The effects of silver nitrate and silver nanoparticles on ...

The effects of silver nitrate and silver nanoparticles on Chlamydomonas reinhardtii: a proteomic approach

Anna Lena Lindgren Degree Project for Master of Science in Ecotoxicology, 60 ECTS credits Department of biology and environmental sciences University of Gothenburg February 2014

Abstract Silver has a broad antibacterial effect and is widely used in food storage, household products, disinfectants, medical equipment etc. During recent years of development in nanotechnology the use of silver nanomaterials (AgNP) have increased. The physiochemical properties of silver nanomaterials, and the relative low cost of production, has made them very popular. While the toxic mechanism of silver is known the toxic mechanism of action of silver nanoparticles has not yet been confirmed. Studies have been made investigating the difference in toxicity of silver ions and AgNP in order to see if the toxicity is due to particle or the release of free Ag+. The aim of this study was to investigate the toxic mechanisms of silver nanoparticles and silver nitrate in the green alga Chlamydomonas reinhardtii using a proteomic approach, with 2D gel electrophoresis (2-DE). Concentration response tests were made with concentrations of AgNO3 and AgNP ranging from 0.5-100 µg/L and 0.001 to 2200 µg/L respectively. The observed concentrations corresponding to approximately 20 percent effect (EC20) were chosen for exposures for proteomic tests, 10 µg/L for AgNO3 and 215 µg/L for AgNP. The results suggest that both silver nitrate and silver nanoparticles tends to regulate in similar ways suggesting that the toxicity is mainly due to release to free silver ions. The regulated spots were analysed and identified through LC-ESI-MS/MS. It was not possible to identify the exact proteins that contribute to the difference in protein regulation due to the vast number of proteins that matched for each spot. The oxygen evolving enhancer protein 2 of PSII seemed to be down regulated by both silver nitrate and silver nanoparticles.

Sammanfattning Silver har en bred antibakteriell effekt och används flitigt i utrustning för matförvaring, hushållsprodukter, desinfektionsmedel, medicinsk utrustning med mera. Under senare år har utvecklingen inom nanoteknologin lett till en ökad användning av silvernanomaterial. Silvernanopartiklarnas fysikaliska och kemiska egenskaper och dess relativt låga produktionskostnad har gjort dem mycket populära. Medan mekanismen bakom silvers toxicitet är känd har silvernanopartiklens verkningsmekanism ännu inte bekräftats. Skillnaden mellan silverjoners och silvernanopartiklars toxicitet har undersökts för att se om silvernanopartikelns toxiciteten kommer ifrån själva partikeln i sig eller ifrånsläppandet av silverjoner. Syftet med denna studie var att undersöka den toxiska mekanismen av silvernanopartiklar och silvernitrat hos grönalgen Chlamydomonas reinhardtii, genom att använda proteomik med 2D gelelektrofores (2-DE). Koncentrationer mellan 0.001 – 2200 µg/L för AgNP och 0.5-100 µg/L för AgNO3 testades. Den observerade koncentrationen motsvarande 20 procent effekt (EC20) valdes för exponeringar för proteomik tester, vilket motsvarade10 µg/L för AgNO3 och 215 µg/L för AgNP. Resultatet tyder på att effekten av både silvernitrat och silvernanopartikeln regleras på samma sätt, vilket indikerar att toxiciteten i huvudsak orsakas av silverjoner. De reglerade punkterna analyserades och identifierades genom LC-ESI-MS/MS. Det var inte möjligt att identifiera exakt vilka proteiner som upp- respektive nedreglerades på grund av väldigt många proteinträffar per analyserad punkt. Oxygen Evolving enhancement protein 2 av PSII verkade nedregleras av både silvernitrat och silvernanopartiklar.

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Table of Contents Abstract

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Sammanfattning

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1. Introduction Silver Silver in the environment Uptake and bioavailability Toxicity Proteomic approach The aim

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2. Material and methods Chemicals Flow Cytometer and growth rate Toxicity tests Concentration response analysis Exposure experiments for proteomics Harvesting Samples preparation and two dimensional gel electrophoresis (2-DE) Samples preparation Homogenization of cells Protein cleaning Protein level measurement Two-dimensional gel electrophoresis (2-DE) First dimension: Isoelectric focusing (IEF) Second dimension: SDS-PAGE Data analysis Analysis of silver

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3. Results Optimization of method Toxicity tests 2-DE

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4. Discussion Concentration response tests and using silver as a compound Proteomic results

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5. Summary and Conclusion

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Acknowledgments

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References

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Appendix I

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Appendix 2

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1. Introduction Silver Silver is a noble metal that has a high electrical conductivity, heat stability and special optic properties. This has made it popular to use in electronic and photochemical industry. It is and has also been used in jewelry, coins and also in medicine for a long time (Hiriart-Baer et al., 2006; Luoma, 2008; Winjhoven et al., 2009). Silver has a broad antibacterial effect and due to this, it is widely used in food storage, household products, disinfectants, textiles, medical equipment etc. (Blaser et al., 2008; Navarro et al., 2008; KemI, 2012; Poynton et al., 2012). The recent years of development in nanotechnology have also increased the use of silver nanoparticles, (AgNPs), (Luoma, 2008; Choi et al., 2008; Oukarroum et al., 2012; Farkas et al., 2010; Fabrega et al., 2011). AgNPs is commonly used as coating for many products such as medical devices, food storage containers, handrails etc. AgNPs is also spun down in fabrics and some cases as powder for use in shoes (Luoma 2008). The optical and physical properties of AgNPs make it also very useful in medical applications (Winjhoven et al., 2009). Nanoparticles have at least one dimension of 100 nm or less (Luoma 2008; Tejamaya et al., 2012). Engineered nanoparticles typically consist of a core coated with a shell or a cap with molecules that prevent aggregation and to keep the nanoparticles as stable as possible (Levard et al., 2012). There are many different types of coatings or “capping agents” that act and stabilize the nanoparticles differently. Citrate is a very common organic capping agent, which stabilizes the nanoparticles by charge repulsion, while another capping agent, Polyethylene glycol, (PEG), sterically stabilizes the nanoparticle (Tejamaya et al., 2012). The physiochemical properties of silver nanomaterials, and the relative low cost of production, has made its use very popular and fast growing (Luoma, 2008; Fabrega et al., 2011).

Silver in the environment Like many industrial products that are produced and used in large quantities, silver is most likely to end up in the aquatic environment (Navarro et al., 2008; Blaser, et al 2008; Fabrega et al., 2011). Blaser et al. (2008) estimated the production of silver - containing products to reach about 110-230t by 2010 in Europe, and then stabilize by 2015, this is also confirmed by Fabrega et al, 2011, who state that the silver production worldwide 2011 was about 500t. Blaser et al. (2008) also estimated in their analysis that in 2010 15% of emitted silver in water was going to be from biocidal plastics and textiles. There are several routes of discharge of AgNPs; synthesis, production, transferring goods (Fabrega et al, 2011). Different models of routes of silver and silver nanoparticles have been modeled (Blaser et al., 2008; Fabrega et al., 2011). These show that silver ends up in sewage waste treatment, into sludge, some into surface waters. A study investigated how persistent singly dispersed silver nanoparticles, behaved in different freshwater systems. Results demonstrated 3

that AgNP partly agglomerated in the sediment at early release point. However, some fractions were kept stable for a while. This could pose a risk for AgNP to travel to marine waters (Chinnapongse et al., 2011). Concentrations of dissolved silver have been measured around ng/L in aquatic environments (Luoma, 2008). Also, higher concentrations, over 0.1 mg/L, have been found in surface waters (Dewez & Oukarroum 2012).

Uptake and bioavailability The form of silver will affect the uptake and bioavailability. The form depends on the physiochemical condition of the environment and the bioavailability of silver is dependent on its speciation (Ratte, 1999; Fortin and Campbell, 2001). Silver binds strongly with reduced sulphur, chloride, thiosulfate and organic material (Choi et al., 2008; Ratte, 1999). Silver in reducing condition will be in metallic state or in sulphide complexes, which is insoluble in water. In oxidative condition silver is commonly found in complex with bromide, chlorides and iodides. In polluted water silver thiolates have been found. With increased salinity an increase in formation of silver- chloro complexes will happen (Winjhoven et al., 2009). Silver uptake decreases with increasing salinity (Ratte 1999). The uptake of silver can be through different routes such as adsorption to cell surface, through different ion channels and ligands (Ratte, 1999). For silver ions, Ag+, uptake rate and bioaccumulation are high (Luoma, 2008). Silver ion, Ag+, has been reported to have high bioconcentration factors, (>105), for freshwater green algae and marine algae (Piccapietra et al., 2012; Ratte 1999). However, most of the silver tends to attach on the surface of the alga. Since sulphide concentration is often much higher than silver in water, this lead to a low concentration of free Ag+ ions in water, thus making the main form of silver in aquatic environments sulphide complexes, (Ratte, 1999; Hiriart- Baer et al., 2006 and Luoma, 2008; Dewez & Oukarroum, 2012). Fortin and Campbell (2001) tested the hypothesis that silver could when in complex with thiosulphate enter the membrane through anion transporters used in algae for assimilation of sulphate. The silver uptake increased when thiosulphate was in presence and sulphate concentrations were low indicating a competition in transport. A follow up study investigated if this was unique to Chlamydomonas reinhardtii and also how the increase of uptake would affect the toxicity and came to the conclusion that the uptake of silver by thiosulphate complex was not unique to Chlamydomonas reinhardtii but appears in other alga and that increased uptake lead to increase toxicity however not that much (Hiriart-Baer et al., 2006). Uptake of silver nanoparticles by aquatic organism is likely through membrane, epithelia, gills and surface. Moore (2006) states that at cellular level, most intakes of nanoparticles will occur via endocytosis. The uptake of carbonated AgNP was tested on a cell wall free mutant of green algae Chlamydomonas reinhardtii. Results showed that cell free wall had a higher accumulation rate of AgNP than the cell wall containing Chlamydomonas renhardtii, which indicate that the cell wall protect and limit the uptake of silver. However, the results showed little uptake and low bioavailability in both strains of Chlamydomonas reinhardtii (Piccapietra et al., 2012). 4

Toxicity Silver ions have been found to be toxic to several organisms such as bacteria, algae and fungi amongst many others (Wood et al., 1996; Ratte, 1999; Moore 2006; Choi et al., 2008; Navarro et al., 2008). Studies with silver, mainly silver nitrate, have resulted in LC50 around 6.5-65 µg/L for fish (Wood et al., 1996) while for the more sensitive organisms, algae, the EC50 has been reported to be lower: 188 nM (Navarro et al., 2008), 15-30 nM (Hiariart-Baer et al., 2006) down to 12 nM (Lee et al. 2005). For the most sensitive organisms to silver, bacteria and Daphnia magna, EC50 is as low as 0.4-0.8 nM (Lok et al., 2006) and 1.10 µg/L (Völker et al., 2013) respectively. For E.coli more than 50% inhibitory effects on growth was observed at 4.2 µM AgNP, while at the same concentration 100 % effect was observed for silver ions. In most cases the toxicity of silver ions is much higher than silver nanoparticles. The toxicity is of silver is hypothesized to be due to disruption of membrane transport processes that disturb osmoregulation and finally lead to cell death (Choi et al., 2008; Luoma, 2008; Poynton et al., 2012). The toxicity of silver is high when exposed to organisms in early development phases and when taken up via food (Luoma, 2008). Silver ions also inhibit different important cycles (S, N and P), of nitrifying bacteria, disturb DNA transcription, destroy cell wall of bacteria and thus its membrane permeability which could cause cell lysis (Ratte, 1999). Wood et al. (1996) investigated the mechanisms of action of silver nitrate to adult rainbow trout. It was noticed that when an increase of salinity, Cl-, in water occurred it seemed to decrease the toxicity. Results also showed that exposure of AgNO3 gave similar effects, internal physiological disturbances, as exposure of acid conditions. They concluded that it was most likely because of Ag+ binds to the gill surface and interferes with Na+/Cl- uptake, which leads to decrease in plasma Na+ and Cl- concentrations, fluid balance etc. Some indications of disturbance of photosynthesis have also been reported. HiriartBaer et al., 2006 suggest in their study that the intracellular targets for silver ions in Chlamydomonas reinhardtii are more likely to be enzymes and proteins not associated with photosynthetic processes but for another green alga, Psuedokirchneriella subcapitata, the photosynthetic apparatus was targeted (Hiriart-Baer, 2006). The toxicity of nanoparticles depends on the shape, size, structure of the particle and aggregation (Choi et al., 2008; Oukarroum et al., 2012; Poynton et al, 2012; Dewez & Oukarroum, 2012). The aggregation, in turn, will depend on different types of factor in the aquatic environment such as pH, organic matter, ionic strength and ionic composition etc. (Oukarroum et al., 2012). Nanoparticles are found to be reactive because of their small sizes leading to a high volume surface ratio which in turn leads to a lot of binding sites for metals and other compounds (Moore 2006; Farkas et al., 2010). This allows them also to quite easily enter membrane and accumulate inside cell and cause damages (Choi et al., 2008; Oukarroum et al., 2012). Silver nanoparticles have been reported to have an effect on reproducibility, DNA and development (Winjhoven et al., 2009). Study on 5 dpf zebrafish embryos showed effects on survival, embryonic growth and pigmentation at high concentration of AgNP and effects on swim bladder and larval swimming at low concentration of AgNP. Results also showed that AgNP changes the neurobehavioral endpoints and that changes are differently from Ag+ (Powers et al., 2011).

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Due to their physiochemical properties AgNP can act as catalyst and produce reactive oxygen species, ROS, (Choi et al., 2008, Moore 2006). The formation of free radicals on the surface of AgNPs have been observed (Kim et al., 2007) and an induced formation of ROS in two green algae fresh water alga Chlorella vulgaris and marine water alga Dunaliella tertiolecta, has also been observed (Oukarroum et al., 2012). Dewez and Oukarroum (2012) state that exposure of 50 nm AgNP at concentrations of 1, 5 and 10µg/L on Chlamydomonas reinhardtii indicated inhibitory effect on photosystem II (PSII). The study showed agglomeration of AgNP as a potential source of toxicity. The study also showed different sensitivities depending on if light treated or dark treated, where more effects on PSII were seen in light treated organisms. This would suggest AgNP to induce ROS formation with the help of light (Dewez and Oukarroum 2012). Other possible mechanisms for toxicity have been suggested to be interaction of thiol-groups that are part of important proteins, enzymes that are involved in cellular respiration and ion transport (Levard et al., 2012), Same study also suggests that nanoparticle’s toxicity could be caused by formation of aggregation of algae cells when exposed to nanoparticles. This would lead to decreased light and nutrition and thus and negative effect of growth (Oukarroum et al., 2012). Several hypotheses about the toxic mechanism of action of silver nanoparticles have been formulated, however still there is none really explaining it. Studies have been made investigating the difference in toxicity of AgNO3 and AgNP in order to see if the toxicity is due to particle or the release of free Ag+. It has been suggested that the toxicity of AgNP is due to the release of Ag+ (Piccapeitra et al., 2012; Navarro et al., 2008). Navarro et al. (2008) found indirect evidence that the toxicity of AgNPs is due to Ag+ release and that algae might contribute to more Ag+ by oxidation (H2O2 production) during exposure. Meanwhile, there are studies that have shown that AgNPs affect differently than Ag++ (Powers et al., 2011; Poynton et al., 2012). A study made by Poynton et al. (2012), investigated the difference in the change in genes of Daphnia magna when exposed to two different types of silver nanoparticles and silver nitrate. Results showed similar regulation of genes when exposed to silver nanoparticles but different from AgNO3. This suggests that the toxicity of AgNP is not only contributed by the release of Ag+.

Proteomic approach To further understand the toxic mode of chemicals and to find new biomarkers proteomic is a valid choice of method and a good tool. Proteomics is the study of proteins expressed in an organism, tissue or a cell (Bodson-Kulakowska et al., 2007). When an organism is exposed to outer stress in forms of different anthropogenic compounds, lack of nutrition, excessive light etc this could cause effects on the genomes which in turn regulates the proteins. The term proteomics was developed during the 1990’s when large scal studies of the genome and also the proteome for ecotoxicological purposes became more common.. By looking at proteins and comparing how they are expressed under different types of treatments, early responses were able to be observed and finding out more information about chemicals mode of action and perhaps also relevant biomarkers, which could be used for environmental monitoring. There are different types of methods used in proteomics. A traditional method is two-dimensional gel electrophoresis (2-DE). The method aims to separate the proteins due to their isoelectric point (pI) and their molecular weight. The proteins are extracted and separated in two dimensions on a gel, where each spot on a gel represent a protein. Samples preparation is a fundamental step in this since impurities and poorly solubilized proteins could interfere with the separation and result 6

in unclear gels. The better extraction of proteins together with good conditions in the two separations steps results in clearer images and thus better result when continuing to analysis. When separation is done, the gels are stained and scanned for visualization and analysis. By using software program such as PDQuest or Progeneisis Samespots, intensity of different spots are measured and compared in order to find differently expressed proteins or in some cases just to identify proteins. The final step is identification, which is done with mass spectrometry (MS) usually coupled with liquid chromatography and tandem mass spectrometry (LS-MS/MS) for a better result (Bodson-Kulakowska et al., 2007; Cañas et al, 2007). However, 2-DE has been recognized with some drawbacks, such as poor reproducibility between technical replicates, the range of protein able to be quantified -it is not applicable for low weighted proteins e.g. This has developed other methods that is now also used in proteomics (Albertsson, 2011). Nevertheless, proteomics is used for detecting effects at sub-cellular level and could be an approach in environmental risk assessments in order to get a better understanding of toxicants effects and thus make better toxicity predictions (Nestler et al., 2012; Albertsson, 2011).

The aim The aims of this study were (i) to investigate the toxicity of silver ions and silver nanoparticles to the green algae Chlamydomonas reinhardtii and (ii) to compare the mode of action of both toxicants using a proteomic approach. This was done in three steps: -

Optimizing the proteomic method, two-dimensional gel electrophoresis (2-DE) for work with Chlamydomonas reinhardtii. Focus of the optimization was on samples preparation since this step is crucial to obtain good results.

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Find a concentration, which corresponds to a low effect concentration (ECx) by doing toxicity tests, for both AgNO3 and AgNP. By exposing Chlamydomonas reinhardtii to low concentration of silver it would enable observation of more specific responses caused by silver.

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Comparing and analyzing regulated proteins of AgNO3 and AgNPs, using Progenesis Samespots software program to quantify and then LC-MS/MS to identify, this to in order to understand the toxic mode of action.

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2. Material and methods Chemicals The chemicals that were used were silver nitrate, AgNO3, CAS number: 7761-88-8 (Sigma Aldrich) and silver nanoparticles, (AgNPs), 20 nm PEG - 5000 (Cline Scientific). The AgNPs were in MilliQwater with a concentration of 0.06 mg/ml. The AgNPs were coated with Mercaptopropionylaminoetylmethyl polyethylene glycol (PEG) 5000 and characterized by Cline Scientific.

Test organism and cultivation Test organism was the unicellular freshwater green alga Chlamydomonas reinhardtii strain number 81.72 from Göttingen University. C. reinhardtii was grown in sterile cell culture flasks with constant shaking at 20°C (underneath lamp 21-23°C), at a 16:8 h light and dark cycle. Light intensity was 140 µmol*s-1*m-2 (±15%), using Lumilux de lux, cool daylight 6500k lamps. The algae were grown in Woods Hole MBL medium (MBL) pH 7.2 (See appendix I). The algae culture was diluted twice a week when not used in experiments, in order to maintain the culture.

Flow Cytometer and growth rate The growth of C. reinhardtii was measured with FACSCalibur Flow Cytometer and Cell Quest program. The settings were as followed; parameter FSC: E00, Log mode; parameter SSC: 250, log mode and parameter DDL: FL1. Calibration beads were used to count cells. Absolute cell count = (number of events/ number of calibration beads) x calibration number (cells/ml) In order to obtain the proper cell density following formula was used: Average growth rate = (ln(density at 72h)- ln(starting density))/number of days (3days =72h) The growth rate was approximately ten fold per day.

Toxicity tests In order to obtain low effect concentrations (around EC20) for exposure experiments, toxicity tests were made. These were made according to OECD guideline 201 Freshwater Alga and Cyanobacteria, Growth Inhibition Test.

Concentration response analysis AgNP 20nm and AgNO3 were tested in a variety of concentrations ranges (See appendix 2). For AgNPs, between 6-8 concentrations were tested with 3 replicates and for AgNO3, 5 concentrations with 2 replicates were tested. 6 controls were used in each test. 8

The tested concentrations for silver nanoparticles were between 0.001 to 2200 µg/L and for silver nitrate to 0.05 to 100 µg/L. The tests were carried out in small cell culture flasks with the same conditions settings as for cultivation of C. reinhardtii. The cell density of the culture was measured with flow cytometer and diluted to 2-7*105 cells/ml. 9 ml of test concentration was mixed with algal suspension of 1 ml. Initial cell numbers in each flasks were 2-7*104 cells /ml. Flasks were randomly placed on shaker and the positions were changed every 24th hour. pH was checked in the beginning of the experiment and in the end. After 72h of exposure the cells were counted and growth rate was calculated, concentration response curves were made and effect concentrations (ECx) -values were estimated.

Exposure experiments for proteomics A concentration corresponding to a low effect concentration obtained by toxicity tests was used for both AgNPs and AgNO3. In each experiment run both AgNP and AgNO3 was used as exposure. The tests were carried out in large cell culture flasks, with the same conditions as for cultivation of C. reinhardtii. 11 replicates from each treatment; control, AgNP and AgNO3, making a total of 33 flasks in each experiment run. Solution was made with MBL-medium (see Appendix 1). Algae were measured with flow cytometer and diluted to 2-7*105 cells/ml. Initial cell numbers in each flask were 2-7*104 cells/ml. The flasks were randomly placed on the shaker and the positions were changed every 24th hour. Exposure time was 72 h. pH was checked in the beginning and in the end of each experiment.

Harvesting After 72h of exposure the treatments were pooled and distributed into falcon tubes and centrifuged with Centrifuge 5810R Eppendorf at 4000 rpm, (3200 rcf), 4°C, 7 minutes. (repeated 3 times) total of 12 falcon tubes. 4 from each treatment. The pellet in falcon tube was transferred with sterile pipette into kryo- Eppendorf tubes and centrifuged again for 9 minutes, 9000 rcf. Any supernatant was removed and the pellets were then snap frozen in liquid nitrogen. Transferred to and store in -80°C freezer until use.

Samples preparation and two dimensional gel electrophoresis (2-DE) For optimizing the sample preparation and two dimensional gel-electrophoresis (2-DE), different buffers, isoelectric focusing conditions and staining colors were used. Methods for sample preparation were taken from different literatures and combined (Förster et al., 2006; Gillet et al., 2006 & Bodson-Kulakowska et al., 2007, Chen et al., 2010; Cid, et al. 2010; Baba et al., 2011; Cañas et al, 2007; Albertsson, 2011).

Samples preparation Homogenization of cells The kryo tubes containing frozen algal pellets were thawed and buffer was added. In the beginning homogenization buffer containing 0.1M (pH 7.4) NaKPO4, 0.15M KCl was used. This was later switched to a lysis buffer containing 7 M Urea, 2 M Thiourea, 4 % Chaps, 100 mM 9

Dithiothreitol (DTT) & 40 mM Tris. This buffer was used in experiments and also as isoelectric focusing (IEF) - buffer. After the addition of buffer samples were freeze-thawed in 3 cycles followed by sonication for 5 sec. Then the samples were centrifuged for 20 minutes at 10 000 x g to remove bigger particles and then ultra-centrifuged at 33 000 rpm (105 000xg) for 60 minutes. The supernatant was distributed into aliquots of 100 -200 µl and stored at -80 degrees until use. Protein cleaning Calibiochem’s Protein Precipitation kit (Calbiochem cat. No. 539180) was used to precipitate the proteins. Precipitation Agent and Wash solution was prepared in advanced according to manufacturer’s protocol and stored at – 20 degrees. Aliquots of homogenized sample were thawed and 4 times sample volume of cold precipitation was added followed by brief vortexing. The samples were incubated for 60 minutes at – 20 degrees. The proteins were then pelleted by centrifugation at 10 000xg for 10 minutes. The supernatant was discarded by careful aspiration. The protein pellets were then washed in 500 µl cold Wash solution and vortexed briefly followed by 2 minutes of centrifugation, at 10 000xg. The wash solution was aspirated and the washing procedure was repeated. After the second washing the pellets were let to dry. After 50 minutes 200µl resolubilization buffer/IEF buffer was added to each pellet. The pellets were let to dissolve in the buffer by vortexing every 15 minutes and placed in water bath at 26-27 degrees. After 60 minutes the solubilized solution was centrifuges and then the supernatant was transferred into a clean Eppendorf tube. Protein level measurement Before proceeding to measure protein with RC DC kit (Bio-Rad Laboratories, Cat. No. 500-0119), about 60µl of each sample, diluted by a factor of 2.5 – 4 was prepared. Protocol for Microfuge tube assay was followed. Reagent A’ was prepared by adding 5µl of Reagent S to every 250µl Reagent A. A protein standard was made from Albumin from bovine serum in resolubilization buffer: 0,2mg/ml, 0,5mg/ml, 0,8mg/ml, 1,2mg/ml and 1,5mg/ml. 25µl of standard and samples was pipetted into clean Eppendorf tubes (one tube for standards and two tubes for samples). 125µl of RC Reagent I was added to each tube and vortexed. After approximately 1 min of incubation at room temperature 125 µl of RC Reagent II was added. The tubes were vortexed and then centrifuged for 8 minutes at 15,000xg. The supernatant was discarded by inverting the tubes on clean absorbing paper, (Kleenex). The tubes were drained dry from liquid as much as possible. A second wash was performed by first adding 125µl of RC Reagent I and after vortex and 1 min incubation at RT 40 µl of RC Reagent II followed by centrifugation at 15,000 x g for 8 minutes. The supernatant was discarded as previous. 127µl of Reagent A’ was added to each standard and sample. The tubes were vortexed and incubated for 5 minutes at room temperature. Before and directly after adding 1 ml of DC Reagent B to each tube the tubes were vortexed. The tubes were incubated for at 15 minutes before transferred to a 96 well plate, two wells per standard and three wells per sample-tube, that is 6 wells per sample in total. Absorbance was read at 750 nm. The concentration was calculated and samples were diluted to a concentration of 0.5µg/µl proteins in a volume about 200µl.

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Two-dimensional gel electrophoresis (2-DE) Different types of focusing conditions and staining colors were tested in order to optimize and get a good image.

First dimension: Isoelectric focusing (IEF) Samples of 200 µl containing about 80µg protein per sample was evenly pipetted into the IEF focusing tray, in each channel. IPG- strips were stripped of their plastic coating and put gel-side down on the sample in channel carefully without causing air bubbles. About two layers of mineral oil drops were placed over the strip and then lid was placed over and the tray was put into the Protean IEF cell. Different types of focusing conditions were used. Both preset methods with rapid focusing and slow focusing was tested: Active rehydration, 12h without pause before going to focusing, 250 V for 15 min (S1: cannot be changed), S2 use default: 8000V – 2:30 hrs or change. Hold at 500V. S3 use default: 8000V , 35000 Vh. Put down number of strips 1-12. (About 22h in total: start at 2 finished around 12.) Active rehydration, 12h without pause before going to focusing, 250 V for 15 min (S1: cannot be changed), S2 use default: 8000V – 2:30 hrs or change. Hold at 500V. S3 use default: 8000V , 35000 Vh. Put down number of strips 1-12. (About 22h in total: start at 2 finished around 12.) The focusing condition used for experiments was: Active rehydration for 12h, at 50 V and 20 degrees, using 11cm IPG-strips, no pause before going to focusing: 250 V for 1h, slow ramping for 2,5h 8000V followed by rapid ramping 35 000 Vh, 800V. Hold step at 500V, total (22h). Second dimension: SDS-PAGE 2% of DTT was added to SDS equilibration buffer. About 4 ml of SDS- equilibration buffer was added to rehydration/equilibration tray per strip. The IPG strips were carefully taken out from focusing tray. Mineral oil was let to drop away before strip was placed in rehydration/equilibration tray gel side up containing SDS- equilibration buffer. With gentle agitation, the strips were let to equilibrate for 20 minutes. Gels were taken out and prepared. IPG strips were taken out and rinsed in SDS running buffer the Agarose sealing gel was pipette in the well of the gel and then IPG strip was quickly put on. The underneath plastic cover strip of the gel was taken off and the gels were placed in electrophoresis tank. 3 µl of protein standard was pipetted to each gel. SDS- running buffer was poured in the electrophoresis tank.

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The tank was put on magnetic stirrer, magnet in the tank. The gel was applied to 50 V for 10 min and then 180-200 V for 50 min. After one hour of electrophoresis the gels were very carefully taken out from the plastic cover. Depending on the staining, different proceedings were followed: Staining with Biosafe-Coomassie: The gels were rinsed with Milli-Q water 3 times. Biorad Biosafe-Coommassie blue was used to stain the gel. The gel was soaked in Coomassie blue for about 1h under gentle agitation. The Coomassie blue was then removed and the gels were let to soak in MQ-water over night in order to let stains appear. Staining with SYPRO Ruby protein gel stain: Gels were washed with 10% ethanol, 7% acetic acid for 30 min. The solution was removed and the gels were covered with SYPRO Ruby protein gel stain overnight (16-18h) with continuous gentle agitation. The gels were then rinsed in 10% ethanol, 7% acetic for about 1 h. Before scanning gels were washed with Milli-Q water. Gels were stored cool and dark in 5% acetic acid.

Data analysis Gels were scanned at Proteomics Core Facility, Göteborg, with Versadoc scanner. The images where then handled and analysed in Progenesis Samespots software program, from Nonlinear Dynamics, now Total lab (http://www.totallab.com). In the program a statistical tool is incorporated, Samespots Stats, which uses one way Anova test, equivalent to t-test for two groups. Spots of interests were manually picked out and then analysed by LC-ESI- MS/MS at Proteomic Core Facility. The analysis was performed by Proteomics Core facility. The results were searched against Gramene database (http://www.gramene.org/Chlamydomonas_reinhardtii/Info/Index) with at least 2 unique peptides at a significance level at 95% to count as a hit. Search window was 10ppm.

Analysis of silver Samples for silver analysis were taken in the beginning, 30 min after addition of algae and after 72h of exposure. Samples filtered with Vivaspin through centrifugation (4000 rpm, 80min, 25⁰C), and unfiltered samples were acidified in 3:1 HCl 37%, and HNO3 65%, stored in dark at cool until sent for analysis. Silver content in the samples were not measured as a part of this thesis.

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3. Results Optimization of method Parts of the methods were taken from different literature in order to get a clear 2-DE gel. First attempt with homogenization buffer (figure 1. a) did not produce a lot of spots. When changing the buffer to a recommended lysis buffer more spots became visible (figure 1. b-d). The settings during the iso-electric focusing conditions were also changed to get the clearest focusing (figure 1. b-d), with better visibility of spots using a combination of slow and rapid focusing (figure 1. d). When changed from Biosafe Coomassie to SYPRO Ruby staining a better gel image was found with more spots, that is a higher resolution. The samples preparation concluded a precipitation step, which was found as a necessary step in order to quantify and continue with 2-DE. pH 3

pH 10

a

101

c

b

d

Figure 1. First gel image (1) shows unexposed C. reinhardtii , using homogenisation buffer (0.1M (pH 7.4) NaKPO4, 0.15M KCl and rapid ramping in IEF. The other gel images (2,3,4) have different isoelectric focusing conditions. 2: rapid ramping, 3: slow ramping and 4: combination of slow and rapid ramping. Lysis buffer (7 M Urea, 2 M Thiourea, 4% Chaps, 100 mM DTT & 40 mM Tris) was used. Gels were stained with Bio-Safe Coomassie stain. Focusing condition nr. 4 was used for further experiments.

13

Toxicity tests Several toxicity tests were made (Fig. 2 and Appendix 2), to find a suitable concentration range (Fig. 2 a), to find different EC-values and in order to have minimal variance as possible. Tests (Fig. 2 a-c) all meet the validity criteria and have coefficient variances of 10 % or less. It was however not possible to statistically estimate effect concentrations. An approximate concentration corresponding to EC20 was estimated from observed data to around 215 µg/L for AgNP and 10 µg/L for AgNO3. Silver nitrate concentration response curves were also compared with earlier silver nitrate tests. Results show a shift in curve (Fig 2 d).

Figure 2. The results of three concentration response tests (CV ≤ 10%), showing results for testing the concentration range, (a) and the observed inhibition for different concentration (a-c). A comparison of the observed inhibition and with earlier studies on AgNO3 made by Matzke et al. (2013).

2-DE Exposure experiments with concentration corresponding to an approximated EC20 from previous toxicity tests were made. First experiment run with a concentration of 10 µg/L AgNO3, resp. 215 µg/L AgNP (approximately 20 % effect in both treatments) resulted in 16 spots that were significantly differently expressed from control (see Annex 2). The experiment was repeated with exact same set up. This resulted in 25 spots (Fig. 4). In both runs the regulation pattern was the 14

same for AgNP and AgNO3 with few exceptions. Both silver nitrate and silver nanoparticles regulates toward the same way.

Figure 3. Gel image shows results from experiment run 1. 16 significantly regulated spots are marked (p< 0,05). In the left corner the upregulation of spot no 883 is illlustrated, showing silvernitrate and silvernanoparticle treatments regulating in the same way.

Figure 4. Gel image shows results from experiment run 2. Showing 25 significantly regulated spots (p< 0.05). In the left corner the down-regulation of spot no 982 is illlustrated, showing silvernitrate and silvernanoparticle treatments regulating in the same way.

15

The two experiment gels were combined and analysed as one set in order to see similar regulated spots, this resulted in 14 significantly regulated spots (Fig.5). The spots were manually cut out and analysed with LC-ESI-MS/MS. Results from analysis was matched using gramene database and resulted in numerous of protein matches per spot (Table 1).

Figure 5. Gel image shows results from combining both experiment runs (fig 3 and fig 4). 14 significantly expressed spots are marked (p< 0,05). In the left corner the down-regulation of spot no 961 is illlustrated, showing silvernitrate and silvernanoparticle treatments regulating in the same way.

Table 1. Results from analysis (LS-ESI-MS/MS) of 14 spots (fig. 5) with the most likely proteins presented. Full report from analysis presented in Annex 2.

Spot nr

Fold p-value 1,7

143 4,04e-004

1,9 144 1.762e004

Protein(s)

Function /Biological process

Unique Peptides

Accession

Elongation factor 2 ClpB chaperone, Hsp100 family Predicted protein Coatomer subunit beta (Beta-coat protein) Cobalamin-independent methionine synthase Elongation factor 2 ClpB chaperone, Hsp100 family Flagellar associated protein Phosphorylase Cobalamin-independent methionine synthase

Protein biosynthesis Protein processing cysteinyl-tRNA aminoacylation ER-Golgi transport Metheonine biosynthetic process Protein biosynthesis Protein processing ATP Catabolic process Carbohydrate metabolism Metheonine biosynthetic process

41 38 13 12 10 38 36 13 13 8

EDO96511 EDP06752 EDP06006 EDO97648 EDO96787 EDO96511 EDP06752 EDP08480 EDO98385 EDO96787

Oxygen-evolving enhancer protein 2 of photosystem II

Photosynthesis (H2O splitting)

3

EDP03062

Glutamine synthetase

Glutamine biosynthetic process

10

EDP03611

-1,9 961 1.093e006

16

Spot nr

Fold p-value 1,8

666

2,788e005 -2,0

1228 2.141e-00 -1,4 665 2.908e004

1,5 1240 3.176e004 1238

-1,4 0,002

1,7 544 0,004

1,4 426 0,004

1,5 1236 0,005 1,5 586 0,006

1248

1,4 0,006

Protein(s)

Function /Biological process

Unique Peptides

Accession

Elongation factor Tu Spermine synthase Chlorophyll a-b binding protein of PSII Geranylgeranyl diphosphate synthase Oxygen-evolving enhanc prot 2 of PSII Plastid ribosomal protein L6 Ribosomal protein L13a Superoxide dismutase Actin Histone H4 Histone H2B UDP-Glucose:protein Transglucosylase Histone H3 Glutamine synthetase Isopropylmalate synthase Membrane AAA-metalloproteas Acetohydroxyacid dehydratase Acetolactate synthase, large subunit

Protein biosynthesis Metabolic processes Photosynthesis, light harvesting Isoprene biosynthesis Photosynthesis (H20 splitting) Translation Translation Antioxidant enzyme Involved in cell mobility Nucleosome assembly Nucleosome assembly Cellulose biosynthetic process Nucleosome assembly Glutamine biosynthetic process Leucine biosynthetic process Proteolysis Branched chain amino acid biosynthesis Branched chain amino acid biosynthesis

6 7 9 6 7 12 7 5 4 3 2 3 5 3 7 5 7 3

DAA00908 EDP08628 EDP00448 EDO96545 EDP03062 EDP00937 EDP03478 EDP05850 EDO98923 EDO96007 EDO95978 EDP08939 EDP08535 EDP03496 EDP08580 EDP00358 EDP03205 EDP01876

Sar-type small GTPase Superoxide dismutase AGG4 (Flagellar flavodoxin) Plastid ribosomal protein L6 Peptidyl-prolyl cis-trans isomerase Glutamine synthetase Actin Rubisco activase RNA binding protein Aspartate carbamoyltransferase

ER-Golgi transport, Protein transport Antioxidant enzyme Negative regulation of transcription Translation Protein folding Glutamine biosynthetic process Involved in cell mobility. Regulates RuBisCo. Carbon fixation. RNA binding Pyrimidine nucleobase biosynthetic process

7 6 5 9 6 10 5 5 6 5

EDO98600 EDP05850 EDP08044 EDP00937 EDP08887 EDP03496 EDO98923 EDP04194 EDP01473 EDP06852

Eukaryotic initiation factor 4A-like protein Ribosomal protein L4 3-phosphoshikimate 1carboxyvinyltransferase Adenosylhomocysteinase 4-hydroxy-3-methylbut-2-enyl diphosphate reductase Elongation factor 2 Thiamine thiazole synthase, chloroplastic Sedoheptulose-1,7-bisphosphatase Photosystem II stability/assembly factor HCF13 Glutamine synthase 3,8-divinyl protochlorophyllide a 8-vinyl reductase Phosphoglycerate kinase RNA binding protein Isocitrate dehydrogenase, NAD-dependent Phosphoribosylformylglycinamidine cycloligase Thiamine thiazole synthase, chloroplastic Photosystem II stability/assembly factor HCF13 Actin Acidic ribosomal protein P0

Translation, Protein synthesis. Translation Amino acid synthesis.

22 10 11

EDP05185 EDP02388 EDO96795

One-carbon metabolism IPP biosynthetic process

8 10

EDP03365 EDO97597

Protein biosynthesis Thiamine biosynthesis Carbohydrate metabolism, Calvin cycle Photosynthesis

8 10 10 7

EDO96511 EDO99354 EDP04487 EDP08171

Glutamine biosynthetic process Possible Chl synthesis

12 10

EDP03611 EDP09906

Glycolysis RNA binding Tricarboxylic acid cycle IMP biosynthetic process

8 5 2 17

EDO98586 EDP01473 EDP00536 EDP07083

Thiamine biosynthesis Photosynthesis

10 11

EDO99354 EDP08171

Cell mobility Ribosome biogenesis, transaltional elongation

11 9

EDO98923 EDP00752

17

Spot nr

Fold p-value 1,4

1247 0,023

Protein(s) Thylakoid lumenal 17.4 kDa protein Ribosomal protein S14 Ribosomal protein S17 Peptidyl-prolyl cis-trans isomerase Ribosomal protein L14

Function /Biological process Translation Translation Translationl elongation Protein folding Translation

18

Unique Peptides

Accession

5 7 3 4 7

EDP01837 EDP00328 EDO96968 EDP03498 EDP04708

4. Discussion Concentration response tests and using silver as a compound The observed EC20 was around 10 µg/L for AgNO3 and for AgNP it was around 215 µg/L. Studies on C. reinhardtii exposed to silver nitrate have resulted in somewhat higher effect concentrations which would make this observed result likely, however most EC50 values are lower than the observed 10 µg/L (Hiriart- Baer et al., 2006; Lee et al., 2005). Comparisons with earlier performed toxicity tests with AgNO3 also showed a difference response curves. This could of course suggest differences in laboratory practice, but considering the properties of silver it is not perhaps uncommon. Silver is known for to easily form complex in different medium and to change form due to photolysis. As already stated silver and its speciation is highly depending on the physiochemical properties of the environment. In this case it could be the medium, light etc. The quantification of silver and free silver ion is thus essential in order to know at what exact concentrations the study is conducted in. To avoid complexion of silver studies have been conducted with very short exposure time and with a “clean” buffer media (Piccapietra et al. 2012). Shorter exposure times and simple buffers are however not environmentally realistic and results should therefore be treated carefully.

Proteomic results The results from both experiment runs show that both silver nitrate and silver nanoparticles tends to regulate protein expression in similar ways with a few exceptions. That is whenever there is an up regulation from control; both silver nanoparticles and silver ion treatments are upregulated. This suggests that the effect from silver nanoparticles is due to silver ion release. It has been shown that C. reinhardtii does not incorporate silver nanoparticles due to its protective cell wall, and even cell wall less mutants have low uptake of nanoparticles (Piccapietra et al 2012) which confirms this result. From the 14 spots analysed there was only one with a significant difference between silver nitrate and silver nanoparticles (spot nr. 1236 Fig. 5 and Table 1). The proteins with the highest score and the highest number of unique peptides identified were proteins involved in thiamine biosynthesis, carbon reduction cycle, (Calvin Cycle) and photosynthesis. In contrast to studies that have shown reactive oxygen species (ROS) formation when exposed to silver and silver nanoparticles, no increase in regulation of typical antioxidant enzyme was found. In fact, the only evidence of proteins involved in antioxidant system was superoxide dismutase, which was found in spots with a down regulation from control. Even though algae are considered to be very sensitive organisms, they have a protective wall and membrane thus can be quite resilient. In this case, concerning silver, daphnids are considered to be the most sensitive organisms (Ratte, 1999; Bodarenko, 2013) Four spots out of the fourteen analyzed were down-regulated (Fig. 5 and Table 1). Proteins that were matched to these are involved in translation, transportation, protein-folding and antioxidant 19

system amongst other things. On the other hand, the types of up-regulated protein were proteins also involved and translation, protein folding and protein transport. Many of the possibly up-regulated proteins were as mentioned proteins involved in protein biosynthesis, glutamine synthesis, proteolysis and photosynthesis (Table 1). These are common proteins that are important for the cell function. This does not mean that it could not the mode of action of the silver compound though. A study with a toxicogenomic approach on Daphnia magna exposed to silver nanoparticles observed general effects on protein metabolism (Poynton et al. 2012). Another study but with a proteomic approach on the gram-negative bacteria E.Coli, elucidated that silver nanoparticles around 10 nm gave a stimulated response in expression of outer cell membrane proteins (Lok et al., 2006). An accumulation of precursor cell envelope proteins was observed which indicated that the mode of action of silver nanoparticle is partly to destroy the proton motive force by destabilization of membrane and destruction of membrane potential. The number of matched proteins per analyzed spots was high. This is most likely caused by a combination using a sensitive instrument for analysis and common problems with smaller 2-DE gel, such as background proteins and poorly focused proteins. It is not possible to determine which of the protein matched that is contributing to the difference in regulation between treatments, even though the number of unique peptides found and score give an indication of that. However, one spot resulted in only one protein match, no 961 (Fig. 5 and Table 1). Oxygen evolving enhancer protein 2 (OEE2) of photo system II (PSII), which was down regulated. The protein is unique for photosynthesizing organisms as it is involved in the photosynthesis and associated in the water splitting part of PSII that is generating the energy that is transferred to PSI. Förster et al., 2006, observed changes of regulation in oxygen evolving enhancer proteins in C. reinhardtii when exposed to high levels of light and stress. Dewez and Oukarroum (2012) also found effects on photosystem II when exposing C. reinhardtii to silvernanoparticles. They also indicated that this have been observed in earlier studies when exposing metals to alga, for example, Faller et al. (2005) observed PSII inhibiting effects at water splitting part of PSII when exposing C. reinhardtii to cadmium. For future work this would be interesting to investigate further.

20

5. Summary and Conclusion The use of proteomics as a way of detecting biomarkers and obtain more information on how chemicals act at proteomic level could be a most relevant and a useful technique for detecting effects at sub-cellular level and as an approach in environmental risk assessments. However, comparing to other approaches used in ecotoxicology it is relatively time consuming and sometimes hard to extrapolate information given to relevant environmental issues. In this case, due to vast number of protein matched it was not possible to identify the proteins affected by silver. Nevertheless, working properly, it is a very informative and a quite sensitive method, which would make it useful for searching for early response signs and develop new biomarkers. The increased use of nanomaterials including the use of silver nanoparticles will require more information on how they affects the environment. More information and further studies would be useful and proteomics would be a good tool for that. This together with proper legislation and techniques for quantifying and monitoring nanomaterial in the environment are needed. In this study it was demonstrated to be the silver ion that is causing the effects from silver nanoparticles. It is not possible to identify the exact proteins that contribute to the difference in protein regulation due to the vast number of protein matched per spot analyzed. The oxygen evolving enhancer protein 2 (OEE2) of PSII involved in photosynthesis seemed to be downregulated by both silver ions and silver nanoparticles.

21

Acknowledgments Thanks to my supervisors, Joachim Sturve, Thomas Backhaus and Åsa Arrhenius at the department of Biological and Environmental Sciences at Gothenburg University. Thanks to Jörgen Bergström at Proteomics Core Facility at Gothenburg University and also thanks to Karine Bresoline de Souza.

22

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Appendix I MBL medium CaCl2

1.838 g (50ml dH2O)

MgSO4, NaHCO3

1.849 g 0.630 g

K2HPO4 NaNO3 NaSiO3*9H2O Na2EDTA FeCl3 *6 H2O Metal mix CuSO4 * 5H2O ZnSO4*7H2O CoCl2*6H2O MnCl2* 4H2O NaMoO4*2H2O Tris stock H3Bo3

0.435 g 4.250 g 1.421 g 0.218 g 0.1575 g (1L dH2O) 0.01 g 0.022 g 0.01 g 0.18 g 0.006 g 7.1 g 12.5*5 g (5 * 50 ml)

Resolubilization buffer/IEF buffer 7 M Urea, 2 M Thiourea 4 % CHAPS 0.002 % Bromophenol blue (from 0.1% stock) 40 mM Tris 0.2% Biolyte (20%) 100 mM Ditiotreitol (DTT) (added prior to use) SDS Equilibration buffer: 50 mM Tris-HCl (1.5 M pH 8.8) 6 M Urea 30 % Glycerol (100%) 2% Sodium dodecyl sulfate (SDS) 0.002 % Bromophenol blue 2 % Ditiotreitol (DTT) (added prior to use) SDS running buffer/electrophoresis buffer: (5x) 25 mM Tris 192 mM Glycine 0.1 % Sodium dodecyl sulfate (SDS) 2,5 L MilliQ H2O

27

Appendix 2 Tables I-III below shows data from toxicity tests made and presented in graphs in results (Figure 2a-c). Table I. Data from toxicity test, range finding test, illustrated in figure 2a (Result part).

Graph 1 Cells/ml 0h 6,90E+04 Treatment Control Control Control Control Control Control AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNO3

Average growth rate controls 1,389003224 Concentration (µg/L) 0 0 0 0 0 0 2185,66194 2185,66194 2185,66194 274,0042546 274,0042546 274,0042546 34,35033854 34,35033854 34,35033854 4,30627827 4,30627827 4,30627827 0,53988935 0,53988935 0,53988935 0,06763449 0,06763449 0,06763449 0,00852173 0,00852173 0,00852173 0,0010787 0,0010787 0,0010787 55,03788

CV % Controls 10,4

pH 0-72h 7,2-8,1

Cells/ml 72h

Growth rate

Inhibition %

9,62E+06 2,92E+06 4,58E+06 2,94E+06 4,53E+06 4,55E+06 1,48E+04 1,48E+04 2,42E+04 2,15E+06 2,01E+06 2,06E+06 8,36E+06 9,71E+06 4,72E+06 3,40E+06 2,63E+06 3,67E+06 1,31E+07 1,07E+07 5,74E+06 4,44E+06 9,95E+06 5,96E+06 2,35E+06 6,15E+06 5,96E+06 3,13E+06 4,88E+06 3,23E+06 8,84E+04

1,64570224 1,248184179 1,398460463 1,250672331 1,394774668 1,396225462 -0,512489941 -0,512722634 -0,349104115 1,146510592 1,124487047 1,131365136 1,598845831 1,64885232 1,408713942 1,299444952 1,213865028 1,324735934 1,74755521 1,682491728 1,473692464 1,388263789 1,657077963 1,486298327 1,175947032 1,496850452 1,486395115 1,27121774 1,419373347 1,282418398 0,082737893

-18,4808078 10,13813666 -0,680865191 9,959004466 -0,415509807 -0,519958326 136,8962384 136,9129909 125,1334273 17,45803231 19,043597 18,54841543 -15,10742403 -18,70759487 -1,419054905 6,447664766 12,60891212 4,626863975 -25,81361798 -21,12943293 -6,097123366 0,053234912 -19,29979246 -7,004670777 15,3387831 -7,764361227 -7,011638989 8,479856793 -2,18646887 7,673475771 94,04336205

28

Graph 1 Cells/ml 0h 6,90E+04 Treatment AgNO3 AgNO3 AgNO3 AgNO3 AgNO3 AgNO3 AgNO3 AgNO3 AgNO3

Average growth rate controls 1,389003224 Concentration (µg/L) 55,03788 9,767525 9,767525 1,732674 1,732674 0,3091634 0,3091634 0,0543584 0,0543584

CV % Controls 10,4

pH 0-72h 7,2-8,1

Cells/ml 72h

Growth rate

Inhibition %

1,05E+05 2,46E+06 2,15E+06 3,65E+06 2,07E+06 2,07E+06 4,72E+06 3,16E+06 7,87E+06

0,13854736 1,191158961 1,146189719 1,32245868 1,133764449 1,134440257 1,408232273 1,274760101 1,579091201

90,02541122 14,24361435 17,48113325 4,790812734 18,37567907 18,32702489 -1,3843776 8,224827763 -13,68520776

CV % Controls 6,78

pH 0-72h 7,2-8

Cells/ml 72h

Growth rate

Inhibition %

1,52E+06 2,46E+06 1,29E+06 1,78E+06 2,28E+06 1,87E+06 1,21E+05 1,02E+05 8,59E+04 1,21E+05 9,33E+04 1,09E+05 9,99E+05 8,23E+05 8,59E+05 1,82E+06 1,97E+06 3,24E+06 3,02E+06 2,20E+06 3,56E+06 1,88E+06 2,52E+06 3,41E+06

1,136796559 1,297209919 1,080890159 1,188664807 1,272015579 1,206768089 0,292436473 0,236380663 0,179016344 0,292914052 0,20642455 0,258271937 0,997030703 0,932487985 0,946697181 1,197658132 1,223209585 1,389498408 1,365253387 1,260690641 1,420583999 1,208081125 1,304774237 1,406495495

5,034090594 -8,366548707 9,704409145 0,701111837 -6,261859537 -0,811203332 75,57039082 80,25319091 85,04530137 75,53049482 82,75566991 78,4244338 16,70987509 22,10165593 20,9146456 -0,050174134 -2,184695852 -16,07616062 -14,05077582 -5,31579487 -18,6729941 -0,920891919 -8,99845797 -17,49606624

Table II. Data from toxicity test illustrated in figure 2b (Result part).

Graph 2 Cells/ml 0h 5,02E+04 Treatment Control Control Control Control Control Control AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm

Average growth rate controls 1,197057519 Concentration (µg/L) 0 0 0 0 0 0 1079,56296 1079,56296 1079,56296 428,89112 428,89112 428,89112 170,4346 170,4346 170,4346 67,74236 67,74236 67,74236 26,85963 26,85963 26,85963 10,689917 10,689917 10,689917

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Graph 2 Cells/ml 0h 5,02E+04 Treatment AgNO3 AgNO3 AgNO3 AgNO3 AgNO3 AgNO3 AgNO3 AgNO3 AgNO3 AgNO3

Average growth rate controls 1,197057519 Concentration (µg/L) 99,88356 99,88356 31,76569 31,76569 10,005343 10,005343 3,193556 3,193556 1,0497966 1,0497966

CV % Controls 6,78

pH 0-72h 7,2-8

Cells/ml 72h

Growth rate

Inhibition %

4,89E+04 4,60E+04 8,07E+04 2,99E+04 5,41E+05 5,51E+05 2,56E+06 2,65E+06 2,49E+06 2,76E+06

-0,00897044 -0,029371963 0,158150126 -0,172487931 0,792182086 0,798824685 1,31104102 1,322090952 1,3018832 1,335317464

100,7493742 102,4536801 86,7884272 114,4093269 33,82255458 33,26764397 -9,521973622 -10,44506477 -8,756946078 -11,54998348

CV % Controls 8,02

pH 0-72h 7,2-8,1

Cells/ml 72h

Growth rate

Inhibition %

2,12E+06 1,28E+06 1,90E+06 1,65E+05 1,18E+05 7,31E+05 1,62E+06 2,07E+06 1,62E+06 2,59E+06 7,70E+06 3,36E+06 1,98E+05 1,88E+05 2,33E+05 3,37E+05 1,48E+06 1,17E+06 1,72E+06 1,49E+06 1,86E+06

1,182514115 1,012787882 1,145596994 0,330546471 0,218817999 0,827085831 1,092682642 1,174770656 1,091339461 1,248852209 1,611736009 1,335348345 0,391051173 0,373796866 0,445570705 0,569297196 1,061809226 0,982775661 1,112585459 1,063807704 1,138585952

-6,185261958 9,055507072 -2,870245114 70,31818637 80,35097739 25,7308437 1,881262058 -5,489928833 2,00187459 -12,14217005 -44,72775262 -19,9091935 64,8850946 66,43446568 59,98944837 48,87928091 4,653577176 11,75049014 0,094064959 4,474121489 -2,24068033

Table III. Data from toxicity test illustrated in figure 2c (Result part).

Graph 3 Cells/ml 0h 6,12E+04 Treatment Control Control Control AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNP 20nm AgNO3 AgNO3 AgNO3 AgNO3 AgNO3 AgNO3 AgNO3 AgNO3 AgNO3

Average growth rate controls 1,113632997 Concentration (µg/L) 0 0 0 1066,72643 589,29381 325,44379 179,81929 99,2404 54,90583 30,31147 16,71985 9,27682 63,53543 35,05775 19,09299 10,787 5,900489 3,2361 1,779855 0,9967188 0,5458222

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Results from Progenesis Samespots Results from spot analysis of 2-DE gels, using C.reinhardtii exposed to concentrations of AgNO3 and AgNP corresponding to an approximated EC20: 10 µg/L AgNO3, resp. 215 µg/L AgNP. The analysis was made with Progenesis Samespots software (http://www.totallab.com) and the results are presented in table IV-VI below. The volume of each spot in the gels were measured and normalized (performed by program) between the different gels for better comparison. Fold indicates number of times a treatment has increased or decreased compared to control group. Table IV. Results from experiment run 1. Spot Anova (pFold Average Normalised Volumes No. value) Control AgNO3 AgNP 883 312

1.975e-005 3.976e-005

1.2 1.2

3.352e+005 3.761e+005

5.874e+005 9.224e+005

6.872e+005 7.529e+005

2187 968 2189

2.631e-004 2.935e-004 7.192e-004

1.1 1.1 1.1

9.871e+005 1.501e+006 5.563e+005

2.247e+006 2.425e+006 1.164e+006

2.383e+006 2.677e+006 1.238e+006

1035 2227

7.346e-004 7.476e-004

1.0 1.1

1.474e+006 1.116e+006

6.682e+005 1.911e+006

6.767e+005 1.666e+006

2205 2173 2207

9.335e-004 0.001 0.002

1.0 1.1 1.2

4.347e+005 1.588e+006 3.441e+006

1.011e+006 2.322e+006 2.166e+006

1.045e+006 2.443e+006 1.862e+006

2044 2281

0.003 0.004

1.3 1.4

1.824e+006 4.866e+006

5.313e+005 3.702e+006

6.827e+005 5.302e+006

2234

0.004

1.1

5.421e+006

9.137e+006

8.184e+006

399 778

0.005 0.005

1.0 1.1

4.771e+006 1.373e+006

7.281e+006 2.239e+006

7.170e+006 2.049e+006

2184

0.012

1.3

3.346e+006

2.023e+006

1.560e+006

Table V. Results from experiment run 2. Spot Anova (pFold Average Normalised Volumes No. value) Control AgNP AgNO3 982 935 953 1301 695 1306 1313

8.839e-006 2.648e-005 5.693e-005 3.070e-004 5.648e-004 6.661e-004 0.001

2.1 1.7 1.7 2.2 1.9 1.6 1.8

3.063e+006 2.171e+006 4.464e+006 6.363e+006 1.233e+006 2.095e+006 1.590e+006

1.431e+006 1.381e+006 3.183e+006 4.759e+006 2.396e+006 1.290e+006 2.661e+006

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1.448e+006 1.264e+006 2.648e+006 2.878e+006 1.980e+006 1.273e+006 2.792e+006

Spot No.

Anova (pvalue)

Fold

1035 1107 1341 1329 1303 847 1311 1317 175 1315 516 176 238 1323 624 1219 1331 617

0.002 0.005 0.005 0.006 0.007 0.011 0.012 0.014 0.015 0.018 0.018 0.025 0.026 0.028 0.032 0.034 0.048 0.497

1.7 1.4 1.4 1.4 1.5 2.1 1.7 1.4 1.6 1.8 1.8 1.7 1.5 1.6 1.3 2.2 1.5 1.2

Average Normalised Volumes Control AgNP AgNO3 1.915e+006 1.152e+006 1.237e+006 4.341e+006 3.070e+006 3.104e+006 2.037e+006 1.824e+006 1.423e+006 1.123e+007 8.268e+006 9.137e+006 2.743e+006 4.048e+006 2.773e+006 6.548e+005 6.068e+005 3.134e+005 2.014e+006 3.218e+006 3.502e+006 3.235e+006 3.728e+006 2.600e+006 1.433e+006 2.277e+006 2.235e+006 1.331e+006 7.519e+005 8.302e+005 1.246e+006 2.038e+006 2.234e+006 1.431e+006 1.524e+006 2.371e+006 1.581e+006 2.296e+006 1.962e+006 2.535e+006 1.937e+006 1.612e+006 2.877e+006 2.657e+006 2.176e+006 2.734e+006 1.222e+006 1.369e+006 7.798e+005 1.147e+006 1.207e+006 1.129e+007 1.137e+007 9.865e+006

Table VI. Results from experiment run 1 and 2 combined. Spot Anova (pFold Average Normalised Volumes No. value) Control AgNO3 AgNP 961 1.093e-006 1.9 2.081e+006 1.150e+006 1.069e+006 666 2.788e-005 1.8 1.005e+006 1.768e+006 1.847e+006 144 1.762e-004 1.9 1.107e+006 2.069e+006 2.101e+006 1228 2.141e-004 2.0 6.397e+006 3.171e+006 4.106e+006 665 2.908e-004 1.4 1.741e+006 1.220e+006 1.344e+006 1240 3.176e-004 1.5 8.069e+005 1.172e+006 1.162e+006 143 4.040e-004 1.7 9.309e+005 1.437e+006 1.597e+006 1238 0.002 1.4 5.840e+006 4.254e+006 4.868e+006 544 0.004 1.7 1.585e+006 2.665e+006 2.454e+006 426 0.004 1.4 6.527e+005 8.707e+005 8.980e+005 1236 0.005 1.5 2.313e+006 2.477e+006 3.404e+006 586 0.006 1.5 5.914e+005 8.566e+005 8.684e+005 1248 0.006 1.4 9.106e+005 1.282e+006 1.232e+006 1247 0.023 1.4 1.298e+006 9.582e+005 9.040e+005

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