GO (Figure 2-7a). At the same time, there was still

−. -1 some ROS in the form of O2 in the media for 10 and 200 mg L G (Figure 2-7b). In the case of A.

-1 flavus, there were also a significant amount of ROS produced as H2O2 after exposure to 10 mg L

−. G and small amounts of O2 in the growth media filtrate (Figure 2-8). These differences in forms

−. of ROS observed could have been due to the conversion of superoxide to H2O2 since O2 is an

231, 232 unstable intermediate product of H2O2. This production certainly triggered the apoptosis following broken cell-wall damage in the presence of G and GO.

b) 1.2 a) 100 G 10 mg/L 1.0 G 200 mg/L GO 10 mg/L 80 GO 200 mg/L 0.8 None G/GO TiO 2

60 0.6

40 0.4 OD (470 nm) OD 0.2 Lossof GSH(%) 20

0 0.0 10 + - 10 200 200 None G/GO 0 50 100 150 200 250 300

control G GO Time (minutes) Concentration (mg/L)

Figure 2-7 Aspergillus niger: reactive oxygen species productions (a) H2O2 express in term of loss of −. glutathione and (b) O2 expressed in term of absorbance 470 nm (Ellman’s assay) from the filtrate of the growth fungi under the presence of graphene or graphene oxide. These results were showing the responses of fungi under stress condition. Error bars correspond to standard deviations.

56

a) b) 1.2 100 G 10 mg/L G 200 mg/L 1.0 GO 10 mg/L 80 GO 200 mg/L 0.8 None G/GO TiO 60 2

0.6

40

(470 nm) OD 0.4

Lossof GSH(%) 20 0.2 0.0 0 + - 10 200 10 200 None G/GO 0 50 100 150 200 250 300 control G GO Time (minutes) Concentration (mg/L)

Figure 2-8 Aspergillus flavus: reactive oxygen species productions (a) hydrogen peroxide (H2O2) express in −. term of loss of glutathione and (b) superoxide anion (O2 ) expressed in term of absorbance (470 nm) from the filtrate of the growth fungi under the presence of graphene or graphene oxide. These results were showing the responses of fungi under stress condition. Error bars correspond to standard deviations.

2.3.4 Metabolic changes of A. niger and A. flavus in the presence of G and GO

The metabolic effects of G and GO on the two strains of fungi were also investigated to gain a better understanding on the toxic pathways of these nanomaterials. The investigation of the changes in metabolic pathways was done using two approaches: fungal production of extracellular enzymes and VOCs metabolomics. Extracellular enzymes are produced inside the cell then secreted to break down macromolecules or complex compounds, such as carbohydrates or organic phosphate into smaller or soluble compounds, which can be easily uptaken by the cells for growth and metabolism.233-235 In addition to extracellular enzymes, VOCs were also investigated since they are products of fungal metabolism.206 Fungi are well-known to respond to changes in the environment or lethal conditions by increasing or decreasing enzymes or VOCs for adaptation.236, 237 These two approaches aimed to give an overview of the changes in the metabolomics responses of these microorganisms.

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The enzymatic investigation for both fungi determined that the production of the enzymes acid phosphatase and Naphthol-ASBI phosphohydrolase were similarly affected by the presence of G. In the case of GO, Naphthol-ASBI phosphohydrolase production was reduced by half in both microorganisms, but in A. niger, the acid phosphatase production was completely inhibited

(Figure 2-9). The production of enzymes is typically linked to their growth medium and the need to break down the nutrients for uptake and growth. The phosphatase enzymes hydrolyze a variety of phosphate monoesters and are part of the energy metabolism, signal-transduction pathways or for the acquisition of phosphorus for growth.238 The reduction of this enzyme correlates well with the reduction in fungal biomass, most likely the toxicity of the nanoparticles interfered in the metabolic activity of these microorganisms. The other enzyme, Naphthol-ASBI phosphohydrolase, is essential for the development of fungal diseases and is commonly found to be dominant in isolates of hospital patients.239 This enzyme is commonly indentified in studies of enzymatic characterization of microorganisms such as fungi and is also suspected to be involved in housekeeping activities, which is essential for microbial survival.240-242 The reduction of these two important enzymes indicates that the presence of the nanomaterials can affect the normal fungus enzymatic activity, which could also have affected the fungal growth (Figure 2-9).

In addition to these two enzymes, A. flavus, also produced β-galactosidase and β- glucosidase under normal growth, but their production were affected by the presence of G and

GO (Figure 2-9). β-glucosidase is involved in the catalytic reaction of transglucosidation for solubilization of insoluble glucose to enhance cell uptake .243 This enzyme and β-galactosidase are also involved in diverse growth processes, such as the germination of conidia and tip growth of hyphae.244, 245 In addition, β-galactosidase is also involved in hydrolysis of lactose into glucose and galactose.246 The inhibition of the production of these two enzymes would affect directly fungal growth. These results corroborate the fact that these fungi have different responses to

58

the presence of these nanomaterials and that these nanomaterials can have adverse effects in enzymes essential to the growth and metabolic activity of these fungi.

Acid Phosphatase

Acid Phosphatase Naphthol-As-BI-phosphohydrolase Naphthol-As-BI-phosphohydrolase ß-galactosidase 20 30 ß-glucosidase Aspergillus niger 25 Aspergillus flavus 15 20

10 15

10 5

* 5 * ** * * 0 0

Hydrolyzedsubstrate (nmole) Control G GO Control G GO * No enzyme activity

Figure 2-9 Enzymatic productions of secreted enzymes by (a) A. niger and (b) A. flavus after growth with G and GO at 200 mg/L. The (*) meaning that no enzymatic production was observed. Standard deviations are presented, but they were negligible in the figure since the results of the replicates were identical.

In addition to the enzymatic activity, fungi also produce a mixture of volatile compounds that are very important to the fungus metabolic activity. Volatile organic compounds (VOCs) represent a significant portion of the fungal metabolome and has been demonstrated to provide information in real-time about metabolic changes that occur within the fungal cell.247 These

VOCs are also described to change under stress conditions and hence it is relevant to investigate their changes in the presence of nanomaterials.248-250 In this study, we determined that both fungi produced a number of VOCs comprising of alcohols, esters, ketones, acids, aldehydes and terpenes as well as hydrocarbons.205 These groups of VOCs are commonly found in microbial

VOC investigations, but their derivative compounds depend on the fungal strains and growth conditions .206 The profiles of VOCs relative to the controls of A. niger and A. flavus were very different (Table 2-1). Particularly, A. flavus VOCs were more diverse for alcohols (10), terpenes

(21) and hydrocarbons (6) than A. niger (Table 2-1). This different VOC profiles between the two

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strains is not surprising since VOCs are strain dependent. However, changes in the VOC patterns in the presence of stressors, such as nanomaterials, could shed some lights on the impact of these nanomaterials in fungal metabolism.

The A. niger VOC profile of treated samples with nanomaterials and non-treated showed significant differences (p < 0.05) (Table 2-2). The most affected compounds were alcohols, esters, ketones and aldehydes for A. niger in both G and GO. For instant in alcohols, 3-Methyl-1- butanol was detected in high concentrations in the control samples (408 x 106), but it was significantly reduced in the presence of G (15.77 x 106) and GO (17 x 106) (Table 2-1). This VOC compound was reported in molds in water-damaged houses and has been suggested to have potentially adverse health effects.206 This compound was also identified as one of the molecular biomarkers of the existence of A. niger during its normal growth.205 Changes in this VOC indicate abnormal growth, which corroborates our initial morphological findings. Besides this compound, ethyl-alcohol also had significant reduced production in the presence of the nanomaterials. This compound is also abundantly found in fungal VOC profiles.220 The significant reduction of this

VOC is probably due to the lower metabolic activity of the fungi observed earlier. In fungi, alcohols and aldehydes are reported to be associated with fatty acid metabolism and degradation of aromatic compounds; while ketones and esters are related to biosynthesis of fatty acid.249, 251-253 The presence of the nanomaterials also triggered the synthesis of other

VOCs, such as alcohols (4-methyl-1-penten-3-ol and 5,9-Dimethyl-1-decanol) in presence of G and hydrocarbons (pentane -3,3, dimethyl and 4-methyl hexadecane) in presence of G and GO.

The synthesis of these compounds could be a response to the toxic effects of the nanomaterials, and could potentially serve as biomarkers for these strains. In particularly, the appearance of propanoic acid in fungi exposed to G and GO and 2-ethyl hexanoic acid in G treated samples could be indicative of toxicity to A. niger. These two acids were previously reported to have

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antifungal properties and to inhibit mycelia growth.220, 254, 255 This could indicate that the fungus is self-regulating its growth by producing these two compounds.

In the case of A. flavus, the treatments reduced significantly (p < 0.05) alcohols, esters, terpenes and ketones (Table 1). Similarly to A. niger, 3-Methyl-1-butanol and ethyl alcohol were reduced significantly, which contributed to the overall reduction in the alcohol group (Table S1).

Terpenes in A. flavus were also affected significantly in the presence of nanomaterials (Table 2-

2). For instance, ɣ -cadinene synthesis reduced from 254 x 106 to 71 x 106 and to 115 x 106 for G and GO, respectively (Table 2-1). This compound is commonly produced by A. flavus.256, 257 In addition to the reduction of this compound, there were compounds that were only produced in the presence of G or GO namely: 2, 4-dimethyl-1-heptene and 3,3-dimethyl-1-butanol, respectively. Noticeably, aldehydes were not observed in A. flavus and terpenes were observed abundantly in A. flavus. In previous studies, terpenes were reported to be involved in the backbone synthesis of cells.205, 249, 258. It is well established that sesquiterpenes is produced in the late growth phase and their production is modulated by enzymes, which are induced by environmental stress factors.259 Therefore, it is possible that the enhanced or reduced of sesquiterpenes could be related to a stress response due to the presence of G or GO. The results demonstrated that the two strains of fungi had different responses in terms of VOC production patterns in the presence of G and GO. These results also suggested that the fungal VOCs profile was nanoparticle and strain dependent.

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Table 2-1 Volatile compounds (area relative x 106) detected in the head space of the Aspergillus sp. cultures grown in liquid Czapek medium at 28°C for 10 days.

Aspergillus niger Aspergillus flavus Control G GO Control G GO Alcohols a b b Ethyl-alcohol 325.59a n.r n.r 154.58 54.59 67.06 b b a b b 3-Methyl-1-butanol 408.22a 15.77 16.82 19.50 27.91 16.81 a a a 3,3-Dimethyl-1-butanol 3.24a 1.08 3.82 n.r n.r 2.26 4-methyl-1-penten-3-ol n.r 4.68 n.r 13.00a 0.98a n.r 2-Ethyl-1-hexanol 20.05a 0.68b 8.77c 1.65a 3.03a 3.20a 2-hexanol-2,5-Dimethyl n.r 4.47a 0.49b 5.99a 5.20a 8.71a 3,5,5-trimethyl-1-hexanol 3.99 n.r n.r 48.86a 47.14a 86.07a 3,7-Dimethyl-1,6-octadien-3-ol 1.47a 0.86b n.r 0.08 n.r n.r Phenyl-ethyl-alcohol 21.64a 23.14a 29.04a 2.12a 3.68a 3.31a 5,9-Dimethyl-1-decanol n.r 9.02 n.r 7.04a 8.37a 10.37a 2,6-di-tert-butyl-4-sec- n.r n.r n.r 27.26a 5.16b 13.48a a Totalbutylphenol 784.20 59.7b 58.94 280.08 156.06b 211.27b a b a

Ketones 3-heptanone -6-methyl n.r n.r n.r 15.13 n.r n.r Acetophenone 8.69 n.r n.r 1.15 n.r n.r Total 8.69 n.r n.r 16.28 n.r n.r

Aldehydes 2-octenal 2-buthyl 10.87 n.r n.r n.r n.r n.r Total 18.48 n.r n.r n.r n.r n.r Esters Methyl 3-methylbutanoate 11.00 n.r n.r 3.54 n.r n.r Methyl 2-methyl butanoate 89.84 n.r n.r 1.26 n.r n.r Ethyl 2-methyl butanoate 32.91 n.r n.r 0.12 n.r n.r 2-Ethyl-1-hexanol acetate 2.53 n.r n.r 0.15 n.r n.r 2-Phenylethyl acetate 2.87 n.r n.r 0.092 n.r n.r Ethy-9-decenoate 3.83a 1.44a n.r 0.155 n.r n.r Ethyl n-hexadecanoate 3.23 n.r n.r 5.63 n.r n.r Methyl 4- decenoate n.r n.r 0.98 10.55 n.r n.r Ethyl octadec-9-enoate 10.82a n.r n.r n.r n.r n.r Total 157.03 1.44b 0.98b 21.49 n.r n.r a

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Table 2-1 (Continued) Aspergillus niger Aspergillus flavus Control G GO Control G GO

Hydrocarbons Pentane -3,3, dimethyl n.r 23.01a 13.19a 2.74a n.r 7.43 2, pentene 2,3,-dimethyl 9.43a 10.07a 9.48a 9.84a 9.39a 14.39b 2,4-dimethyl-1-heptene n.r 0.72 n.r n.r 3.17 0 1-pentene, 2,4,4-trimethyl 0.44a 6.14a 3.02a 3.91a 4.56a 5.07a Decane 48.27a 7.55b 3.08b n.r n.r n.r 4-methyl hexadecane n.r 4.08a 4.90a n.r n.r n.r Nonadecane n.r n.r n.r 9.24a n.r 0.91b Eicosane 2 methyl n.r 6.48 n.r 4.46a n.r 8.27a Heptacosane 1.09a 21.30b n.r 1.14a n.r 0.74a Total 59.23ab 79.35a 33.67ab 31.33a 17.12a 36.81a

Acids Acetic acid n.r n.r n.r 0.38 n.r n.r Propanoic acid n.r 0.36 0.61 n.r n.r n.r 2-ethylhexanoic acid n.r 3.28 n.r n.r n.r n.r Decanoic acid n.r 13.32 n.r n.r n.r n.r Total n.r 16.96a 0.61b 0.38 n.r n.r Terpenes 0-cymene n.r 4.37a 2.72a 0.24 n.r n.r Isoledene n.r 0.19 n.r 6.77a 3.53a 1.17a Cadinene n.r 0.17 n.r 83.17 n.r n.r Cubenol n.r n.r 1.51 59.44a 28.40a 3.79b trans-caren-hexen-ol 4.10a 5.85a 5.30b 6.89a 4.41a n.r o-menthan-8-ol 0.14 n.r n.r n.r n.r n.r β -Elemene n.r n.r n.r 8.96a 5.44a 7.65a ɣ-Gurjunene n.r n.r n.r 6.04a 4.27a 5.53a E-farnesene 1.12a 6.86a 0.57b n.r n.r n.r Neoisolongifolene n.r n.r n.r 30.19a 17.04b 10.50b t-muurolol n.r n.r n.r 24.67ab 16.01a 52.77b α- muuroolol n.r n.r n.r 6.95a 5.70a 12.72b t-cadinol n.r n.r n.r 35.78a 13.63a 83.35b cadalene n.r n.r n.r 2.08a n.r 3.44a trans-farnesol n.r n.r n.r 77.09a 73.76a 81.10a ɣ -cadinene n.r n.r n.r 253.65a 70.64b 114.532a a-muurolene n.r n.r n.r 13.60 n.r n.r

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Table 2.1 (continued) Aspergillus niger Aspergillus flavus Control G GO Control G GO Terpenes a a a β-hymachalene n.r n.r n.r 13.91 12.34 18.98 a b α-copaene n.r n.r n.r 0.03 n.r 9.30 a a α-calacorene n.r n.r n.r 0.95 n.r 4.94 longifolene n.r n.r n.r 13.84a n.r 3.18b 1.3.8-p-menthatriene 1.22a 1.14a n.r 1.15a 0.91a 2.27a Total 6.58a 18.58b 10.1ab 645.4a 256.08b 412.04b a), b): statistically significant different in comparison to the control; nr: under detection limit

Table 2-2 Principal chemical groups of volatile compounds (area relative x 106) detected in the head space of the Aspergillus sp. cultures grown in liquid Czapek medium at 28°C for 10 days

Aspergillus niger Aspergillus flavus

Control G GO Control G GO

Alcohols 784.20a 59.7b 58.94b 280.08a 156.06b 211.27b

Ketones 8.69 n.r n.r 16.28 n.r n.r Aldehydes 18.48 n.r n.r n.r n.r n.r Esters 157.03a 1.44b 0.98b 21.49 n.r n.r Hydrocarbons 59.23ab 79.35a 33.67ab 31.33a 17.12a 36.81a Acids n.r 16.96a 0.61b 0.38 n.r n.r Terpenes 6.58a 18.58b 10.1ab 645.4a 256.08b 412.04b a), b): statistically significant different in comparison to the control; nr: under detection limit

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2.4 CONCLUSIONS

In the present study, graphene and graphene oxide showed antifungal properties toward A. niger and A. flavus. The latter was more sensitive to both nanomaterials. Overall, the results showed that the presence of graphene and graphene oxide led to growth inhibition, apoptotic- like responses and changes in volatile organic compounds and enzymatic production. These reductions in synthesis of enzymes and essential volatile organic compounds were attributed to the lower metabolism of the fungi exposed to the nanomaterials. A few volatile organic compounds biomarkers were uniquely expressed in the presence of graphene and graphene oxide and appeared to be linked to essential metabolic activities. All of these results suggest that the antifungal mechanisms of graphene and graphene oxide are not the same for the different fungus and involve a complex combination of hyphae membrane damage as well as changes in enzyme synthesis and volatile organic compound production.

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CHAPTER 3 POLYMERIC ADHESIVE NANOCOMPOSITES OF GRAPHENE AND GRAPHENE OXIDE FOR BIOMEDICAL APPLICATION “Adapted with permission from (Nguyen, Hang N., Nadres, Enrico T., Alamani, Bryan G. and Rodrigues, Debora F. “Designing Polymeric Adhesives for Antimicrobial Materials: Poly(ethylene imine) Polymer, Graphene, Graphene Oxide and Molybdenum Trioxide - A biomimetic Approach.” Journal of Materials Chemistry B (2017) DOI: 10.1039/C7TB00722A (Invited paper).”

3.1 RATIONALE AND OBJECTIVES

The strong adhesive properties of the sticky byssus of the freshwater zebra mussels have inspired many researchers to synthesize catechol-containing adhesive bio-polymers, such as poly[(dopamine methacrylamide)-stat-(2-methoxy acrylate)-stat-(ethylene glycol dimethacrylate) ((C12H15NO3)-stat-(C6H10O3)-stat-(C10H14O4)), which is known to be as strong as commercial preparations of Krazy Glue® and Epoxy®.260 17, 261 These bio-inspired polymers are also known to exhibit excellent adhesiveness to a variety of surfaces, ranging from smooth organic surfaces of polytetrafluoroethylene to roughened inorganic surfaces.262 Like the byssus proteins, the effectiveness of these other bioinspired catechol-containing polymers are mainly due to the binding properties of the catechol groups.263

Previous studies using simple polymerization of dopamine at basic pH showed that these adhesives can be useful in many medical applications, such as soft tissue attachment and bone repair.264 The major drawbacks of using only poly-dopamine and most of the current bioinspired adhesive polymers are twofold. First, these polymers do not present anti-microbial properties and therefore can be a source of nosocomial infections, which affect per year 2 million people and add more than $5 billion in medical costs. Second, the incorporation of anti-microbial components in these polymers is very difficult due to specific pH and solvent requirements. For instance, the occurrence of polymerization of dopamine occurs in aqueous solutions, which would prevent easy synthesis of composites with anti-microbial properties that require organic solvents.

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Our strategy was to synthesize polymeric adhesives whose design was based on the catechol-rich proteins of mussel byssus. Since the catechol side chains of the proteins are responsible for the adhesive properties of the mussel byssus, the incorporation of monomers with catechol side chains in the newly designed polymers resulted into adhesive polymers with similar adhesive property to the mussel byssus. The adhesive polymer, in turn was used to bind surfaces and different anti-microbial materials together to generate an antimicrobial surface.

The antimicrobials selected for this investigation was nanoparticles of G and GO (GO). These antimicrobials were selected for this study because they have distinct properties, compositions, origins, and have been demonstrated to possess antimicrobial properties.5, 76, 153 Furthermore, these antimicrobials, neither G nor GO are soluble or can be easily suspended in water, hence their coatings are not very stable for long time periods unless they are “glued” to the surfaces.

The main scientific question was whether an adhesive material would work with different types of antimicrobials.

In this study, G and GO were used to investigate the nanoparticle interactions with the bio- inspired adhesive polymers. The rationale for selecting these nanomaterials was because they have been previously described to be potent antimicrobials against antibiotic resistant microorganisms, including Methicillin-resistant Staphylococcus aureus. In the past years, polymer nanocomposites have also been showing promise as safer anti-microbial agents as opposed to their pristine counterparts.6, 10, 12 For instance, nanocomposites of G and GO showed superior antimicrobial properties then their pure counterparts as well as negligible mammalian cytotoxicity.6, 12, 15

In this study, we synthesized four different types of polymer adhesives that contain catechol groups mimicking the adhesiveness of the mussel adhesive proteins. The synthetic adhesive polymers were then used to deposit anti-microbial nanoparticles G and GO onto surfaces. Our

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strategy differs significantly from the accepted standard coating procedures since current deposition techniques rely mostly on activation of either the surface or material to be deposited. In our strategy, modification of the surface or antimicrobial material is not necessary, since the antimicrobial materials can be used directly without any chemical derivatization or functionalization. Upon mixing the nanomaterials with the polymers, the resulting composite can be coated onto diverse surfaces directly. This strategy greatly simplifies the deposition of soluble or suspendible materials. With this strategy, we aim to produce antimicrobial coatings consisting of graphene-based polymer nanocomposites with antimicrobial properties, but safe for humans. The antimicrobial composites coatings were characterized and investigated for initial cell attachment, anti-biofilm activity and human cytotoxicity. The stability of the coatings was also investigated using leaching assays.

3.2 MATERIALS AND METHODS

3.2.1 Dopamine methacrylamide

In preparation of Dopamine methacrylamide (DMA), the 3-hydroxytyramine HCl (42 mmol, 8 g) was mixed with 75 mL anhydrous methanol in a nitrogen-purged 250 ml round bottom flask with a magnetic stir bar. Triethylamine (43.2 mmol, 6.0 mL) was then added and the solution was stirred at 0 oC. Methacryloyl chloride (5.85 mmol, 6.0 mL) was then injected in the flask.

Another portion of triethylamine (43.2 mmol, 6.0 mL) was added. The solution was stirred under room temperature for 16 h. The product was isolated by removing most of the methanol with a rotavap. The thick residue was extracted with ethyl acetate (3 X 100 mL). The organic layers were combined and washed with HCl solution (1N, 3 X 100 mL), followed by washing with saturated sodium chloride (100 mL) and then dried with magnesium sulfate. The filtered solution was concentrated to about 100 mL and the solution was stored in freezer overnight to precipitate the DMA product. The white crystal products were filtered, washed with cold ethyl

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acetate and dried. The identity of the product was confirmed by proton NMR analysis. 1H NMR

(DMSO-d6, 400 MHz) δ 8.7–8.6 (2H), 7.9 (1H), 6.5–6.6 (2H), 6.42 (1H), 5.61 (1H), 5.30 (1H), 3.21

(2H), 2.55 (2H), 1.84 (3H).

3.2.2 Synthesis of adhesive polymers

The synthesis of the adhesives was done via free radical polymerization of DMA with other monomers.265 The other monomers used were 2-methoxyethyl acrylate (Polymer A), no copolymer (Polymer B), ethyl methacrylate (Polymer C), and 2-hydroxyethyl methacrylate

(Polymer D). Typically, a 1.5 mmol of DMA (1.5 mmol, 332 mg), 8.5 mmol of the other monomer

(either A, C or D) and 2,2’-azobisisobutyronitrile (AIBN, 1.0 mmol, 164 mg) were dissolve in dimethylformamide (DMF, 5 mL). The solution was bubbled with N2 for 5 min and heated at 60

°C for 16 h. The product was isolated by addition of methylene chloride to the cooled reaction mixture, followed by dropwise addition of the resulting mixture to hexane (200 mL) to induce precipitation of the polymer. The polymer precipitate was obtained after centrifugation (5000 rpm, 10 min). The precipitate was dissolved in dichloromethane (5 mL) and reprecipitated in hexane. The polymer precipitation was done twice. Finally the polymers were dried under vacuum. The molecular weight of the polymers was determined using gel permeation chromatography and the confirmation of the structure was done using nuclear magnetic resonance instrument. Please see details below for the synthetic procedure for Polymers A–D.

Polymer A. Poly(DMA-co-MEA). DMA (1.5 mmol, 332 mg), 2-methoxyethyl acrylate (MEA,

8.5 mmol, 1.10 mL), (AIBN, 1.0 mmol, 164 mg) and DMF (5 mL) were mixed in a vial with septum, degassed and mixed at 60 °C for 16 h. After purification, the yield was 1.03 g. The polymer was analysed by NMR. 1NMR (CDCl , 500 MHz) (m), 4.18 (br s), 3.55 (br s), 3

3.34 (br s), 2.79–2.53 (m), 2.45–2.16 (m), 2.08 (br s), 1.91 (br s), 1.79–1.22 (m), 1.09–0.78 (m).

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Polymer B. Poly-DMA. DMA (5.0 mmol, 1.10 g), AIBN (0.5 mmol, 82 mg) and DMF (2.5 mL) were mixed in a vial with septum were mixed in a vial with septum, degassed and mixed at 60

°C for 16 h. The polymer product was isolated by the addition of dichloromethane (2.5 mL) to the cooled reaction mixture followed by adding the resulting solution drop wise to excess hexane (100 mL). After purification, the yield was 1.30 g. The structure of the polymer was confirmed by NMR analysis. 1H NMR (DMSO-D6, 500 MHzm), 7.35 (br s), 6.68–

6.24 (m), 3.05 (br s), 2.44–2.40 (m), 1.73–1.26 (m), 1.05–0.88 (m).

Polymer C. Poly-(EMA-co-DMA). DMA (1.5 mmol, 332 mg), ethyl methacrylate (EMA, 8.5 mmol, 1.06 mL, AIBN (1.0 mmol, 164 mg) and DMF (5 mL) was mixed in a vial with septum, degassed and mixed at 60 °C for 16 h. After purification, the yield was 1.20 g. The structure of the polymer was confirmed by NMR analysis. 1H NMR (CDCl3, 500 MHz) m), 4.03

(br s), 3.44 (br s), 2.69 (br s), 2.18–1.65 (m), 1.16–0.79 (m).

Polymer D. Poly-(HEMA-co-DMA). DMA (1.5 mmol, 332 mg), 2-hydroxyethyl methacrylate

(HEMA, 8.5 mmol, 1.03 mL), AIBN (1.0 mmol, 164 mg) and DMF (5 mL) was mixed in a vial with septum. The mixture was bubbled with nitrogen for 5 min and then stirred at 60 oC overnight, degassed and mixed at 60 °C for 16 h. The polymer product was isolated by adding methanol

(2 mL) to the cooled reaction mixture followed by dropwise addition of the resulting mixture to excess diethyl ether (200 mL). The collected polymers were dried under vacuum (yield, 1.20 g).

1NMR (DMSO-d6, 500 MHzm7.71–7.36 (m), 6.66–6.28 (m), 4.79 (br s), 3.86 (br s), 3.03 (br s), 2.44–2.43 (m), 2.08–1.50 (m), 1.02–0.8 (m).

3.2.3 Fabrication and characterization of the coated slides

Stocks of 1000 ppm of adhesive polymer (Polymers A–D) solutions were prepared by dissolving the polymers in solvents (absolute ethanol for polymer A, DMF for Polymers B–D), followed by sonication for 10 min (Branson CPXH Series Ultrasonic Tabletop, model CPX5800H-

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E). In another set of vials, 1000 mg/L mixture of antimicrobial agents was prepared by suspending G or GO in corresponding solvents (absolute ethanol or DMF followed by sonication for 30 mins. For each adhesive polymer solution, different proportions (25, 50, 75 and 85 %) of each antimicrobial agent (G or GO) were added to give an adhesive concentration of 250, 500,

750 and 850 mg/L, respectively. The resulting mixtures were sonicated further for 10 min prior to application as coatings.

Small pieces of glass slides (1.0 cm X 2.5 cm) were cleaned by sonicating in 2-propanol followed by rinsing with DI water and dried at 105°C. The glass slides were cooled and loaded into the spin coater. The prepared mixture was dropped in the center of the glass slide and the spin coater was started (initial spin 30 rpm, 10 s; final spin, 3000 rpm, 50 s). The coatings on the glass slides were then annealed in oven at 70 °C for 16 h. The coated glass slides were characterized and assayed for microbial activity. The best antimicrobial results obtained for each type of antimicrobial adhesive nanocomposites were selected for further investigation.

The characterizations of the coatings were carried on with the samples resulting in higher antimicrobial properties (Figure 3-2 and 3-3). The static sessile drop contact angle of water in uncoated and coated glass slides were determined.266 Briefly, a droplet on the surface was generated with a syringe held vertically to the surface. A high resolution camera was used to capture the images of the droplets followed by analysis with ImageJ.267 Briefly, all the images were converted to black and white images. Then, the Drop analysis LB-ADSA in Plugin of ImageJ was used to obtain the contact angles of the droplets. All the measurement was done in triplicate for triplicate samples and the average and standard deviations were calculated.

Scanning Electron Microscopy (SEM, Leo 1525 Gemini Zeiss) was used to take the images of the nanoparticles on coated surfaces.

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3.2.3 Leaching test of the adhesive coatings

These experiments were performed in order to show that the coatings are stable and not leaching any toxic components to the test solutions. Uncoated and coated glass slides were placed in 6-well plates containing 5 mL of sterile phosphate buffered saline solution (PBS, pH =

7.4, Sigma Aldrich, U.S.A.). The plate was incubated at for 7 d at 37 oC. Then, the PBS solution was withdrawn from the wells and tested for E. coli toxicity. Briefly, in a 2 mL Eppendorf, 900 µL of the PBS leachate and 100 µL of E. coli suspension (0.2 of OD600) were mixed and incubated at

35°C for 2 h. Serial dilutions were performed after the incubation period and the microorganisms were plated on tryptic soy agar plate (TSA, Oxoid, U.S.A.) in triplicate. The plates were incubated at 35°C for 12 h and the colony forming units (CFU/mL) were determined.

After the leaching test, the coated slides were characterized again using SEM to confirm the coatings were still intact. Ellipsometry (Gaertner, model LSE – USB, U.S.A.) was also used to determine any changes in thickness of the coatings after the leaching test.

3.2.4 Bacterial suspension preparation

Antimicrobial experiments were carried out using Gram-negative (Escherichia coli MG 1655 and Pseudomonas aeruginosa) and Gram-positive (Bacillus subtilis 102 and Staphylococcus epidermidis) microorganisms. A 16 h culture was freshly prepared each time in tryptic soy broth

(TSB, Oxoid, U.S.A.). All the growth was conducted at 35 oC while shaking at 150 rpm

(ThermoFisher, U.S.A). To harvest the cells, the growth medium was centrifuged at 10,000 rpm for 5 min, and then rinsed twice using PBS, thereby completely removing the TSB media. The bacterial pellet was then re-suspended in PBS at 0.05 optical density of 600nm (OD600), which corresponds to 5 x 104 CFU/mL.

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3.2.5 Live/dead assay

Each coated slide was rinsed with PBS and 70% ethanol following by air-drying under the sterile biosafety hood before placing at the bottom of sterile 6-well plates (BioLite, U.S.A.).

Control samples, such as the uncoated glass slides and slides coated only with the adhesive polymers investigated, followed the same procedure as the investigated samples. An aliquot of

4 mL bacterial suspension was added to each well to fully cover the coated slides, and then the plate was incubated at 35oC for 1h and 2h without shaking. After the incubation period, the slides were removed using a sterile tweezer. The LIVE/DEAD Baclight bacterial viability kit

(Invitrogen, U.S.A), which contains SYTO9 and propidium iodide (PI) dyes was used to investigate for membrane disruption caused by the antimicrobial coatings. The staining procedure was explained in our previous study.5 The fluorescent images at 40x objective were taken using

Olympus microscope (BX 51 Olympus Fluorescent Microscope) equipped with DP72 digital camera and Fluorescein isothiocyanate (FITC) filter. All the experiments were performed in triplicate. The results were calculated from the equation 3-1, and then the averages and standard deviations were obtained. The t-test was used to determine statistically significance of the results. The equation 3-1 was described below:

Number of dead cells (Red) Dead cells (%) = x 100. (Equation 3-1) Number of total cells (Green)

3.2.6 Fixation of bacterial samples for Scanning Electron Microscopy images

SEM images of B. subtilis and E. coli were obtained on the surface of uncoated and coated slides. The same procedure as the Live/dead assay with a 2 h incubation time was followed to obtain the cell initial attachment to the surfaces. After incubation, the slides were removed with sterile tweezers to proceed to the fixation immediately. A 200 µL solution of 2% glutaraldehyde in 0.05 M Cacodylate buffer was added to completely cover the slide surface.

The details of the fixation, post-fixation with 1% osmium tetraoxide and washing can be found in

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our previous study.268 Finally, the slides were coated with gold at 0.05 Torr, 40 mAmps in 40s

(Denton V Desk Sputter). The images were acquired using a scanning electron microscope (JSM

6010LA, Jeol U.S.A.).

3.2.7 Biofilm assay using confocal images

Bacterial cultures were grown in TSB for 16 h at 35oC. Coated and uncoated glass slides were placed in 6-well plates and 100 µL of the diluted bacterial suspension and 6 mL of growth medium were added to each well. All the plates were incubated at 35 oC for 72 h. The z-stack images of the biofilms were acquired using Leica Confocal (10x/0.3 HCPL FLUOTAR, LEICA TCS

SPE). The images were analyzed using Comstat 2.1.2 to obtain the biomass and maximum thickness.269 Six images were taken for each sample and the experiments were done in triplicate.

The results were averaged for all results and standard deviations were also obtained.

3.2.8 Cytotoxicity of the coatings against human corneal epithelial cell

The human cytotoxicity was performed using the PBS solution after the leaching experiment as previously described.268 The CellTiter 96 Aqueous One Solution Cell Proliferation Assay kit

(Promega, USA) and immortalized human corneal epithelial cell line (hTCEpi) in KBM-2 complete media (Lonza, U.S.A Catalog# CC-3107) were used in this experiment to investigate the safety of

PBS solution that was in contact with the coated glass slides. Briefly, hTCEpi cells with density of

30 x 104 cells per mL were prepared from a 48 h culture flask (passage number 48). Then, aliquots of cell suspension (100 µL) were added to the wells containing 100 µL of test solutions:

PBS from leaching experiment, negative control (sterile PBS) or positive control (0.02% of benzalkonium chloride, BAC). At the same time, the wells with KBM medium without cells were prepared for each sample to subtract the background. The plates were incubated at 37 oC with

5% CO2 humidified incubator (NuAire, U.S.A) for 24 h. All the samples were prepared in triplicate. After 24 h, the wells were washed three times with sterile PBS. The CellTiter reagent

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and KBM were added to the wells and then incubated for another 3 h before reading the fluorescence at 490 nm (FLUOstar Omega, BMG Labtech, Germany). The percentages of living cells were then calculated. The results were averaged and standard deviations were also obtained.

The growth of hTCEpi cell line on the surface of glass slides coated with adhesive and G or

GO were also investigated. In this experiment, the Live/Dead Cell Imaging kit (R37601,

Invitrogen, U.S.A) was employed to determine any damage to the cells in contact with the coated surfaces. A concentration of 30 x 104 of hTCEpi cells per mL was prepared as described above. The coated slides and a negative control (glass slide only) were placed in a sterile 6-well plate. Then, 3 mL of cell suspension was introduced and the cell culture was incubated at 37 oC for 16 h. After 16h, the slides were removed from the wells using a sterile tweezer; and then, a

10 µL of dye was added over the slides and incubated at room temperature for 5 min. The staining dye mixture was prepared following the manufacture’s protocol.270 The fluorescent images were taken using confocal microscopy (10x/0.3 HCPL FLUOTAR, LEICA TCS SPE).

Additionally, the images were also taken using the Olympus microscope (BX 51 Olympus

Fluorescent Microscope) for viable cell counts. A positive control was also prepared from the uncoated glass slides after 16 h cell incubation. This positive control followed a treatment with

0.02% BAC for 15 min before the staining process. The experiment was performed in replicate and six images were taken for each sample and control. The results were expressed in term of percentage of dead cells which were obtained using the following equation:

Number of dead cells (Red) Dead cells (%) = x 100. (Equation 3- 2) Number of total cells (Green+red)

3.2.9 Ellman’s assay for detection of reactive oxygen species

In the Ellman’s assay, the activity ROS was quantified indirectly through the loss of glutathione activity.35, 271 The uncoated slide (control) and coated slides with adhesive B, D, B-

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G50 (50% of G), and D-GO75 (75% of GO) were placed in 15 mL conical tubes containing 2 mL of

0.4 mM GSH (dissolved in 50 mM bicarbonate buffer, pH 8.6) and 2 mL of NaHCO3. A positive control containing 2 mL of 30% H2O2 was prepared in parallel and treated with the same reagents. The samples were left shaking at 150 rpm for 2 h at room temperature. After that, 500

µL of samples were withdrawn and placed in 2 mL tubes. The samples were analysed as described previously.35 The absorbance was read at 412 nm (Synergy MX Microtiter plate reader, BioTek, U.S.A.) and the results were express in terms of loss of GSH which was calculated from equation 3-3 below:

(absorbance of negative control−absorbance of sample) Loss of GSH (%) = x 100. (Equation 3-3) absorbance of negative sample

3.3 RESULTS AND DISCUSSION

3.3.1 Synthesis and characterization of the polymers.

This study aims to design adhesive polymers that will simultaneously immobilize and promote the antimicrobial properties of G and GO. The adhesive polymers that were prepared have catechol side chains and a co-polymer that provide side groups with a variety of properties.

A 15 mol% amount of catechol groups was chosen to approximate the amount found in naturally occurring mussel adhesion protein,272 as well as in many previously described synthetic polymer adhesives.273 The different side groups, on the other hand, were investigated for effective interaction of the antimicrobials with the adhesive polymers. Figure 3-1 shows the synthetic reaction and the variation of side chains that has been incorporated in the synthesized adhesive polymers and the typical structure of each adhesive polymer. Polymer A contained a polar aprotic side chain, Polymer B is composed of only a monomer with a catechol side chain

(homopolymer), Polymer C contained a short hydrophobic side chain, and Polymer D contained a polar protic hydroxyl side chain. NMR analysis of the obtained polymers proved that the proportion of the catechol side chain of the polymers was around 15 %. The proportion of the

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catechol was determined by comparing the integrated area of the methylene groups of DMA and co-polymers. GPC analyses estimated that the polymers have low molecular weight of 7-45 kDa (Table 3-1). The slight differences in sizes of the polymers should have little effect on our application since they will be cross-linked into 3-D networks when applied as coatings. Also, GPC estimated the polydispersity index to be between1.4-2.0, values that are commonly observed for polymers of this type prepared by free radical polymerization. 273, 274

A: Polar non hydroxylic B: No other side chain

Me Me random n m O O NH O

O H

HO OH C: Nonpolar short chain D: Polar hydroxylic

Figure 3-1 Synthesis of polymeric adhesives

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Table 3-1 Table of NMR/GPC for characterization of the adhesives polymer used in this study

MP (NMR)a M (GPC)b M (GPC)b n n w Đc Polymer Mol % g/mol g/mol A 84 27 509 39 527 1.44 B 0 7 554 15061 1.99 C 84 4 136 7 710 1.86 D 85 29 525 44 691 1.51 a 1 Mole percent of copolymer (MPn) in a polymer chain determimed by H NMR. b The number average molecular weight (Mn), The weight average molecular weight (Mw) determimed by GPC. The molecular weight calibration was based on polystyrene standards. c Polydispersity index (Đ) was calculated as Mw/Mn using Mw and Mn values determined by GPC

3.3.2 Selection of the best polymer

There were a total of four synthesized polymers that were evaluated as adhesives for coatings with antimicrobial materials onto glass surfaces. Experiments were performed to determine which polymers were the best adhesives for each type of antimicrobial material. In this initial assessment, mixtures of the adhesive polymers with G or GO with 50 % were first prepared and used to coat glass slides by spin coating. E. coli culture was then exposed to the coated surfaces and the bacterial mortality was assessed using the live and dead assay. At a

50:50 ratio of adhesive polymers and antimicrobials materials, all combinations coated on the glass slides exhibited antimicrobial properties. These results show the adhesive polymers did not hinder the antimicrobial properties of the materials tested. The percentage of inactivated cells ranged between 20 and 80% (Figure 3-2).

Interestingly, different kinds of adhesive polymers were found to be optimum for G and GO differently. Polymer B and D worked the best for G and GO, respectively (Figure 3-2). The figure expressed the results as percentage of dead cells (coatings with 50% materials in 2 h exposure).

The controls: glass slides only, adhesives only were not showing any dead cells (not presented in the figures).G is non-polar and has aromatic rings in its structures that facilitate π-bond

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interactions. Therefore, the π-π bonding between the catechol rings of Polymer B with that of G sheets generated a better antimicrobial coating. Antimicrobial assays of coatings made from different percentages (25, 50, 75 and 85%) of adhesives showed that the coatings composed of

50% combination of Polymer B and 50% of G (B-G50) had the best performance (Figure 3-3).

Note, that the addition of more G did not increase the antimicrobial activity. Others working with G and polymer composites also observed that G’s performance as an antimicrobial material was enhanced due to increase dispersion of this nanomaterial in the polymer.6, 275 Hence, higher concentrations of G will lead to higher aggregation and reduced antimicrobial property.

Meanwhile, the Polymer D adhesive with more polar side chains, such as hydroxyl groups, was a more effective adhesive for GO because of the hydrogen bonding. Further assays showed that the ratio of 25% of Polymer E with 75% GO (D-GO75) exhibited the best antimicrobial effect

(Figure 3-3).

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Graphene oxide 100 Graphene 100

80 80

60 60

40 40

Dead cells (%) cells Dead Dead cells (%) cells Dead

20 20

0 0 A B C D A B C D

Figure 3-2 Live and Dead assessment to select the best adhesives (A, B, C, D) for G and GO.

100 Adhesive B 100 Adhesive D

80 80

60 60

40

40

Dead cells (%) cells Dead Dead cells (%) cells Dead 20 20

0 0 25% 50% 75% 85% 25% 50% 75% 85% Graphene oxide Graphene GO25 GO50 GO75 GO85 Figure 3-3 Selection of the best ratio of G and GO with their respective adhesives. The coatings contained Graphene2525, 50, 75Graphene50 and 85%Graphene75 of antimicrobialGraphene85 materials.

3.3.3 Characterizations of the best coatings for each antimicrobial

SEM images of glass slides coated with Polymer B and D were found to be smooth and uniform (Figure 3-4). SEM images of the surface deposited with B-G50, and E-GO50 showed nanoparticles homogenously deposited on the surface. The nanoparticles were randomly distributed on the surface.

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The successful coatings were monitored by determining changes on the surface property of the coated glass slides through contact angle measurements. The results showed that the starting uncoated glass slides were hydrophilic with the contact angle of 17.5°. Upon coating with the adhesive polymers, hydrophobicity of the surface increased (Figure 3-5). In the case of polymer B, the change in contact angle of the glass slide was marginal, but increased

276 substantiallyA when coated with B-G50. Clearly, theA hydrophobic-MoO350 nature of G has imparted its properties to the nanocomposite product. On the other hand, the presence of polar polymer D coating has increased the contact angle to 39.1o. The glass surface and addition of GO to the polar adhesive (D-GO75) increased the contact angle to 43.2o. These significant increases in contact angle demonstrate the success in coating improvement of the glass slides with the prepared adhesive polymers and composites.

B B-G50

D-GO75 D

Figure 3-4 Scanning electron microscope (SEM) images of the coatings. Scale bar 1µm.

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60

50

40

30

20

Angle(degrees) 10

0 Glass B B-G50 D D-GO75 slide Figure 3-5 Contact angle results of the best coatings: adhesive B with graphene 50% (B-G50) and adhesive D with GO 75% (D-GO75) 3.3.4 Stability of the coatings through leaching test

This experiment was performed in order to test for the potential release of coating materials in solution. The solution after using for 24 h leaching (experiment, which described at section 3.2.3, was tested for toxicity against bacteria and human cells. Results showed that there was no sign of toxicity to either bacteria or human cells after incubation for 2 h and 16 h

(Figure 3-6 and 3-7), respectively. The nontoxic results of the leaching solution confirmed that there was no significant release of coating materials to aqueous solutions.

To confirm the stability of the coatings, the glass slides were re-characterized after the leaching tests to determine any surface changes. Coatings with B-G50 and D-GO75 were re- characterized after the leaching test (Figure 3-8). The results showed no significant changes in the coatings. The thickness of the coatings was also evaluated before and after leaching for 7

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days at 37 oC. The results showed no significant losses of the coating (Table 3-2). These results indicated that the polymeric adhesives can produce stable coatings under biological conditions.

1x107

1x107

9x106

8x106

Control B B-G50 D D-GO75 Bacterial survival (CFU/mL)

Figure 3-6 Investigation of bacterial survival after the leaching experiment (tested against E. coli K12). The microbial survival was determined using the plate count method.

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100

80

60

40

Livecells (%)

20

0 B D B-G50 BAC D-GO75 Untreated Figure 3-7 Cytotoxicity of leaching solution against hTCEpi cell line (human corneal epithelial). The

negative control with untreated cells and positive control using benzalkonium chloride (BAC) 0.02% are also presented in the figure.

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A-MoO350 C-PEI75

B-G50 D-GO75

Figure 3-8 SEM images of the antimicrobial coatings after leaching. Scale bar 1 µm

Table 3-2 Thickness of the coatings before and after leaching for 7 days at 37 oC

Coatings Thickness (nm)* Standard deviation B only 68.56 1.08 B-G50 68.79 0.19 B-G50 leached 68.97 0.34 D only 72.06 1.29 D-GO75 69.4 0.21 D-GO75 leached 69.4 0.2

3.3.5 Antimicrobial effects and human toxicity of the coatings

From the results, other important trends were observed. First, the optimum concentration of B as adhesive coatings can only be as low as 25% because the antimicrobial activity declines when lower concentrations are used (Figure 3-3). In contrast, Polymer D could be used with a concentration as low as 15% and still present excellent antimicrobial activities. The hydrogen bonding interaction of the polymers with the nanomaterials could have played a key role in creating a more effective bond between the materials and the adhesives. Furthermore, GO exhibited a concentration dependency. For instance, at 50% and 75%, the microbial inactivation was 44 ± 5.7% and 95 ± 8.9%, respectively (Figure 3-3). Similar trend in concentration

30, 220 dependency was previously reported for GO. However, this trend was not observed for G, in which the antimicrobial activities showed a plateau and were not significantly different at

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concentrations above 50% for G (Figure 3-3a). These results contradict previously reports in antimicrobial studies that show concentration dependency for the nanoparticles. 6 In the present case, addition of more G (≥ 50%) did not improve the antimicrobial activity. This is presumably because the aggregation of particles cancelled the addition effect of more antimicrobial material.

After the ratio selection of adhesives and antimicrobials was completed, further investigation was carried out against different Gram-negative and Gram-positive bacteria to determine the range of anti-microbial activity of the coatings. The toxicity of the slides coated with composites exhibited excellent activity against E. coli. This effect was observed at time of 1 h interaction and the bacteria mortality went from 78 to 98% for most coatings while uncoated glass slides and slides coated with adhesives only showed no dead cells (Figure 3-9). Also, the 1 h interaction results demonstrated that the polymer adhesives enhanced the antimicrobial activity of G and GO due to more efficient contact between the coated surface and bacteria. 5, 6

The antimicrobial assays also revealed that compared to E. coli samples, B. subtilis had more cells inactivated after 1 h interaction for all antimicrobials.

The experiments also revealed that the antimicrobial activity of the coatings B-G50 and D-

GO75 took a little longer to inactivate E. coli than B. subtilis. B. subtilis for these coatings was inactivated in less than 1 h. For instance, in the case of D-GO75, the dead cells were 78 ± 8%

(1h), 92 ± 9% (2h) and 98 ± 3% (1h), 97 ± 5% (2h) for E. coli and B. subtilis, respectively (Figure 3-

9). This inactivation difference between these two bacteria was previously reported for G and

GO.30, 220 The investigation of the antimicrobial property of the coated surfaces toward other

Gram-negative and Gram-positive bacteria was also investigated, using Pseudomonas aeruginosa and Staphylococcus epidermidis cultures. The coated glass slides caused cell death upon contact with these microbes as well (Figure 3-9). However, the highest inhibition activity

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was observed at longer incubation time (2h). This could be due to P. aeruginosa, S. pyogenes and S. epidermidis being more resistant microorganisms in general, since they are known to resist several antibiotics and drugs.277-279 These results once again confirmed the effectivity of the adhesives for coating surfaces with antimicrobial materials. It was worth to note that the controls consisted of only glass slides and the adhesive only coating the slide, which presented a result of zero or less than 2% of dead cells (Figure 3-9).

1h 1h 120 120 a) 2h b) 2h * * * 100 * * 100 * * * 80 80

60 60 40 40

Deadcells (%) 20 Deadcells (%) 20 0 B D 0 Control B D Control B B D D G50 GO75 G50 GO75 1h 1h 120 2h 120 c) * d) 2h * 100 100 * *

80 80 * * 60 60 * * 40 40

Deadcells (%) 20 Deadcells (%) 20

0 0 Control B B D D Control B B D D G50 GO75 G50 GO75

Figure 3-9 Live and dead assays of the coatings expressed as percentage of dead cells of E. coli (a), B. subtilis (b), Pseudomonas aeruginosa (c) and Staphylococcus epidermidis (d). (*) indicates statistically significant results between the control (slides coated with the adhesive only) and the adhesive composites The microorganisms exposed to the coated surfaces were analyzed by SEM (Figure 3-11).

The SEM images of samples incubated with the coated surfaces show that the cells had twisted shape or were busted. In comparison, cells with smooth and healthy shapes were observed only

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in the control and uncoated slides. The images of the destroyed microorganisms were similar to

G and GO cellular damage previously observed in other studies.5 In addition, the images showed damage of the cell membranes, which led to the cell death (staining red), after contact with coated surfaces (Figure 3-10).These results suggest that the antimicrobial activity of the latter two materials involved cell membrane damage as well.

B. subtilis Total cells Dead cells

Control

B only

B-G50

Figure 3-10 Microscopic images of live and dead assay for antimicrobial properties of the coatings showing total cells (green) and dead cells (red). The images showed B. subtilis with B, B-G50 and the control. Scale bar at 100 µm

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a) b)

c) d)

e)

Figure 3-11 Scanning Electron Microscope (SEM) images showing the damaged microbial cells after interacting with the coating surface for 2h interaction with B. subtilis (control (a), B and BG (b, c), D and D-GO (d, e). Scale bar at 1 µm

Longer time exposure to investigate anti-biofilm formation was performed with the optimized coatings. During biofilm formation, there are a combination of different forces and interactions, such as van der Waals or electrostatic force and cell-substrate or cell-cell interaction on the same surface.280, 281 In the presence of antimicrobial coatings, the bacteria

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were inactivated upon contact with the antimicrobial surface, which led to a reduced biofilm growth. In the case of G and GO with the adhesives, all the coatings containing G or GO showed significant anti-biofilm activities. The biomass on the surface without any coating was 13.7 ± 3.7

µ3/µ2, while the presence of coating showed only 0.1 ± 0.08 and 1.6 ± 0.2 µ3/µ2 for B-G50 and D-

GO75, respectively, when exposed to E. coli for 72 h (Figure 3-12). Anti-biofilm was also expressed in the interaction with B. subtilis (Figure 3-12 and 3-14). Significant anti-biofilm activity for other microorganisms, i.e. P. aeruginosa and S. epidermidis, was also observed with these coatings (Figure 3-12). The anti-biofilm was also expressed in the lower thickness in the formation of biomass of four bacteria (Figure 3-13).

It is worth pointing that the adhesives by themselves also inhibited, at some extend, biofilm growth. However, they did not present any antimicrobial property (Figure 3-9). This biofilm inhibition could be because of the contact angle properties of the adhesives. It is known that the microbial adhesion and biofilm formation relies strongly on the hydrophobic and/or hydrophilic interactions of surfaces with microbial cells.282

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a) 24h b) 24h 

 20 72h 10 72h

 m





m 

15 

m 



m  10 5

5

Biomass( 0 Biomass( 0 Control B B D D Control B B D D G50 GO75 G50 GO75 20 c) 24h d) 24h 20

 72h

 72h 

15 

m

m

 

 15



m m

 10  10

5

5 Biomass( Biomass( 0 D 0 Control B B D Control B B D D

G50 GO75 G50 GO75 Figure 3-12 Biomass volume of the biofilm (a) E. coli; (b) B. subtilis; (c) P. aeruginosa and (d) S. epidermidis

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24h 25 b) 25 d) 24h 72h 72h m) 20

 20

m)  15 15

10 10

Thickness( 5 5 Thickness(

0 0 Control B B D D Control B B D D G50 GO75 G50 GO75

30 25 f) 24h h) 24h 72h 25 72h

20 m)

m) 20   15 15 10 10

5 Thickness( 5 Thickness( 0 0 Control B B D D Control B B D D GO75 G50 GO75 G50

Figure 3-13 Thickness of the biofilm (a) E. coli; (b) B. subtilis; (c) P. aeruginosa and (d) S. epidermidis

Control B-graphene 50%

Figure 3-14 Representative confocal images of biolfilm of B. subtilis: control (glass slide) and adhesive B with 50% G

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In order to utilize the coatings for biomedical applications, these coatings were tested for cytotoxicity against the hTCEpi cell line. Results showed that no cell death was observed on surfaces with the new coatings (Figure 3-15). These results confirmed that the composites of adhesives containing G or GO are toxic against bacteria, but not to human cells. This implies safety and biocompatibility of these new coatings materials for use in bio-applications. It was worth to note that there are still no studies to clearly explain the conflict in behavior of microbial cells and human cells, which lead to the different level of toxicity.

100

80

60

40

Livecells (%) 20

0 Uncoated B B-G50 D D-GO75 BAC

Uncoated (live cells) Coated (live cells) BAC (dead cells)

Figure 3-15 Cytotoxicity of coated slides against the hTCEpi cell line (human corneal epithelial) expressed in terms of percentage of dead cells. The uncoated glass slide represents the negative control and BAC (benzalkonium chloride, 0.02%) represents positive control 3.3.6 Mechanism of toxicity

The antimicrobial materials (G and GO) were reported to interfere with the cell’s oxidation repair mechanisms which were one of the factors contributing to cell death. 30 In this study, we also monitored the ROS production of the coating materials to gain insights about their

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mechanisms of action. The results showed that the incorporation of these antimicrobial materials in the adhesive polymers still express similar mechanisms of toxicity as their pristine counterparts as previously described in the literature. All the coated slides produced a certain amount of ROS after 2 h contact with the GSH solution (Figure 3-16). Although the ROS was produced by all coated slides, the G had the lowest ROS production, which could be due to the lack of oxygen functional groups present on G sheets. This phenomenon was previously reported in studies investigating different G based materials.35 It is important to note that the glass slides coated with the adhesive polymer only (as negative control) did not produce ROS

(Figure 3-16). Polymers are commonly used for biomedical applications, from natural polymers to synthetic polymers, such as poly(vinyl alcohol), polyethylene, polypropylene or poly(lactic acid), so it is not surprising the negligible production of ROS by the adhesives only.283-285

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100 * *

80

60

40 Lossof GSH(%) *

20

0 + - B B D D Control G50 GO75 Figure 3-16 Reactive oxygen species production from the coatings when in contact with glutathione (GSH). The results are expressed in terms of percentage of GSH loss in comparison to the negative control. The symbol (*) indicates the sample results are statistically different from the negative control

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3.4 CONCLUSIONS

In the present study, several polymers with catechol side chains were successfully synthesized and blended with antimicrobial materials (G and GO) to generate antimicrobial and anti-biofouling coatings without presenting toxicity to human cells. The adhesive polymers were used as a component of the coating in amounts as low as 15% to immobilize the antimicrobial materials on the surface. The composites were also demonstrated to be stable under physiological conditions, and thus, could potentially be used in clinical and other biomedical applications to prevent growth of pathogenic bacteria on surfaces of medical devices. The results have also shown that the coating materials are active on a broad range of pathogenic microorganisms. Although our investigation was based on specific materials, it is possible to assume that the incorporation of other kind of antimicrobial materials such as polymers (PEI, and/or similar FDA approved polymer-based antimicrobials) in such formulations could potentially produce other types of coatings capable of preventing microbial attachment and biofilm formation.

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CHAPTER 4 THE ACUTE TOXICITY OF GRAPHENE TO THE BIOLOGICAL WASTEWATER TREATMENT PROCESS “Adapted with permission from (Nguyen, Hang N., Sarah L. Castro-Wallace, and Debora F. Rodrigues. "Acute toxicity of graphene nanoplatelets on biological wastewater treatment process." Environmental Science: Nano 4.1 (2017): 160-169).”

4.1 RATIONALE AND OBJECTIVES

Carbon-based nanomaterials are being intensively used in many applications in diverse fields. Among the carbon-based nanomaterials, G is the building block of graphitic materials, such as fullerenes, carbon nanotubes, GO, and graphite. G consists of a monolayer of carbon atoms, arranged in a two-dimensional hexagonal. G has been reported with high Young modulus ranges from ~ 1 TPa to 2.4 TPa, which is 5 to 20 times larger than steel (200 to 220 GPa).286

Additionally, G has high electrical conductivity and antimicrobial properties.287 G nanomaterials have been used in broad applications, such as energy, automotive, aerospace, electronics, biomedical devices, cytotoxicity of tumor cell-lines and others therapeutic products.127

In the next 10 years, it is estimated that $ 1.3 billion dollars will be spent in the development of new applications for graphene.288 Graphene’s anticipated market will grow from $20 million to $390 million dollars from 2014 to 2024.2 This large market growth is indicative that more graphene will be consumed or produced by diverse industries in the coming years. Recent studies investigating the potential release of carbon based nanomaterials and other nanoparticles, such as carbon nanotubes and silver nanoparticles, by various industries have demonstrated that release will happen due to consumption, reuse and production of these nanomaterials.289-291 These studies have raised the issue of the end-of-life of nanowastes due to increasing nanomaterial production and consumption.292 In these studies, different scenarios have been discussed on the potential release of these nanomaterials to the environment.293 The consensus is that the release of these nanomaterials will happened in the environment via soil, air or waterways, which will ultimately end up in wastewater treatment plants.294 Wastewater

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treatment plants have microbial communities involved in the biological treatment process that can be affected by toxic chemicals and nanomaterials. G has known antimicrobial properties, however, little is known about the impact of G on wastewater treatment plants.6

Previous studies investigating other carbon-based nanomaterials showed that some of them can negatively impact wastewater treatment. For instance, GO and carbon nanotubes were shown to be toxic to activated sludge, which is the aeration sewage water containing microorganisms helping the biological treatment process.20, 295, 296 Another study stated that multi-walled carbon-nanotubes affected the nutrient removal and community structure of activated sludge.19 Hence, since G has been shown to have antimicrobial properties, and wastewater treatment is mainly a microbiological process, the impact of G in wastewater treatment needs to be investigated.

In the present study, acute toxicity of G, i.e., high concentrations of G for a short exposure time, was investigated using bioreactors to simulate the biological wastewater treatment process. The impact of G was determined by investigating the performance of nitrogen and phosphorous removal in the bioreactors. Acute toxicity of G in the abundances of ammonia oxidizing bacteria (AOB)297, 298 and phosphate accumulating organisms (PAO) were also investigated in the sludge.299 Finally, the overall acute toxicity of G to the wastewater microbial community was determined using 16S rRNA gene deep sequencing analyses.

4.2 MATERIALS AND METHODS

4.2.1 Source of activated sludge

Activated sludge was collected directly from the aeration basin of the Sims South Bayou

Wastewater Treatment Plant (WWTP) (Houston, TX. USA). The activated sludge was collected in sterile Nalgene bottles, stored in a cooler containing ice, and transported to the laboratory immediately to start the experiments. The schematic flow of the treatment at the Sims South

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Bayou is described in figure 4-1. The characteristics of the sludge collected for the experiments are presented in Table 4-1. Collecting point

Grit removal Aeration Clarifiers Influent (headworks) basins

Chlorine Neutralization prior to Mixing and clarifier ponds discharge treatment

Figure 4-1 Diagram of the flow of the wastewater at the Sims South Bayou Wastewater Treatment Plant. Red arrow indicates where the activated sludge was collected for this study

4.2.2 Experimental design of batch reactors

Most of the chemicals used in this study were purchased from Sigma-Aldrich with purity >

99%, unless stated otherwise. Synthetic wastewater (SWW) was used as a feeding solution in all the bioreactor experiments. The synthetic wastewater consisted of mixing 100 mL solution A with 1900 mL solution B. These solutions were mixed just before use to obtain a fresh feeding solution.300 The solution A at pH 5.5 was prepared in 1 L of DI-water and contained

NaCH3COO.3H2O (17.53 g), MgSO4 (0.49 g from EMD Millipore, U.S.A), CaCl2.H2O (0.45 g from

Fisher, U.S.A), NH4Cl (3.3 g), Peptone (0.5 g) and 6 mL of nutrient solution. The nutrient solution contained a mixture of FeCl3 (0.9 g), H3BO3 (0.15 g), CuSO4.5H2O (0.03 g), KI (0.18 g from EMD

Millipore, U.S.A), MnCl2.4H2O (0.12 g), Na2MoO4.2H2O (0.06 g), ZnCl2 (0.1 g), CoCl2.6H2O (0.15 g) and ethylenediamine tetraacetic acid (EDTA; 10 g). The solution B contained KH2PO4 (0.0285 g) and K2HPO4 (0.0325 g) in 1 L DI water, and its pH was adjusted to 10 using 10 M NaOH. Both solutions were autoclaved separately at 121oC for 20 min. Characteristics of the synthetic wastewater are summarized in Table 4-1.

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Table 4-1 Characteristics of synthetic wastewater and Sims South Wastewater Treatment activated sludge Parameters Synthetic wastewater Sims South pH 7.0 ± 0.5 7.2 ± 0.6

Ammonia – nitrogen (NH3 – N) (mg/L) 70 ± 2 5.38± 0.86 Nitrate – nitrogen (NO3 – N) (mg/L) 32 ± 1 23.4 ± 2.8 Phosphate (mg/L) 40.7 ± 1.5 0.16 ± 0.06 Chemical oxygen demand (COD) (mg/L) 673.7 ± 9.6 72 ± 1

After collection of the activated sludge, the sludge was settled for 30 min and then transferred to reactors with synthetic wastewater for acclimation at 22oC. All reactors in this study were continuously mixed using a stir bar at 100 x g (units of time gravity) and air was introduced in the reactor through fine air bubbles with a flow of 0.5 litter per minute (Fisher air meter). The pH was monitored and maintained at 7.0 ± 0.5 throughout the experiments. A 4 L beaker was used as the main reactor for acclimation of the activated sludge. The beaker had an active volume of 3.2 L, which consisted of 2 L of synthetic wastewater and 1.2 L of activated sludge. The reactor was run for 44 h with a cycle every 10 to 11 h of settling, decanting, and feeding of 2 L of synthetic wastewater. This cycle was selected since this was the period required for the sludge to have an ammonia removal of 85- 90%. Samples were taken every 3, 6 and 10 h for ammonia determination with a total of 4 cycles in this sludge acclimation period.

At the end of the acclimation period, the activated sludge in the main reactor was divided into five smaller reactors. The smaller bioreactors were set up with 200 mL of acclimated activated sludge and 1 L of synthetic wastewater. Each reactor was amended with the following

G concentrations: 0, 1, 10, 100, and 300 mg/L. The reactors were run simultaneously for 10 h.

The retention time of 10 h corresponds to the relative time for the activate sludge to remove

85% of ammonia in the control reactor (0 mg/L G).

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The same acclimatization and experimental procedures with G were repeated three times to compare the reproducibility of the results of the reactors with sludge samples collected from the wastewater treatment plant at different time periods.

4.2.3 Analytical methods

During the simultaneous run of the five reactors, samples were taken from each reactor at times 0, 5 h and 10 h with 10 min settling time before ammonia (NH3 – N), nitrate (NO3 – N),

3− phosphate (PO4 ) and chemical oxygen demand (COD) sample analyses. All the analyses were done in triplicate using colorimetric methods (Hach, DR3900 spectrometer). The supernatant water (after 10 min settling) was immediately filtered using 0.2 µm pore size syringe filter

(Corning filter) to remove particles. Mix-liquor was collected to determine the biological oxygen

301 demand (BOD5) for all three periods. BOD5 was determined based on Standard Methods. All the analyses were done in triplicate, and the results were averaged out. The standard deviations were calculated and reported as well.

4.2.4 Determination of microbial metabolic activity

The metabolic assay was done at the end of each run using the Vibrant Cell Metabolic Assay kit (Invitrogen, U.S.A.). The kit includes resazurin, a non-fluorescent dye, which is reduced by viable cells yielding resorufin, a highly fluorescent product. Samples containing 100 µL of mix- liquor were mixed with 60 µL of 10 µM resazurin in a 96-well black plate (Greiner, U.S.A.). After gentle mixing, the plate was incubated at 37oC for 15 min in the dark, and the resorufin production was determined by measuring the fluorescence at 530/587 nm wavelength using a plate reader (Synergy MX Microplate reader, BioTek, U.S.A). The results were expressed as percentages to indicate the metabolically active cells following this formula:

. (Equation 4-1)

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where fluorescence of the control was measured from the sample of the reactor without G.

4.2.5 Microscopic observation of the interaction of G with sludge

Qualitative observation of the interaction of the sludge with G was done under a fluorescence microscope using the SYTO9 green-fluorescent staining (Invitrogen, U.S.A.). The following samples were observed under the microscope: 1 mL of G suspension, 1 ml of sludge

(no G), and 1 ml of sludge containing 100 mg/L G. Then, 1 µL of SYTO9 was added to each tube.

All the tubes were vortexed and incubated for 2 min at room temperature. The fluorescent images were taken using the BX 51 Olympus Fluorescence Microscope (Leeds Instrument Inc.,

USA) equipped with a DP72 digital camera under 40 objective and a fluorescinisothiocyanate

(FITC) filter.

4.2.6 Polymerase chain reaction (PCR) and cloning

All PCR reactions in this study used the same procedure and reactions set-up. Briefly, triplicate PCR reactions of 25 µL for each sample were performed using 12.5 µL of 2X Amplitaq

GoldFast PCR master-mix (Invitrogen, U.S.A.), 200 nM of reverse and forward primers, 0.125 µL of 0.1 ng/µL BSA, and 100 ng/µL of each DNA template in Applied Biosystems, Veriti 96-well thermal cycler with the thermal condition described in Table 4-2. All the PCR products were confirmed by agarose gel electrophoresis using 1% agarose gel.

The clones were generated from fresh PCR products using the extracted DNA from the

WWTP activated sludge with specific primers for AOB, amoA and PAO gene. The TOPO TA cloning kit (Invitrogen, U.S.A.) was used to clone the PCR-amplified genes. Successful cloning of the genes was confirmed by PCR amplification with specific primers following the procedure suggested by the manufacturer. The agarose gel electrophoresis was used to determine whether the clones had the expected size of the AOB, amoA and PAO genes.

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4.2.7 Sludge DNA extraction and real time PCR (RT-PCR)

Samples for DNA extraction were collected at times 0 h and after 10 h running the reactors.

Aliquots of 2 mL of activated sludge were collected from each reactor, and centrifuged immediately at 22000 x g (units of times gravity) for 1 min. The total DNA extraction was conducted using PowerWater DNA isolation kit according to manufacturer’s protocol (MoBio,

U.S.A.). The concentrations of extracted DNA were quantified by the Take3 reader (Biotek,

U.S.A.). Extracted DNA samples were kept at -20 oC until further experimentation.

RT-PCR was performed using the StepOne Plus Real-Time PCR system (Applied Biosystems,

U.S.A.) to quantify ammonia oxidizing bacteria (AOB), the ammonia monooxygenase gene

(amoA), phosphate accumulating organisms (PAO) and the total bacterial population. Standard curves for quantification of these genes were generated using clones of the genes AOB, amoA and PAO prepared as described in the previous section. The genes cloned were cultivated at

37oC overnight and freshly extracted for RT-PCR (QIAprep Spin, Qiagen, U.S.A.). The 16S rRNA genes were evaluated using the universal primers E8-F and E533-R with a standard curve generated from E. coli K12 DNA.302

The RT-PCR reaction contained 7.5 µL of 2X Power SYBR Green PCR master-mix (Invitrogen,

U.S.A.), 0.6 µL of 0.1 ng/µL BSA, 1 µl of DNA template, and specific amounts of each primer as described in Table 4-2. Sterile RNA/DNA free water was used to obtain a final reaction volume of

15 L. The concentrations of the primers were optimized using the protocol described by the

SYBR Green manufacturer. To prepare the standard curves, the plasmid copy numbers extracted for each cloned gene were initially calculated, using the equation 4-2 below:303, 304

, (Equation 4-2)

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where DNA concentration corresponds to concentration of genomic DNA of E. coli or plasmid in

µg/µL and DNA length corresponds to the number of base pairs (bp) of double-stranded products (genome or plasmid).

Table 4-2 Target gene, concentration of primers and thermal cycle

Primer final Regular Primer Target Name concentration RT-PCR References PCR (5’-3’) (nM) GGAGR 50oC 2mins, CTO 189-F AAAGC 300 95oC 10mins, Ammonia- A/B AGGGG 40 cycles of 305, 306 307, oxidizing ATCG o 95 C 1min, 308 bacteria (AOB) CTAGCY o 50 C 1min 16S rRNA TTGTAG o CTO 654-R 300 and 60 C TTTCAA 1min ACGC GGGGT TTCTAC 95oC 15mins, amoA-1F 300 o 10 min TGGTG 95 C 4mins, o Ammonium 306, 309-311 of 95 C; GT 50 cycles of monooxygenase o 297, 308 35 CCCCTC 94 C 30s, (amoA) o cycles of KGSAA 56 C 30s and o o 94 C in amoA-2R 300 72 C 30s AGCCTT 30 s, 55 CTTC oC in 40 CCAGC s, and AGCCG o 518-F 50 72 C in CGGTA 95oC 3min, 1 min; Accumulibacter AT o 45 cycles of 299, 312 72 C for 16S rRNA genes GTTAG o 95 C 30s, 7 min, (PAO) CTACG o o 60 C 40s and 4 C PAO846-R GCACT 50 infinite AAAAG G AGAGT TTGATC E8-F 300 CTGGCT 95oC 3mins Universal 16S CAG 44 cycles of rRNA gene 302, 313, 314 TTACCG 95oC 15s (Universal) CGGCT 55oC 1min E533-R 300 GCTGG CAC

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After determining the plasmid copy number extracted, dilutions of the plasmids were made

2 7 to obtain concentrations ranging between 10 to 10 copy/µL. The Ct values corresponding to each dilution was used to plot the standard curves for each primer.

For each gene investigated, serial dilutions of each experimental sample, negative RT-PCR reaction controls containing no DNA template, and dilutions of the plasmid for the standard curve were run together in triplicate. The results were expressed in concentrations that were normalized to 1 ng of DNA template. Paired T-test analyses were performed to interpret the statistically significant (p ≤ 0.05) differences between each experimental and control reactors for each gene investigated.

4.2.8 16S rRNA gene amplification and deep sequencing

Amplicon preparation, library construction, and sequencing were carried out according to

Illumina technical instructions (16S Metagenomics Sequencing Library Preparation Rev. B,

Illumina, San Diego, CA). Briefly, a 460 bp amplicon spanning the V3-V4 region of the 16S rRNA gene was obtained using the forward S-D-Bact-0341-b-S-17 (5’-CCTACGGGNGGCWGCAG-3’) and reverse S-D-Bact-0785-a-A-21 (5’-GACTACHVGGGTATCTAATCC-3’) primers.315 The DNA was amplified following the protocol described in 16S Metagenomics sequencing library preparation in the Illumina protocol with the addition of one more holding stage at 98oC for 20 sec at the beginning of the thermal cycling. All the following steps, i.e. clean-up and index PCR followed the protocol from Illumina. The Illumina MiSeq Reagent Kit v3 (2x150 bp paired-end reads) was used to prepare the library and for sequencing, which were conducted at the NASA JSC

Microbiology Laboratory (Johnson Space Center, Houston, TX). The data obtained was deposited in the NCBI database under the BioProject ID: PRJNA276567.

Illumina MiSeq Reporter software was used for quality control, trimming, and mapping. The diversity of each consortium was determined using the 16S Metagenomics v1.0 application on

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Illumina’s BaseSpace cloud-computing platform. Coverage of the species was determined by rarefaction curves generated by “iNEXT online: interpolation and extrapolation (Version 1.3.0)” software (http://glimmer.rstudio.com/tchsieh/inext/) (Figure 4-2).

Figure 4-2 Sample-size-based rarefaction curves of activated sludge from reactors exposed to different concentrations of G

4.3 RESULTS AND DISCUSSION

4.3.1 Impact of G on chemical parameters of the wastewater treatment

In this study, we investigated the effect of the presence of G in chemical oxygen demand

(COD) and biochemical oxygen demand (BOD), which are important chemical parameters for the wastewater treatment. Overall, the presence of G in the sludge impacted all these parameters as shown in figure 4-3.

The presence of G in the sludge had a direct impact on COD removal (Figure 4-3a). In the case of COD, its removal was slightly inhibited with the presence of G. For instance, after exposing the reactors for 10 h to G, the COD removals were 93 %, 90%, 85%, and 79% for 0, 10,

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100 and 300 mg/L of G, respectively (Figure 4-3a). These reductions were not observed in previous studies, where no significant effects of COD removals were observed with increasing concentrations of carbon nanotubes.296, 316 However, this result is in agreement with a long-term exposure study with multi-walled carbon nanotubes (MWCNT) that also observed reduced COD removal.19 Hence, G, like MWCNT, can have a negative impact on the COD removal at concentrations higher than 1 mg/L.

The acute effect of G to BOD was also investigated using the BOD5 assay. The assay allows us to determine the microorganism’s capability to remove organic matter in the presence of

317 oxygen. The results showed a reduction in BOD5 after 5 h exposure of the sludge to G (Figure

4-3b). Furthermore, the impact of G was directly related to its concentration. For instance, there was a reduction in the wastewater BOD from 23% to 49% after exposure to G concentrations ranging from 10 to 300 mg/L, respectively (Fig 4-3b). On the other hand, there was no change in the wastewater BOD for the control and the wastewater exposed to 1 mg/L. In the latter, the high BOD levels, which is typically observed in wastewater effluents, is due to the decline in dissolved oxygen (DO) levels caused by the high microbial oxygen demand in the wastewater. In the presence of antimicrobials in the water, such as G and chlorine, the BOD will typically be smaller, since there will be not as many active microorganisms to decompose the organic matter and consume oxygen. Previous studies with carbon-based nanomaterials, such as graphite, G and GO showed similar trend. These materials were shown to be toxic to bacteria in either pure culture or activated sludge when the nanomaterial concentrations increased.4, 20, 35 Besides the concentration effect, the time exposure of G to the sludge, i.e. 5 h and 10 h, also affected the level of G toxicity. The time dependency of G toxicity was more apparent in the concentration of

300 mg/L (Figure 4-3a).

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Figure 4-3 a) Chemical oxygen demand concentration before and after 5 and 10 h; b) Biological oxygen demand before and after 5 and 10 h run under exposure to different concentrations of G. * Statistically significant different results compared to control samples (0 mg/L) for each time- period (p ≤ 0.05).

This overall low BOD in the sludge in the presence of G suggested that G could be affecting the microbial metabolic activity during biodegradation of the organic matter and other biological processes. Further investigation of the metabolic activity of G showed that G with concentrations ranging from 10 to 300 mg/L presented about 24% to 98% metabolic activity reduction, respectively (Figure 4-4). Further microscopic investigation of the interaction of G with the sludge showed that G is able to interact with the sludge flocs (Figure 4-5). This direct interaction of the G with the sludge would explain the negative impact of G in the sludge metabolic activity.

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Figure 4-4 Metabolic activity assay of activated sludge with different concentrations of G. *Statistically significant different results compared to control samples (0 mg/L) (p ≤ 0.05).

Figure 4-5 Microscopic images of interactions between activated sludge and G (100 mg/L). Scale bar at 20µm

It is worth to note that no significant changes in microbial metabolic activity, BOD and COD were observed in the reactors containing 1 mg/L of G (Figure 4-3). These results suggest that acute toxicity can lead to reduced microbial metabolic activity and that G at concentrations higher than 1 mg/L can impact the wastewater treatment chemical parameters.

4.3.2 Acute toxicity of G on the wastewater biological processes

The reduced metabolic activity results suggest that other biological process for wastewater treatment could be in jeopardy, such as phosphorous and nitrogen removal. In wastewater,

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nitrogen and phosphorus need to be removed because of eutrophication effects and human health problems.318 The removal of these compounds requires microbial communities present in the sludge, such as AOB and PAO. During microbial activity, under aerobic conditions, ammonia is converted to nitrate, and phosphate is removed and accumulated intracellularly by PAO.

The results showed that the ammonia removals in the control and in 1 mg/L G reactors were

54% and 53% after 5 h of incubation and 81% and 80% after 10h, respectively. When the G concentrations were 10, 100, and 300 mg/L, the ammonia removals after 5 h were 43%, 27%, and 23%; and after 10 h, they were 69%, 53%, and 38%, respectively (Figure 4-6a). Based on these results, the 300 mg/L of G exhibited the highest toxicity to the nitrifiers. To confirm the reduced ammonia transformation to nitrate, we measured the amount of nitrate produced by the activated sludge. The results showed no significant increase in nitrate concentrations in the reactor having 300 mg/L of G, even after 10 h (Figure 4-6b). This indicated that the ammonia oxidation decreased, since nitrate was not produced from the activity of ammonia oxidizing microorganisms.

Figure 4-6 a) Ammonia concentration and b) nitrate concentration produced before and after 5 and 10 h in the presence of different concentrations of G. * Statistically significant different results compared to control samples (0 mg/L) (p ≤ 0.05).

The ammonia-oxidizing bacteria (AOB) population abundance in the sludge exposed or not to G was further investigated by real-time PCR. Two genes were investigated to determine the

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abundance and activity of AOB: the conserved region of the 16S rRNA gene for AOB and the amoA gene. The amoA gene encodes the active site of ammonia monooxygenase, an enzyme unique to nitrifying bacteria.319 The initial inoculated activated sludge in the reactors (time 0 h) had a concentration of 54 AOB gene copy/ng. The gene copies increased to 224 and 221 copy/ng for 0 and 1 mg/L after 10h running reactors with freshly prepared synthetic wastewater media, respectively (Figure 4-7). A similar trend was also observed for the amoA gene copies that were

69 copy/ng and increased to 137 and 139 copy/ng for 0 and 1 mg/µL of G, respectively. These results indicate that at low G concentrations, i.e. 1 mg/L, and short time exposure (10 h) the

AOB population is not affected (Figure 4-7). On the other hand, the reactors with concentrations of G of 10, 100 and 300 mg/L exhibited 58%, 65% and 63% lower concentrations of AOB gene copies and 69, 62 and 56% reduction in the amoA copy numbers in comparison to the control reactors after 10 h of contact with G (Figure 4-7). Clearly, the presence of G impacted the AOB cell growth in the bioreactors, which resulted in lower ammonia removal as observed in figure

4-6.

In the case of phosphate, inhibition of the activity of PAO microorganisms will lead to accumulation of phosphate in the effluent, instead of phosphate removal. The removal of phosphate by the control reactors were 31% and 68% after 5 h and 10 h incubation (Figure 4-

8a). For the reactor containing 300 mg/L of G, only 10% and 23% removals were observed after

5h and 10h incubation, respectively. The abundance of PAO was also determined after 10 h running the reactor. The gene copies for PAO in the reactors with 10, 100 and 300 mg/L G were

41% less than the control reactors (Figure 4-8b). These results suggest that G can inhibit the PAO activity in the activated sludge, and thus prevent the removal of phosphate during wastewater treatment.

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2.5x102 AOB 2.0x102 AmoA

1.5x102

1.0x102  5.0x101

0.0 No graphene 0 1 10 100 300

AOB/amoA genes (copy number/ng) Time 0h Concentration of Graphene (mg/L) Time 10h

Figure 4-7 Abundance of AOB and amoA gene in the activated sludge containing different concentrations of G at initial exposure (before addition of G) and after 10 h. * Statistically significant different compared to control samples (0 mg/L) (p ≤ 0.05)

Similar results were observed in a previous acute toxicity study of activated sludge with

GO. In this study, nutrient removal was increasingly inhibited with increasing concentrations of

GO in the activated sludge.20 This nutrient inhibition trend, however, is not true for all carbon- based nanomaterials since another acute toxicity study with MWCNT on activated sludge did not present any significant change in nutrient removal.19 This difference in nutrient removal could be explained by the different antimicrobial properties of MWCNT and G. For instance,

MWCNT does not display strong short-term antimicrobial activity.320 G, on the other hand, has been shown to have antimicrobial property in less than 1 h exposure.6 In previous studies, the antimicrobial effects of G have been associated to production of reactive oxygen species, nanomaterial large surface area, and sharp edges. 83, 321 The small size of the G used in this study (less than 100 nm) could be one of the reasons for the strong antimicrobial activity observed in the AOB and PAO sludge communities.

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b) 4 1.2x10

9.0x103 * * * 3 6.0x10

3 3.0x10

0.0 No graphene 0 1 10 100 300 PAOgenes (copy number/ng) Time 0h Concentration of graphene (mg/L) Time 10h Figure 4-8 a) Phosphate concentrations in the reactors before and after 5 and 10 h exposure to different concentrations of G; b) Abundance of PAO under different G concentrations. * Statistically significant different compared to control samples (0 mg/L) respectively for each time-period (p ≤ 0.05).

4.3.3 Changes in the sludge Microbial community exposed to G

Besides looking at the impact of acute toxicity of G in specific microbial communities, i.e.

AOB and PAO, we also investigated the effects of G in the total bacterial community abundance and composition. The change in abundance of the eubacterial community was determined by real-time PCR with universal primers for the 16S rRNA gene. Increasing concentrations of G resulted in reducing concentrations of 16S rRNA gene copies from 39% to 49% in concentrations ranging between 10 and 300 mg/L after 10 h exposure, respectively (Figure 4-9). This trend was not observed in the control and in the reactor with 1 mg/L of G, which presented an increase in the concentration of gene copies (Figure 4-9). These results suggest that in these reactors the microbial community is growing over time. These results corroborate well the findings for the

PAO and AOB microbial communities.

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1.2x106

* 9.0x105 *

*

6.0x105

3.0x105

0.0 300 No graphene 0 1 10 100 16SgenesrRNA (copynumber/ng) Time 0h Concentration of graphene (mg/L) Time 10h

Figure 4-9 Change in the total microbial community abundance in the reactors with different concentrations of G at initial exposure (before addition of G) and after 10 h

In order to investigate the overall changes in the sludge microbial community structure, 16S rRNA gene deep sequencing was performed with the Illumina MiSeq. The Basespace cloud system showed that there were 2,216,142 effective reads, after filtering out the low-quality reads. The reads identified to the genus level accounted 40% of all reads. There were 1,486 operational taxonomic units (OTUs) identified at the species-level.

In all reactors, Proteobacteria was the predominant phylum with 57 to 60% of the total bacterial sequences identified (Figure 4-10a). Other dominant phyla were Bacteroidetes (18 to

24%), Firmicutes (4 to 5%), Verrucomicrobia (4 to 5%), and Actinobacteria (2 to 3%). The dominance of Proteobacteria, Bacteroidetes and Actinobacteria were similar to a previous report investigating the sludge microbial community exposed to MWCNT.19

In the reactors, the phyla Bacteroidetes and Proteobacteria were the most affected by the presence of G in the sludge (Figure 4-10a). In the phylum Proteobacteria, the Beta-

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proteobacteria was the most abundant class in all samples at time 0 h and in the samples having

0 and 1 mg/L of G. This class includes ammonia-oxidizing genera.322 In the reactors containing G, the Beta-proteobacteria class decreased when compared to the control reactor (Figure 4-10b).

The decreasing number of microorganisms in this class would explain the reduction in ammonia removal rates observed earlier (Figure 4-6a).323

In the case of Bacteriodetes, the classes most affected were Sphingobacteriia and

Flavobacteriia (Figure 4-10b). These two classes are commonly found in wastewater treatment plants and they are involved especially in protein degradation.324, 325 In the reactors containing

G, both these classes decreased in abundance. The reduction of these classes could explain the lower BOD and COD removals. In the case of Flavobacteriia, which contains the genera

Flavobacterium, this class has been reported to participate in formation of flocs in the sludge.

Hence, reduced abundance in this class could potentially affect the wastewater treatment settling process.326

a b ) )

Figure 4-10 The top 10 phylum (a) and top 20 classes (b) with the highest abundance in the reactors with different concentration of G. Results are presented at 0 h and 10 h. The abundance was expressed in terms of percentage of total effective sequences in each sample (excluding unclassified phyla/ classes). Less abundant phyla/ classes were presented as others.

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At the genus level (Figure 4-11), some important genera involved in the wastewater treatment from the Proteobacteria and Bacteroidetes phyla changed in the presence of G. For instance, the genera most affected were Dechloromonas, Curvibacter, Rubrivivax, Pedobacter,

Zoogloea, and Flavobacterium. (Figure 4-11) Among these genera, Dechloromonas have been described to promote removal of phosphate removal in biological reactors.327 Besides being involved with phosphate removal, Dechloromonas and Curvibacter have also been described to reduce perchlorate in bioreactors.328, 329 In the presence of G, the levels of these genera went below the detection limit of the deep sequencing method. This result, i.e. the significant reduction of Dechloromonas in the reactor, is consistent with the lower removal of phosphate in the presence of G (Figure 4-8).

Rubrivivax and Pedobacter, on the other hand, have been associated with COD and BOD removals.330, 331 The reduction of these genera is consistent with the decrease in COD removal observed in the present study (Figure 4-3a). In the case of the Zoogloea and Flavobacterium, both genera decreased in the presence of G (Figure 4-11). Both genera have been reported to be abundant in heavy metal polluted sewage samples.332 Zoogloea have also been reported to be resistant and have heavy metal biosorption capabilities.333 Furthermore, species of Zoogloea have been widely reported in activated sludge, and to play an important role in the flocculation of activated sludge.334, 335. Therefore, the decrease of Zoogloea in the reactors containing G would potentially reduce the sludge settling ability.

Both Zoogloea and Flavobacterium have been previously reported to be sensitive to nanoparticles, such as silver, titanium dioxide and zinc, hence it is not surprising that it is also sensitive to G.333, 336 Flavobacterium was shown to not be resistant to nano-Ag, but to be resistant to silver ions.336 Clearly both of these genera are not resistant to G, since the presence of G reduced their presence in the reactors (Figure 4-11). Many other species have also been

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shown to be affected by the presence of G at concentrations higher than 1 mg/L, but it is still unclear their role in the wastewater treatment process and therefore they are not discussed in this study.

24 Genus Phylum

20 Dechloromonas Curvibacter Proteobacteria Rubrivivax 16 Azohydromonas Zoogloea Vogesella 12 Thermomonas Pedobacter Lewinella Bacteroidetes

8 Flavobacterium Percentage (%) Percentage

4

0 No graphene 0 1 10 100 300 Time 0h Concentration of Graphene (mg/L) Time 10h

Figure 4-11 Percentage changes of abundance of the most abundant genera identified in the reactors. The abundance was expressed in term of percentage of total effective sequences of each sample (excluding unclassified number of genera)

4.4 CONCLUSIONS

This study aimed to determine the acute toxicity of different concentrations of graphene to the microbial community involved in the wastewater biological treatment process. The results showed significant effects on the chemical and biological parameters of the reactors in the presence of graphene at concentrations higher than 1 mg/L. The changes in the biological parameters of the wastewater treatment in the presence of graphene was further confirmed by investigating the changes in abundance of ammonia oxidizing bacteria and phosphate

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accumulation organism communities and the total microbial community. Results also showed that the graphene acute toxicity involved significant reduction of the microbial community metabolic activity, which led to reduced biological oxygen demand, nitrogen and phosphorous removals. Additionally, the presence of graphene led to significant changes in the sludge microbial community structure. The deep sequencing analyses showed that several important genera involved in the wastewater treatment process were no longer detected in the reactor when graphene was present, probably because they were below the detection limit of our number of sequencing reads. The concentrations of graphene impacting the wastewater biological treatment process were overall smaller than the ones observed for graphene oxide and MWCNTs, which suggests that graphene can be more deleterious to the wastewater treatment process than other carbon-based nanomaterials. It is important to highlight, however, that the relatively high concentration of graphene necessary to impact the wastewater treatment process (concentrations higher than 1 mg/L) suggest that the impact of graphene in wastewater treatment will most likely happen in waste streams from industries or manufacturers of graphene and carbon-based nanocomposites or in case of accidental spills of this nanomaterial.

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CHAPTER 5 TOXICITY OF GRAPHENE AND GRAPHENE OXIDE IN SEQUENCING BATCH BIOREACTORS: A COMPARATIVE INVESIGATION

5.1 RATIONALE AND OBJECTIVES

Recently, G based nanomaterials have been intensively used due to the unique characteristics and broad applications of these materials in different fields, such as water and wastewater treatment, medical devices, electronic and aerospace.2, 3, 337 The global market of these nanomaterials is expected to grow and reach up $986.7 million dollars by 2018.338 A recent study by Lazareva & Keller estimated, based on nanomaterial production data of 2010, that the presence of carbon nanotubes in the wastewater treatment plants of New York City would be around 1.5 mg/Kg and 0.2 g/L per year in biosolids and treated effluents, respectively.339 These results showed that CNTs, which is a material made of G, will tend to be retained in the biosolids. It is expected that GO and G, since they are also made of G, will behave similarly in wastewater and biosolids as CNTs. Hence, the increasing production of GO and G will probable lead to similar accumulation trends in sludge as CNTs since the productions of GO and

G have increased over the years in a similar fashion as CNT back when Keller’s group performed their estimations for CNTs.

In previous studies, the impact of carbon based nanomaterials in wastewater treatment has been investigated mostly in very high concentrations and for one or three days as acute toxicity assays.19-21, 340 These studies aimed to simulate worse case scenarios in case of industrial spills.

These nanomaterials, however, will most likely be introduced in the wastewater treatment plants in much smaller concentrations than the ones previously investigated since the release of nanomaterials will be the result of direct consumption and disposal, as well as wear and tear of products containing CNTs, G or GO. Hence, in this study, we aim to simulate the entrance and accumulation over time of GO and G in the wastewater influent when introduced in smaller

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amounts. We hypothesize that G, which is more hydrophobic and prone to aggregation in aqueous environment, will interact and accumulate more in the sludge flocs than GO. We also hypothesize that accumulation of the GO and G in the sludge flocs will eventually hinder the biological treatment process due to the antimicrobial properties of these nanomaterials. In order to investigate these hypotheses, we set up bioreactors to simulate the wastewater treatment process. These reactors were fed with low concentrations of G and GO in the influent for up to 10 days, which was when the performance of the reactors was sub-optimal, but the microbial population seemed to start to recover or get adapted to the presence of the nanomaterials. Through these ten days, we monitored the performance of the reactors by investigating chemical oxygen demand, biological oxygen demand, microbial metabolic activity, nitrogen and phosphate removals, as well as gene abundances for ammonia oxidizing bacteria

(AOB), phosphate accumulating microorganisms and (PAO) ammonium monooxygenase (amoA) genes. The changes in microbial diversity structure and abundance were also determined using the 16S rRNA gene deep sequencing technique. We also monitored the release of these nanomaterials in the effluent using a previously published technique.341 Through mass balance, we determined the accumulation of these nanomaterials in the sludge over time.

5.2 MATERIALS AND METHODS

5.2.1 Activated sludge batch reactors with continuous feeding of nanomaterials

All the reactors were set up with activated sludge freshly collected from the aeration tank from the Sims South Bayou Wastewater Treatment Plant (Houston, TX. USA). The reactors were fed with synthetic wastewater (SWW) with or without the nanomaterials. Detailed information on the components of the reactor and the SWW preparation procedure can be found in our previous study 21 and Table 5-1.

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Table 5-1 Characteristics of synthetic wastewater and Sims South Wastewater Treatment activated sludge mixture

Parameters Synthetic wastewater Sims South pH 7.3 ± 0.7 7.1 ± 0.3

Ammonia – nitrogen (NH3 – N) (mg/L) 50 ± 1 5.25± 0.15 Nitrate – nitrogen (NO3 – N) (mg/L) 35 ± 1 22.45± 1.5 Phosphate (mg/L) 60.7 ± 1.5 0.23 ± 0.02 Chemical oxygen demand (COD) (mg/L) 498.1 ± 9.6 65 ± 2.1

The acclimation of the activated sludge to the SWW was done prior to introducing the nanomaterials in the influent. Steady ammonia removal was used as an indicator of stability and efficiency of the reactor. The reactor for acclimation was set up in a 4 L beaker with 3.5 L active volume comprised of 1.5 L of SWW and 2.0 L of freshly collected activated sludge from the wastewater treatment plant. The reactor was designed to have a 12 h cycle, which included 0.25 h of feeding with SWW without mixing or aeration, 1 h of mixing only, followed by 8 h of mixing and aeration continuously, then 2 h of settling and a total 0.5 h for decanting effluent and taking samples for analysis, and a 0.25 h for idle period.336 This allowed a hydraulic retention time of 24 h and a sludge retention time period of 20 days.19 The feeding with SWW during the acclimation period was of 1.5 L synthetic wastewater without nanomaterials. Samples were collected for analysis at the end and at the beginning of each cycle. The pH of the reactors were not adjusted, but monitored at the time of sample collections. The reactors were fully acclimated at cycle 16, where ~ 100% removal efficiency of ammonia was obtained (Figure 5-1). We continued to run the reactors until cycle 21 to ensure that the microbial community in the sludge was stable.

After that, using the acclimated sludge, we started the reactors with G and GO.

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60 100 Influent Effluent

Removal (%) -N/L) 80 45 3

60 30

40 Removal(%) 15 20

0 0 (mgNH Influent/Effluent 0 1 2 3 4 5 6 7 8 9 10 11 Time (days)

Figure 5-1 Ammonia removal efficiency (mg/L) during the acclimation of the reactor for 21 cycles (10.5 days). The reactor became acclimated after 16 cycles (8 days).

A total of five reactors were set up in triplicate with the acclimated sludge. More details about the reactors set-up and acclimation process can be found in previous study.21 Among the reactors set up, there were control reactors (without nanomaterials) and reactors containing 1 or 5 mg/L of G and 1 or 5 mg/L of GO. Each reactor contained 495 mL of acclimated sludge, 500 mL of SWW with or without nanomaterials. The time period for each cycle was the same as the acclimated reactor. For analysis in each cycle, a volume of 500 mL of effluent was taken and a volume of 500 mL SWW, with or without nanomaterials, was added as influent to the reactor.

Each reactor received in each cycle the same influent concentration of nanomaterial that was used at the initial reactor set up. The results of the triplicate reactors were averaged and their standard deviations were calculated.

5.2.2 Analysis of chemical parameters

At each cycle, the effluent of each reactor was analyzed for the following nutrient removals:

3- ammonia (NH3-N), nitrate (NO3 -N), phosphate (PO4 ) and chemical oxygen demand (COD).

Effluent and influent were collected and filtered through 0.2 µm sterile syringe filters (Corning,

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U.S.A). Ammonia and nitrate were analyzed using Orion Dual Star benchtop equipped with

Orion™ High-Performance Ammonia Electrode and Orion™ Nitrate Electrodes (Thermo

Scientific, U.S.A). Hach kit was used to measure phosphate and COD with a spectrophotometer

DR3900 (Hach, U.S.A). All the results were expressed as days running the reactor versus concentrations measured (mg/L).

Biological oxygen demand (BOD) was one of the most important parameters to determine the biological activity of the reactors. It was used to evaluate the oxygen consumption by microbes during biological activity in the activated sludge. BOD was analyzed using BOD5 standard method with 2 mL of sludge.301 Statistical analysis using t-test was conducted for this investigation. Besides BOD5, metabolic activity of the microbes in activated sludge and microscopic images were also investigated using Vibrant Cell Metabolic Assay kit (Invitrogen,

U.S.A) and SYTO9 and propidium iodide (PI) dye as described in previous study.21

5.2.3 DNA extraction and real time PCR (RT-PCR)

Activated sludge samples were collected at 0, 2, 4, 6, 8 and 10 days. Amounts of 0.5 g of settled activated sludge were collected for DNA extraction with the PowerWater DNA isolation kit (Mobio, U.S.A.). All DNA samples were investigated with RT-PCR for three genes, namely: ammonia oxidizing bacteria (AOB), monooxygenase ammonia bacteria (amoA) and phosphate accumulation organisms (PAO). The analyses of the abundances of the genes were determined using standard curves with serial dilutions of known concentrations of the genes cloned into a plasmid provided by the TOPO TA cloning kit (Invitrogen, U.S.A.). Details about the standard curves and thermal conditions for the RT-PCR were described in our previous study.21 All the samples were run in triplicate. The triplicate DNA extracts from each triplicate reactors were averaged out. The results were expressed in concentrations that were normalized to 1 ng of

DNA template versus concentrations of nanomaterials.

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5.2.4 16S rRNA metagenomics sequencing

Metagenomics of all the samples with and without G and GO of the reactors were investigated using Illumina Miseq (Genome Sciences, Bioscience Division, Los Alamos National

Laboratory, New Mexico). The 16S rRNA gene libraries for each sample were prepared as described by Illumina with only modifications in the PCR amplification procedure.

The DNA was amplified in a 25 µl reaction containing 80 ng of DNA template, 12.5 µl of 2x

AmpliTaq Gold® Fast PCR Master Mix (ThermoFisher Scientific, U.S.A.), 500 nM final concentration of each primer (IDT, Coralville, IA) and nuclease free water was added to obtain a final volume of 25 µl. The following conditions were used for thermal cycling: initial denaturation at 95°C for 10 min and 35 cycles of 95oC for 3 sec, 55oC for 3 sec, 68oC for 15 min; and a final elongation step at 72oC for 10 min. Electrophoresis gel was run for confirmation of amplification. PCR products were cleaned-up, followed by index PCR reaction to incorporate the barcode. The pooling procedure was done following the protocol described by Illumina, U.S.A for the 16S rRNA library preparation.

The conserved region targeted for analysis was the V4 region of the 16S rRNA gene using the primers F515 and R806 with Illumina adapters and barcodes.342 More details on the library preparation and analysis can be found in the supporting information. Pair-end sequencing was employed using 600-cycle MiSeq® Reagent Kit V3 (Illumina, U.S.A.). The output results from sequencing were analyzed using Ilumina basespace 16S Metagenomics v1.0.1. The data of metagenomics were deposited on the NCBI database under accession number SRP082429.

5.2.5 Approximated Quantification of the amount of G or GO (GO) in activated sludge

In order to estimate the amounts of nanomaterials accumulated in the activated sludge, the amounts of G and GO were estimated in the effluent after the settling period. To quantify the concentration in effluent, UV-vis light scattering was used as previously described (UV 2600,

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Shimadzu, U.S.A).341 The quantification was carried out using a standard curve made with G or

GO at 0 mg/L, 0.1mg/L, 0.5mg/L, 1 mg/L, 1.5 mg/L, 2 mg/L, 2.5 mg/L, 3 mg/L, 4 mg/L, 5 mg/L, 8 mg/L, 10 mg/L, 15 mg/L, 20 mg/L, 25 mg/L, 30 mg/L, 35 mg/L, 40 mg/L, 45 mg/L and 50 mg/L using the effluent of the control reactor (without nanomaterial) as the dilution media. These solutions were scanned in the wavelength range of 200 nm to 800 nm (Figure 5-2). The effluent from the control reactor was used as baseline zero to subtract the blank signal coming from the effluent without G or GO.

3.5 0.075 3.0 Graphene 0.1 mg/L Graphene oxide 0.1 mg/L Graphene 1 mg/L Graphene oxide 1 mg/L 0.060 2.5 Graphene 5 mg/L Graphene oxide 5 mg/L 2.0 0.10 0.045 0.08 1.5 0.06 0.030 0.04

1.0 Absorbance 0.02

Absorbance 0.015 0.00 0.5 200 300 400 500 600 700 800 Wavelength (nm) 0.000 0.0 200 300 400 500 600 700 800 200 300 400 500 600 700 800 Wavelength (nm) Wavelength (nm)

Figure 5-2 Spectra of G and GO after subtracting the background of effluent control without nanomaterials showing the increasing in absorbance when G and GO increased (scanning from 200 to 800 nm using UV 2600).

For G quantification, we selected the wavelength of 400 nm as reported in a previous study.341 GO showed a major peak at 230nm and a peak at 300 nm. These peaks have been reported previously by other researchers.343, 344 To minimize the interference of the organic matter present in the sludge, also detected at the wavelength of 230 nm, we selected the

300nm peak to quantify the concentration of GO in the effluent. Using these two wavelengths, the concentration of G and GO retained in the sludge was estimated.

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The calibration curves were recorded using absorbance versus concentration of nanomaterial. We were able to obtain an R2 = 0.996 for G and R2 = 0.976 for GO using a linear fitting formula of absorbance = slope x concentration.341 The results of the standard curves prepared in triplicate at the wavelengths of 400 nm and 300 nm for G and GO, respectively are presented in Figure 5-3. The effluents of the reactors were withdrawn in triplicate at the end of each cycle for measurements and the standard deviations were calculated from the absorbance after subtracting from the background of the effluent in the control. From the concentrations of

G or GO in effluent, the amount of nanomaterials in activated sludge was approximately estimated which was displayed in figure 5-4.

0.10 a) Graphene 0.4 b) Graphene Graphene oxide Graphene oxide 0.08

0.3 0.06 y = 0.0075x 2

Abs y = 0.0073x R = 0.976

0.2 2 Abs R = 0.997 0.04

y = 0.0048x y = 0.0051x 2 2 0.1 R = 0.999 0.02 R = 0.996

0.0 0.00 0 10 20 30 40 50 0 1 2 3 4 5 6 7 8 9 10 11 -1 Concentrations (mg/L) Concentrations (mg L )

Figure 5-3 Calibration curves to estimate concentrations of nanomaterials (from 0 mg/L to 50 mg/L (a) and from 0 to 10 mg/L (b)) in effluent using effluent of the control as the dilution media. Standard deviation expressed the triplicate preparation of standard. The wavelengths were used in this experiment: 300 nm (GO) and 400 nm (G).

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Graphene 1 mg/L Graphene 5 mg/L Graphene oxide 1 mg/L 35 Graphene oxide 5 mg/L 30

25 20

15 10

5

at eachcycle (0.5 day) Concentrationof G/GO 0 0 1 2 3 4 5 6 7 8 9 10 11 Time (days)

Figure 5-4 The accumulation concentrations of G and GO in the reactor at beginning of each cycle (0.5 day).

5.3 RESULTS AND DISCUSSIONS

5.3.1 Impact of G and GO on chemical parameters of the wastewater treatment

Chemical oxygen demand is one of the most popular parameters used to measure indirectly the contamination of particulate matter in water and wastewater. In a conventional wastewater treatment, COD removal is also used as a mean to determine the treatment quality of biological processes. The results showed that COD removal reduced significantly after five and half and three days feeding reactors with 1 and 5 mg/L GO, respectively (Figure 5-5). We were able to estimate that there were about 3.64 mg/L (5.5 days) and 12.83 mg/L (3 days) GO in the reactors, respectively. These concentrations were the results of accumulation of the nanomaterials in the activated sludge due to the continuous feeding of nanomaterials in the influent (Figure 5-4).

Consequently, the COD of the effluent in the 1 and 5 mg/L GO reactors were about 92 mg/L (5.5 days) and 78 mg/L (3 days), as opposed to 10 mg/L in the control reactors. The reduction in COD

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removal continued up to nine days then it reached a steady state. In the case of G, significant reduction on the COD removal started after 7.5 and 5.5 days for the reactors fed with 1 and 5 mg/L G, respectively (Figure 5-5). Similar to GO, the COD removal reached a steady state after nine days. Overall, these results showed that lower nanomaterial input, i.e. 1 mg/L, led to less impact and smaller reduction on the COD removal. Additionally, the fact that the COD removal reached a steady state after nine days suggested that some microbes could have been adapting to the presence of G and GO. Therefore, BOD5 and metabolic activity of the microbes in the activated sludge were investigated after ten days to evaluate the metabolic activity of the bacteria in the activated sludge.

Influent Graphene 5 mg/L Control Graphene oxide 1 mg/L Graphene 1 mg/L Graphene oxide 5 mg/L

300

225

150

75

CODconcentration (mg/L) 0 0 2 4 6 8 10 12 Time (day)

Figure 5-5 Chemical oxygen demand in influent, effluent of the control (without nanomaterials) and effluent of reactors treated with G and GO at different concentrations. The errors bar represented the standard deviation COD results from triplicate of the reactors (n = 3).

In wastewater treatment, the BOD5 is typically high due to the high metabolic activity of microorganisms consuming the dissolved oxygen during the oxidation process of organic matter in wastewater. However, in the presence of antimicrobial compounds, microorganisms can be

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inactivated, which would yield a lower BOD5 due to fewer microbes performing the organic matter oxidation. At the end of ten days, all the reactors with G or GO presented a lower BOD5 than the control, which suggested that some microorganisms were probably inactivated or metabolic inhibited by the presence of the nanomaterials (Figure 5-6). The impact of G and GO in the microbial metabolic activity was confirmed using the metabolic activity assay (Figure 5-7).

The results showed that the reactors exposed to the nanomaterials presented lower metabolic activities than the control reactors. For instance, the reactors fed with 5 mg/L G and GO presented only 44.5 and 19.1 % metabolic activities compared to the control, respectively

(Figure 5-7). This low activity was corroborated by the live and dead cell staining assay with the activated sludge, which presented a larger number of cells with damaged membrane (in red) in the sludge containing G or GO as opposed to the control sludge (in green) (Figure 5-8). These results suggested that the lower COD removal was probably caused by less active microbes in the activated sludge. It is worth to point out that although G and GO affected the COD and BOD5 removals, a certain number of microorganisms were still metabolic active after ten days exposed to the nanomaterials.

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700

600 500 *

400 *

(mg/L) 5 300 *

BOD 200 * 100

0 Control 1 5 1 5 Graphene Graphene oxide Concentrations (mg/L)

Figure 5-6 Biological oxygen demand (BOD5) of the sludge mixture after 10 days running the reactors. Analyses correspond to the control (without nanomaterials) reactors and reactors with G or GO. (*) Shows that the samples were statistically significant different (t-test with P ≤ 0.05)

120

100

80 * *

60 *

40

20 Metablic(%) activity *

0 Control 1 5 1 5 Graphene Graphene oxide Concentrations (mg/L)

Figure 5-7 Metabolic activity of the reactors containing G and GO at the end of 10 days. The results are expressed as percentage metabolic activity. (*) Shows that the samples were statistically significant different (t-test with P ≤ 0.05)

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Figure 5-8 Activated sludge staining with SYTO9 for control (no nanomaterials), G 5 mg/L and GO 5 mg/L under the fluorescence microscope at 40X magnification showing that there were more dead cell (red) in the sludge with G or GO comparing to the control.

The impacts on COD and BOD5 removals in activated sludge were previously reported with carbon based nanomaterials in long and short term assays.19-21 Acute toxicity studies with

MWCNT and G agreed with our G and GO results that low concentrations (1 mg/L) of these nanomaterials do not impact COD removal.19, 21 However, in the case of chronic toxicity, reactors continuously fed with 1 mg/L of G and GO took several days to show an impact on the COD removal. This impact, however, lasted a few days, before the microbial population could adapt to the presence of these nanomaterials and reach a steady COD removal. These results were not observed in the chronic toxicity study with 1 mg/L MWCNT.19 Clearly, different nanomaterials will present different toxic behaviors, this was more evident with our GO and G reactors, since the impact on COD removal and BOD5 were lower for G than for GO at each corresponding time period, even though the accumulation of G in the sludge was higher than GO. Just to illustrate this observation, at five and half days, the COD removal reduction in the 5 mg/L GO reactors was higher than in the 5 mg/L G reactors and the amounts of G and GO accumulated in the sludge were 21.11 mg/L and 16.09 mg/L, respectively (Figure 5-4). Clearly, this study shows that GO tends to impact more the COD removal and BOD5 because of its higher antimicrobial properties than G, as previously described.5, 6, 35 Due to the overall impact of the nanomaterials in the

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biochemical wastewater treatment parameters, it is highly possible that these nanomaterials might affect as well as the microbial communities involved in specific nutrient removals, such as ammonia and phosphate.

5.3.2 Impact of chronic toxicity of G and GO on the wastewater biological process

Nitrogen and phosphorus are the two most important nutrients that are typically removed in the aerobic biological wastewater treatment process. These nutrients are essential to organisms, but they are also responsible for causing serious environmental problems, if in excess in the environment.345 The aeration process helps in the removal of these pollutants in

3- the form of ammonia (NH3-N) and phosphate (PO4 ). After setting up the reactors with the nanomaterials, it took about 4 to 4.5 days for the reactors with 5 mg/L GO to start to show reduced removals of ammonia and phosphate compared to the control reactors. While the 1 mg/L G and GO reactors took about 7 to 8.5 days to start to show changes in nutrient removal.

The 5 mg/L G reactor also showed an impact in the ammonia removal after four days, but not in the phosphate removal, which took about six and half days (Figure 5-9 and 5-11). The production of nitrate correlated well with the ammonia oxidation results (Figures 5-9 and 5-10), which showed that less nitrate from ammonia oxidation was being produced in the 5 mg/L reactors with G and GO. Overall, the 5 mg/L GO reactors were the ones with the most pronounced effects on the nutrient removal. Based on the mass balance results of the 5 mg/L reactors, after four days running the reactors, there was about 14.08 mg/L of GO accumulated in the sludge as opposed to 16.68 mg/L of G accumulated in the reactor. The ammonia concentrations in the effluents were 9.5 and 11.6 mg/L for 5 mg/L G and GO, respectively, while it was 0.2 mg/L for the control at four days.

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Influent Control Graphene 1 mg/L Graphene oxide 1 mg/L Graphene 5 mgL Graphene oxide 5 mg/L 30

20

10

Ammoniaconcentration (mg/L) 0 0 2 4 6 8 10 Time (day)

Figure 5-9 Nitrogen residual as ammonia in influent and effluent for the control and reactors treated with G and GO at different concentrations. The results are expressed as concentration versus time in days. The errors bar represented the standard deviation ammonia results from triplicate of the reactors (n = 3). Influent Graphene 5 mg/L Control Graphene oxide 1 mg/L Graphene 1 mg/L Graphene oxide 5 mg/L 80

60

40

20

Nitrateconcentration (mg/L) 0 0 2 4 6 8 10 Time (day)

Figure 5-10 Nitrogen residual as nitrate in influent and effluent for the control and effluent of reactors treated with G and GO at different concentrations. The results are expressed as concentration versus time in days. The errors bar represented the standard deviation of nitrate results from triplicate of the reactors (n = 3).

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Influent Graphene 5 mg/L Control Graphene oxide 1 mg/L Graphene 1 mg/L Graphene oxide 5 mg/L

30

20

10

0

Phosphateconcentration (mg/L) 0 2 4 6 8 10 12 Time (days)

Figure 5-11 Phosphorus residual as phosphate in influent and effluent for the control and effluent of reactors treated with G and GO at different concentrations. The results are expressed as concentration versus time in days. The errors bar represented the standard deviation of phosphate results from triplicate reactors (n = 3).

Despite the fact that there was more G accumulated in the sludge than GO, the reactors containing GO were the most affected. Previous studies have shown that microorganisms are more sensitive to GO than G.6, 35 This sensitivity of microorganisms to GO was explained by the hydrophilic nature and the presence of functional groups in GO. The presence of functional groups in this nanomaterial makes it more prone to interact with biomacromolecules, heavy metals and other contaminants in the water.37, 175 These bio-interactions could explain the higher toxic effects of GO to the sludge microbial community as compared to G. Additionally, other studies showed that the presence of functional groups in GO led to the production of more reactive oxygen species, which is responsible for generating oxidative stress in microorganisms and cellular inactivation.20

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On the other hand, G is more hydrophobic and tends to aggregate in aqueous solutions, which explained its higher accumulation in the sludge. These aggregates were not, however, as single flakes, but as large aggregates, which could have reduced the direct contact of G with the microorganisms in the sludge and therefore reducing its toxicity to the microorganisms. The formation of large aggregates of G in the sludge flocs were also confirmed by microscopic observations (Figure 5-12).

(b) Sludge without G (c) Sludge with G (a) G suspension

(a) GO suspension (b) Sludge without GO (c) Sludge with GO

Figure 5-12 Images of G and GO stained with Syto 9 only showing the nanomaterial suspensions in SWW (a), in the sludge (c) and the control images of the sludge without the nanomaterials (b). Larger aggregates of nanomaterials are observed in the sludge with G than GO. Images are in 10 m scale

In the reactors, concentrations of G and GO as low as 5.68 and 3.48 mg/L, respectively, started to affect the removal of ammonia and phosphate (1 mg/L nanomaterials reactors). The inhibition was more pronounced in concentrations as high as 16.68 and 14.08 mg/L for G and

GO, respectively, in the 5 mg/L nanomaterials reactors (Figure 5-4). It is important to point out that even though the concentration of these nanomaterials continued to accumulate in the

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sludge due to the continuous feeding of nanomaterials to the reactors, the removal of the nutrients still occurred in a steady manner, but with a lower performance than the control reactors (Figure 5-9 and 5-11). Clearly, the removal of nitrogen and phosphate did not get completely inhibited with the continuous addition of nanomaterials to the wastewater. It is possible that some species of, but not all, ammonia oxidizing bacteria (AOB) and phosphate accumulating organisms (PAO) are sensitive to these nanomaterials. This sensitivity could have led to their population reduction in the presence of these nanomaterials and consequent ammonia and phosphate removal reductions. In that case, a subset of the AOB and PAO populations or certain species in these populations could have been resistant and survived in the presence of these nanomaterials and were able to continue to perform the removal of nutrients in the sludge. The low, but steady removal of these nutrients could be an indication that the surviving species of AOB and PAO require some time to gain enough biomass to reach the same level of ammonia and phosphate removal as the control reactors.

These hypotheses were further investigated with the quantification of AOB and PAO in the sludge. We quantified the AOB and PAO populations in the reactors using specific 16S rRNA genes for AOB and PAO. We also investigated the changes of the functional gene ammonia monooxygenase (amoA) overtime in the reactors, as previously described.346 Significant reduction in the PAO, AOB and amoA gene abundances were observed after four days for 5 mg/L of GO reactors (Figure 5-13 and 5-14), which corresponded to the lowest phosphate and ammonia removal in all the reactors (Figure 5-9 and 5-11). In the case of the 1 mg/L reactors, there were also changes in the AOB and PAO populations after eight days, which matched the period where there were changes in the nutrient removals in these reactors.

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Graphene 5 mg L-1 Control Graphene oxide 1 mg L-1 Graphene 1 mg L-1 Graphene oxide 5 mg L-1 ) -1 a) 150

100

50

0 AOBgene (copy number ng 0 2 4 6 8 10 )

-1 Time (days)

60 b)

45

30

gene (copy number ng 15

amoA 0 0 2 4 6 8 10 Time (days) Figure 5-13 a) Abundance ammonia oxidizing bacteria gene (AOB) and b) ammonia monooxygenase genes (amoA) in activated sludge, expressed as gene copy number per µL which were normalized to per nanogram of DNA.

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Graphene 5 mg/L Control Graphene oxide 1 mg/L Graphene 1 mg/L Graphene oxide 5 mg/L 1.5x104

1.2x104

9.0x103

6.0x103

3.0x103 PAOgene (copy number/ng) 0.0 0 2 4 6 8 10 Time (days)

Figure 5-14 Abundance phosphate accumulating bacterial (PAO) genes in activated sludge, expressed as gene copy number per µL which were normalized to per nanogram of DNA.

It was, however, observed that the AOB and PAO populations slowly recovered after ten days running the reactor (Figure 5-13 and 5-14). It is possible that after ten days these populations are still acclimating to the increasing presence of these nanomaterials in the reactors. This was corroborated by the fact that the abundance of the AOB population increased from 83 to 110 copy/ng for G and 37 to 90 copy/ng for GO in the 5 mg/L reactors between six and ten days (Figure 5-13a). While the PAO populations increased from 7.0 x 103 to 8.5 x 103 copy/ng for G and 6.9 x 103 to 9.8 x 103 copy/ng for GO in the 1 mg/L reactors between eight and ten days (Figure 5-14). The PAO population also increased in the reactor 5 mg/L GO from 5.6 x 103 to 9.5 x 103 copy/ng. Interestingly, the PAO increase only occurred in 1 mg/L G reactors, but not in the 5 mg/L G reactors. This was not the case for the AOBs. These results suggest that the PAO is probably much more sensitive to G than AOB. This sensitivity was also clearly seen by an earlier removal reduction of phosphate nutrients than the ammonia removal, even at low

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nanomaterial feeding concentrations, i.e., 1 mg/L for both G and GO (Figure 5-9 and 5-11). This difference could be due to the different and diverse bacterial composition in each group. In the case of PAO, Betaproteobacteria microorganisms are commonly involved in phosphate removal; while AOB is composed by both Beta- and Gammaproteobacteria microorganisms.347, 348

Although we observed a slightly increase in the AOB and PAO populations, the removal of the ammonia and phosphate did not improve over time. It is possible that the AOB and PAO populations require a long time to recover from the increasing presence of the nanomaterial in the sludge. In Wang’s study, which used copper, the AOB population required up to eight days from the initial exposure to copper to recover the nutrient removal efficiency to a similar level as the control.349 In the case of phosphorus removal with copper nanoparticles, the PAO population took more than 40 days to recover in the activated sludge.350 In Chen’s study, the phosphorous removal recovered, but the PAO population changed dramatically. The authors described that other PAO, more resistant to copper, were able to take over and continue to remove the nutrient. In addition to copper nanoparticles, other studies with silver nanoparticles in activated sludge also showed similar trends. In these studies, the activity of both AOB and

PAO populations were found to reach the same removal efficiency as their controls after 4 to 40 days.349-351 In these studies, differences in bioreactor set ups, feeding solutions, source of activated sludge and nanoparticles led to different lengths of the microbial population recovery.

Therefore, it is possible that the microbial community functionality in the wastewater can recover in the presence of G or GO. The fact that they take a long time to recover is because these two populations typically have slow growth rates.348, 352

It is also worth point out that the inhibition of nitrogen and phosphate removals was previously reported in acute studies with carbon nanotubes and GO, but it is the first time that chronic toxicity is investigated with these nanomaterials. This study overall agrees with the fact

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that increasing concentrations of nanomaterials can impact the removal of ammonia and phosphate by affecting the AOB and PAO populations present in the sludge.19, 20 A previous study, on the long term exposure (180 days) of activated sludge exposed to MWCNT at higher loading rate (20 mg/L) led to increase reduction in ammonia and phosphate removals. From 80 days to the end of the experiment, there was no sign of recovery to optimum reactor performance. In Hai’s study, the authors showed that the microbial population was not able to adapt and recover overtime from the high initial dose of nanomaterials.19 In our study, we saw some signs of recovery of the AOB and PAO populations in the reactors after ten days, but these populations did not recover completely to allow satisfactory nutrient removal from the influent.

It is possible, that giving more time to these populations, they could have fully recovered from the presence of these carbon based nanomaterials.

In the case of the amoA gene, the trend observed in this study was similar to other studies with silver ions and silver nanoparticles in activated sludge.333, 336 In these studies, the silver ions and the silver nanoparticles impacted the abundance of amoA gene. Higher effects were observed with higher loading concentrations.336 Studies with pure cultures have shown that both GO and G, like silver nanoparticles, have antimicrobial properties to microorganisms in pure cultures.6, 353 Also, previous studies showed that these carbon based nanomaterials can have different toxic levels depending on the microorganism.5, 354 Different bacteria would express different behavior to toxic environment; hence it is worth to note that there was an increase in amoA gene abundance from eight to ten days in 1mg/L GO and 5 mg/L G reactors, which corroborates the results observed earlier with AOB, but not in 5 mg/L GO (Figure 5-13).

The toxicity of GO was reported in previous studies to be higher than G.4 This could be one of the reasons for the higher impact in nutrient removal in the reactor containing 5 mg/L GO.

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Based on these results, these nanomaterials seem to also hold antimicrobial properties against nitrifiers and PAO in activated sludge, at least to some species belonging to these groups of microorganisms. The initial introduction of toxic materials, such as G and GO, agreed well with others studies for toxicity of nanomaterials to biological process. In these studies, the addition of nanomaterials led to suboptimum wastewater treatment in the bioreactors.292, 355 In some cases the microbial community was able to recover and in others not.336 In the study of

Ma 2015, Nitrospira was impacted differently depending on the methods of feeding Ag or nanoAg. In high dosage feedings, the community was significantly impacted, but not at sequential additions. Clearly the introduction of G and GO, depending on the concentration and frequency, will directly impact the biological wastewater treatment process since these nanomaterials tend to accumulate in the sludge. Now, it is possible (based on the RT-PCR results) that the microbial community in the sludge can potentially adapt to the presence of these nanomaterials. By doing deep sequencing investigations of the population with and without exposure to the nanomaterials, we were able to determine whether the microbial community in the sludge was adapting or other species were being selected and enriched in the presence of these nanomaterials.

5.3.3 Changes in the sludge microbial community exposed to G or GO

In order to understand the overall effect of the chronic toxicity of these nanomaterials in the reactors, we analyzed the changes in the microbial population structure after ten days exposed or not to the nanomaterials. The investigation of the total microbial community in the activated sludge was accessed using deep sequencing 16S rRNA Miseq Illumina. The relative abundances of the phyla in all the reactors are shown in Figure 5-15. The four most abundant phyla observed in the reactors were Bacteroidetes, Proteobacteria, Firmicutes and Verrucomicrobia. These phyla are commonly found in activated sludge of wastewater treatment plants.356 In the reactors

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containing G and GO, there was a clear shift on these phyla. Also, the overall diversity of the reactors with nanomaterials decreased compared to the control reactor. The reactor presenting the lowest diversity was 5 mg/L GO (Table 5-2). The presence of G in the reactors led to increase in the Bacteroidetes population; while the GO reactors, enriched microbial populations from the

Proteobacteria phylum. These results indicate that G and GO do not impact the same populations in the activated sludge.

Figure 5-15 Relative abundances of different phyla in activated sludge in 5 reactors with G or GO and control, expressed in term of percentage of the total readings. The top abundances from 0.1% or greater was selected to show along with all the other reactors with G or GO.

Table 5-2 Abundance analysis of the 16S metagenomics sequencing of the samples with and without G or GO at the end of 10 days

Number of Shannon Simpson Identified ACEa Chao1 JackKnif Shannonb Simpsonc Species Samples evenness evenness species (Sace) (Schao1) e (Sjack.k) (H’) (1/D) richness (J') (E1/D) (Sobs)

Control 754 1264.15 1264.15 754 3.74 0.564 17.48 2.640 6.625

G 1 mg L-1 616 906.46 906.46 616 3.84 0.598 18.41 2.870 6.423

G 5 mg L-1 628 959.76 959.76 628 3.94 0.612 20.02 3.110 6.443

GO 1 mg L-1 598 1037.68 1037.68 598 4.14 0.648 23.48 3.670 6.394

GO 5 mg L-1 302 474.22 474.22 302 3.34 0.585 18.04 3.160 5.710 a ACE: Abundance-base Coverage Estimator; b Shannon diversity index (mean among runs), natural logarithms; c Simpson (inverse) diversity index (mean among runs)

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At the genus level, the microbial communities in the different reactors containing nanomaterials changed significantly compared to the control reactor (Figure 5-16). The heatmap of the relative abundance of the genus shows significant shifts at the genus level between the control reactor and the reactors with G or GO (Figure 5-16). Several genera that was found in the control reactor either disappeared or reduced to a number that was below the detection limit of the Deep Sequencing analysis in the GO and G reactors. That was the case for Lewinella,

Zoogloea, Dechloromonas, Candidatus Accumulibacter, Runella, Curvibacter, Thauera and

Thermomonas that are well-known microorganisms playing an essential role in biological wastewater treatment processes.

Lewinella, for instance, was described to biodegrade organic matter and hydrocarbons.357

The reduction of the abundance of this genus could have affected the removal of COD, as observed in our reactors. Zoogloea is another important genus for wastewater treatment that has the capability in helping the formation of sludge flocs and also reducing nitrate in wastewater.358-360 The consequences of the reduction of this population in the sludge could have yielded poor sludge flocculation and inefficient nitrogen removal in the wastewater. Another microorganism involved in nitrogen removal that also presented reduced abundance in the sludge containing G and GO was Thauera. This microorganism plays an important role in denitrification and removal of organic matter in wastewater.361-363 Thermomonas was also shown to be a denitrifier in a full-scale wastewater treatment plant and in petroleum contaminated soil.364, 365 The reduction of these populations clearly has reflected in the nitrogen and COD removals of the reactors.

In the case of the phosphate removal, Dechloromonas, Runella and Candidatus

Accumulibacter play an essential role in phosphate removal in wastewater.366-370 Runella have also been shown to improve formation of granular sludge.371 The reduction on the PAO gene

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copy in the GO and G reactors could be explained by the reduction in these populations in the activated sludge. In addition to these microbes, Dechloromonas and Curvibacter were affected by the presence of G and GO. These two genera were reported in a previous study to reduce perchlorate in biological treatment, so they can also play a role in the wastewater treatment.329

It is worth to note that the reduction of Lewinella, Zoogloea, Dechloromonas, Curvibacter,

Thermomonas and Flavobacterium in this study was also observed in an acute toxicity study with G in activated sludge.21 These results confirm that these populations are really sensitive to the presence of carbon based nanomaterials.

Even though some important groups of microorganisms involved in biological wastewater treatment were affected by the presence of G and GO, the results show that some populations were actually selected and enriched in the presence of these nanomaterials (Figure 5-16). It is important to point out that not the same groups of microorganisms were enriched in the G and

GO reactors. For instance, in the G reactor, Olivibacter, Haliangium and Dokdonella were enriched, while in the GO reactor Chryseobacterium, Pseudomonas, Stenotrophomonas,

Acinetobacter, Brevundimonas and Pseudoxanthomonas were the ones enriched (Figure 5-16).

Some of these microorganisms have also been described to be involved in nutrient removal in wastewater. Specifically, Olivibacter, Haliangium and Pseudoxanthomonas were reported dominantly in nitrogen removal in which they were isolated from cow manure, biofilters for hydrocarbon clean-up, and full scale denitrification and granular sludge.364, 372, 373

Stenotrophomonas and Chryseobacterium were not directly associated to nutrient removal in wastewater treatment plants, but they have been reported in previous studies to be important in nitrogen cycling and dominant in biofilm reactors treating ammonia contaminated air.374, 375

Dokdonella, Pseudomonas and Acinetobacter have been described to have the capability of accumulating phosphate. These genera were isolated and identified from phosphate removal

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activated sludge processes.376-378 Hence, they play essential roles in nutrient removal in activated sludge. These genera could have adapted to the presence of the nanomaterials and were able to continue to remove the nutrients in the reactor, but probably with lower efficiency than the original microorganisms responsible for nutrient removal in this group. These results would explain the observed increase in PAO and AOB populations in the RT-PCR analyses and the observed steady nutrient removal in the bioreactors during continuous additions of nanomaterials.

5.4 CONCLUSIONS

In conclusion, the accumulation of graphene and graphene oxide in the sludge overtime resulted in significant impact of the ability of the activated sludge to remove nutrients, such as chemical oxygen demand, biological oxygen demand, ammonia and phosphate. The concentrations of graphene and graphene oxide starting to impact the wastewater treatment were as low as 5.26 mg/L and 3.64 mg/L for graphene and graphene oxide, respectively, which were the results of an accumulation of these nanomaterials in the sludge during the feeding of 1 mg/L every day. The reactors receiving higher nanomaterial feedings (5 mg/L) resulted in higher and faster accumulation of graphene and graphene oxide in the sludge, which generated higher impacts in the wastewater treatment. It was noticeable that graphene oxide was more toxic than graphene, due to the fact that graphene oxide is more hydrophilic and therefore aggregates less in the sludge; and also because graphene oxide is more reactive toward biomolecules than graphene. These properties made graphene oxide present higher antimicrobial properties than graphene. The results also showed that the phosphate accumulating organism and ammonia oxidizing bacteria community started to recover after 8 days and that at that time, there was a shift in the microbial community structure and diversity.

These results suggest that the microbial community in the sludge can adapt to the presence of

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these nanomaterials over time through natural selection of the more resistant populations to these nanomaterials. Also, the different toxicity mechanisms of graphene and graphene oxide led to the selection of completely different populations of microorganisms in each reactor.

Caloramator Haliangium Vogesella Thalassospira Olivibacter Dokdonella Megasphaera Prosthecobacter Chitinophaga Runella Niastella Candidatus Amoebophilus Flavisolibacter Thiothrix Luteibacter Dyella Uliginosibacterium Candidatus Accumulibacter Lysobacter Thauera Haliscomenobacter Lewinella Paracoccus Luteimonas Candidatus Liberibacter Zoogloea Rhodobacter Flavobacterium Hylemonella Comamonas Curvibacter Thermomonas Sulfuritalea Giesbergeria Dechloromonas Pedobacter Segetibacter Niabella Rhodanobacter Aquimonas Methyloversatilis Azospira Azoarcus Azospirillum Acidovorax Burkholderia Pseudoxanthomonas Brevundimonas Chryseobacterium Acinetobacter Pseudomonas Delftia

Stenotrophomonas

1

1

-

-

1

-

1 -

-0.11 - 0.11 < -1 0.11 - 0.33

Time day 0 Time -1 - -0.78 0.33 - 0.56 Control 10 days 10 Control

Graphene 5 mg L mg 5 Graphene -0.78 - -0.56 0.56 - 0.78 Graphene 1 mg L mg 1 Graphene -0.56 - -0.33

Graphene oxide 5 mg L oxidemg 5 Graphene 0.78 - 1 Graphene oxide 1 mg L oxidemg 1 Graphene -0.33 - -0.11 > 1

Figure 5-16 Heatmap of relative abundances of different genera in the reactors with and without G or GO. Color scale from Red (lowest abundance) to Green (highest abundance).

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