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.
1
Table of Contents
Abstract
1
Sammanfattning
1
1. Introduction
Silver
Silver in the environment
Uptake and bioavailability
Toxicity
Proteomic approach
The aim
3
3
3
4
5
6
7
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
8
8
8
8
8
9
9
9
9
9
10
10
11
11
11
12
12
3. Results
Optimization of method
Toxicity tests
2-DE
13
13
14
14
4. Discussion
Concentration response tests and using silver as a compound
Proteomic results
19
19
19
5. Summary and Conclusion
21
Acknowledgments
22
References
23
Appendix I
27
Appendix 2
28
2
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).
5
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.
-
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.
-
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.
7
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.
10
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.
11
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.
12
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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Winjhoven, W.P S., Peinenburg, J.G.M W., Herberts, A. C,, Hagens I. W., Oomen, G. A., Heugens, H.W
E., Roszek, B., Bisshops, J., Gosens, I., Van De Meent, D., Dekkers, S., De Jong, H. W., Van Zijverden,
M., Sips, J.A.M A., Geersma, E. R. 2009. Nano-Silver- a review of available data and knowledge gaps
in human and environmental risk assessment. Nanotoxicology. Vol. 3 No. 2. Pp. 109-138
Wood, M.C., Hogstrand, C., Galvez, F., Munger, R.S. 1996. The physiology of waterborne silver toxicity
in freshwater rainbow trout (Oncorhynchus mykiss) 1. The effect of ionic Ag+. Aquatic Toxicology.
Vol. 35. Pp. 93-109
26
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
29
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
30
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
31
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
32
33