Establishment of an In Vitro Assay for Acute Phase Response to Nanomaterial Exposure Master Thesis by Amalie Bregendahl Støvring 01-‐12-‐2015 Internal Supervisor Cathy Mitchelmore External Supervisor Ulla B. Vogel Preface My master`s thesis in Molecular Biology and Medicinal Biology was constructed at The National Research Centre for the Working Environment (NRCWE). Professor Ulla Vogel (NRCWE) was my external supervisor and Associate Professor Cathy Mitchelmore (Department of Science, Systems and Models, Roskilde University) was my internal supervisor. I would like to thank all my colleagues at NRCWE for their collaboration and help. A special thanks to Ulla Vogel and Sarah Søs Poulsen for all their help and guidance and for showing great enthusiasm about my work. Another special thanks to Anne-‐Karin Jensen for her technical support in the laboratory, and to Stefan Bengtson for always being willing to help me with different problems. Also thanks to my supervisor from Roskilde University Cathy Mitchelmore. Copenhagen, December 2015 Amalie Bregendahl Støvring 1 List of Abbreviations ABCA1: ATP-‐binding cassette receptor 1 ABCG1: ATP-‐binding cassette receptor G1 ALICE: Air–liquid interface cell exposure system APP: Acute phase protein APR: Acute phase response ApoA-‐I: Apolipoprotein A-‐I BAL: Bronchoalveolar lavage BET: Brunauer-‐Emmet-‐Teller surface area analysis CB: Carbon black CE: Cholesteryl esters Ct: Threshold cycle cDNA: Complementary deoxyribonucleic acid CNT: Carbon nanotube CRP: C-‐reactive protein CVD: Cardiovascular disease DNase: Deoxyribonuclease ELISA: Enzyme-‐linked immunosorbent Assay FBS: Fetal bovine serum FRET: fluorescence resonance energy transfer GO: Graphene oxide HARN: High aspect ratio nanoparticle HDL: High density lipoprotein IL: Interleukin IDL: Intermediate-‐density lipoprotein LCAT: Lecithin-‐cholesterol acyltransferase. LDL: Low density lipoprotein LPS: Lipopolysaccharide LOX-‐1: Lectin-‐like oxidized LDL receptor-‐1 MCP-‐1: Monocyte Chemoattractant Protein-‐1 mRNA: Messenger ribonucleic acid MWCNT: Multi-‐walled carbon nanotube NM: Nanomaterial NP: Nanoparticles PBS: Phosphate-‐buffered saline qRT-‐PCR: Quantitative reverse transcriptase polymerase chain reaction RNA: Ribonucleic acid rRNA:Ribosomal ribonucleic acid SAA: Serum amyloid A SEM: Scanning electronic microscopy SD: Standard deviation SR: Scavenger receptor SWCNT: Single-‐walled carbon nanotube TNF-‐𝛼: Tumour necrosis factor-‐α VLDL: Very low-‐density lipoprotein 2 Abstract Inhalation of nanomaterials (NMs) has been reported to induce a pulmonary acute phase response, seen by enhanced mRNA expression levels of the acute phase protein serum amyloid a (Saa) in the lungs. SAA are considered a risk marker for development of atherosclerosis, but its pulmonary cellular origin is still not understood. NMs can have many different toxicological effects due to their diverse physical and chemical properties. It is therefore necessary for risk assessment of all NMs, which may potentially come in contact with humans. Risk assessment of NMs in vivo is challenging in terms of time, as well as financial and ethical resources. The aim of this thesis is to establish an in vitro assay for quantifying SAA1, Saa3 and Mcp-‐1 response to NMs exposure in a human alveolar basal epithelial cell line (A549) and a murine alveolar macrophage cell line (J774A.1). This was done by exposing cells to three carbon based NMs different in structure (Mitsui, Printex-‐90, and graphene oxide) and one metal oxide (UV-‐TiO2) in concentrations 50, 100, and 200 µg/ml. Cells were incubated for 24 hours after exposure. SAA1, Saa3, and Mcp-‐1 mRNA expression levels were assessed with qRT-‐PCR in both cell lines. Protein levels were analysed with ELISA for only SAA3 in J774A.1 cells. The measured SAA1, Saa3, and Mcp-‐1 mRNA fold change values were compared to previous published in vivo studies. The viability and proliferation showed a statistically significant decrease in J774A.1 cells exposed to Mitsui, Printex-‐90 and graphene oxide in a dose-‐dependent manner. No statistically significant cytotoxic effect was found in A549 cells after exposure to NMs. In general, SAA1, Saa3, and Mcp-‐1 mRNA expression levels were low when determined by qRT-‐PCR analysis. SAA3 protein levels, in J774A.1 cells, were too low to be detected by ELISA analysis. The Saa3 mRNA fold change values in J774A.1 cells exposed to UV-‐TiO2 and Mitsui were statistically significantly increased compared to the unexposed samples. A549 cells showed no statistically significant effect on SAA1 mRNA fold change values after exposure to all four NMs. Furthermore, the measured SAA1, Saa3, and Mcp-‐1 mRNA fold change values were approximately 240 times lower when compared to previous published in vivo studies. In conclusion, existing in vitro assays cannot be used as substitutes for in vivo studies in risk assessment of NMs based on biomarkers SAA1, Saa3, and Mcp-‐1. 3 Resume Inhalation af nanomaterialer er blevet associeret med induktionen af et pulmonalt akutfaserespons, observeret ved forhøjede mRNA ekspressionsniveauer af akutfaseproteinet serum amyloid a (Saa) i lungerne. SAA anses for at være en risikomarkør for udviklingen af arteriosklerose, men dens pulmonale cellulære origin er stadig uvist. Nanomaterialer menes at have mange forskellige toksiske effekter grundet deres forskellige fysiske og kemiske egenskaber. Det er derfor nødvendigt med risikovurdering af alle nanomaterialer, der potentielt kan komme i kontakt med mennesker. Risikovurdering af nanomaterialer in vivo er beslægtet med mange etiske, finansielle og tidsmæssige begrænsninger. Formålet med dette speciale er at etablere et in vitro assay, der kvantificerer forskellige nanomaterialer i forhold til deres effekt på SAA1, Saa3 og Mcp-‐1 niveau undersøgt i en human alveolær epitel cellelinje (A549) og en murin alveolær makrofag cellelinje (J774A.1). Dette blev undersøgt ved at eksponere cellerne for tre kulstof baseret nanomaterialer med forskellige strukturer (Mitsui, Printex-‐90 og graphene oxid) og et metal oxid (UV-‐TiO2), i følgende koncentrationer: 50, 100 og 200 µg/ml. Cellerne blev inkuberet i 24 timer efter eksponering. SAA1, Saa3 og Mcp-‐1 mRNA ekspressionsniveauer blev målt med qRT-‐PCR i både A549 og J774A.1 celler. SAA3 proteinkoncentrationer blev målt med ELISA kun i J774A.1 celler eksponeret for UV-‐TiO2. SAA1, Saa3 og Mcp-‐1 mRNA fold change værdier blev sammenlignet med publicerede videnskabelige in vivo studier. Procentdelen af levende og delende celler var statistisk signifikant lavere i J774A.1 celler eksponeret for Mitsui, Printex-‐90 og graphene oxid sammenlignet med kontrolværdierne. Ingen cytotokiske effekt blev observeret i A549 celler efter eksponering. Kun SAA1, Saa3 og Mcp-‐1 mRNA ekspressionsværdier kunne måles, SAA3 proteinkoncentrationer var for lave til at blive målt med ELISA. J774A.1 celler eksponeret for UV-‐TiO2 og Mitsui havde en statistisk signifikant stigning i Saa3 mRNA fold change værdier sammenlignet med kontrolværdierne. A549 celler, eksponeret for alle fire nanomaterialer, havde ingen statistisk signifikant stigning i SAA1 mRNA fold change værdierne sammenlignet med kontrolværdierne. Yderligere var mine mRNA fold change værdier cirka 240 gange lavere sammenlignet med tidligere publicerede videnskabelige in vivo studier. 4 Baseret på biomarkøerne SAA1, Saa3 og Mcp-‐1, er det på nuværende tidspunkt ikke muligt at erstatte in vivo med in vitro assay i risikovurdering af nanomaterialer. 5 Table of Contents Introduction ................................................................................................................................................... 8 Aim of the Study ....................................................................................................................................................... 9 Hypothesis .............................................................................................................................................................. 10 Background ................................................................................................................................................. 11 Inhalation of NMs .................................................................................................................................................. 11 Clearance from the Lung ...................................................................................................................................... 12 Inflammation and Acute Phase Response ......................................................................................................... 13 SAA and Atherosclerosis ....................................................................................................................................... 14 Principles of the Methods used ............................................................................................................... 17 Cell Culture ............................................................................................................................................................. 17 RNA Purification .................................................................................................................................................... 17 qRT-‐PCR ................................................................................................................................................................... 19 Standard Curve ....................................................................................................................................................................... 20 Sandwich Enzyme-‐linked Immunosorbent Assay (ELISA) ............................................................................... 21 Standard Curve ....................................................................................................................................................................... 22 Cell Cycle Analysis .................................................................................................................................................. 23 Materials and Methods ............................................................................................................................. 25 Nanomaterial and LPS ........................................................................................................................................... 25 Dose Selection ........................................................................................................................................................................ 26 Mycoplasma Test ................................................................................................................................................... 27 Cell Cultures ............................................................................................................................................................ 28 Cell Types .................................................................................................................................................................................. 28 Culturing ................................................................................................................................................................................... 29 Cell Exposures ........................................................................................................................................................ 30 Setup .......................................................................................................................................................................................... 30 Exposure ................................................................................................................................................................................... 31 Harvest ...................................................................................................................................................................................... 31 Time Experiment .................................................................................................................................................... 32 Priming with LPS .................................................................................................................................................... 32 ELISA ........................................................................................................................................................................ 33 RNA purification .................................................................................................................................................... 35 cDNA Synthesis ...................................................................................................................................................... 36 qRT-‐PCR ................................................................................................................................................................... 37 Cell cycle analysis .................................................................................................................................................. 38 Results .......................................................................................................................................................... 39 Cell culture .............................................................................................................................................................. 39 Experiment 1 (Pilot Experiment) ......................................................................................................................... 39 Proliferation and Viability .................................................................................................................................... 40 Viability ...................................................................................................................................................................................... 40 6 Proliferation ............................................................................................................................................................................. 41 qRT-‐PCR ................................................................................................................................................................... 42 A549 ........................................................................................................................................................................................... 42 J774A.1 ...................................................................................................................................................................................... 44 Conclusion (Experiment 1) .................................................................................................................................................. 46 ELISA ........................................................................................................................................................................ 47 Priming with LPS .................................................................................................................................................... 49 Conclusion (ELISA) ................................................................................................................................................................. 50 Experiment 2 .......................................................................................................................................................... 50 Time Experiment .................................................................................................................................................................... 50 Viability and Proliferation ................................................................................................................................................... 52 qRT-‐PCR ..................................................................................................................................................................................... 54 Mcp-‐1 ......................................................................................................................................................................................... 56 Cell Cycle Analysis .................................................................................................................................................. 58 Discussion .................................................................................................................................................... 60 LPS-‐Induced mRNA Expression Levels ................................................................................................................ 60 NM-‐induced mRNA Expression Levels ............................................................................................................... 61 NM-‐induced Cytotoxicity ..................................................................................................................................... 63 Study Design ........................................................................................................................................................... 64 Choice of Cell Line ................................................................................................................................................................. 64 Dose Selection and Exposure ............................................................................................................................................. 65 Culturing ................................................................................................................................................................................... 66 Conclusion ............................................................................................................................................................... 67 Perspective .................................................................................................................................................. 68 References ................................................................................................................................................... 69 Appendix ...................................................................................................................................................... 82 7 Introduction Cardiovascular diseases (CVD) are the number one cause of deaths globally, causing an estimated 31 percent of deaths in 2012 [1]. Epidemiological studies have shown a link between exposure to particulate air pollution and occurrence of CVD [2,3,4]. Nanotechnology has resulted in the development of new, promising industrial applications, including biomedicine, electronics, cosmetics, and rubber products. Despite the promising applications, nanomaterials (NMs) may also induce toxicological effects [5]. The increase in the industrial use of NMs results in an increased potential for human exposure, especially in occupational settings [6]. Defined as materials with at least one dimension below 100 nm, NMs are more biologically reactive than larger particles due to their small size and corresponding large surface area. Their small material size enables them to deposit in the alveolar region of the lungs [7,8]. Atherosclerosis is the most common underlying process of CVD events, characterized by plaque formation in larger arteries. Disruption of the plaque can reduce blood flow to the target organ, which in severe cases can result in heart attack [9,10]. Acute phase response (APR) is believed to be a predictor of atherosclerosis, as the acute phase protein (APP) serum amyloid A (SAA) has been classified as a risk marker [11,12,13]. The origin of APR is in general viewed as hepatic, but in vivo studies have shown a pulmonary origin after exposure to NMs [14,15]. NM-‐induced pulmonary APR has been observed to be associated with increasing concentrations of SAA in a dose-‐dependent manner. Despite the reported elevated concentrations of SAA in the lungs, the cellular origin is still not well understood [14,15,16]. The high production volume of different NMs has created a burden for toxicological testing. Because of their different physiochemical properties, NMs can cause many different toxic responses. Risk assessment of NMs in vivo is time consuming and associated with major financial and ethical limitations [17]. The ethical limitation can be summarized in guidelines called the three R’s. They are defined as: replacement, reduction, and refinement [18]. The three R’s ensure that in vivo experiments are only used when necessary, that the number of animals needed is held to a minimum, and that the suffering of the animals is minimized [19]. The different limitations of in vivo experiments represent an urgent need for an in vitro screening assay, which can predict and assess the toxicity of NMs. 8 Aim of the Study Ø To measure the SAA1, Saa3, and Mcp-‐1 mRNA expressions levels in a murine alveolar macrophage cell line (J774A.1) and a human alveolar epithelial cell line (A549) after exposure to UV-‐TiO2, Mitsui, Printex-‐90, and graphene oxide (GO). Ø To measure the SAA1 and SAA3 protein concentrations in A549 and J774A.1 cells after exposure. Ø To determine whether the magnitude of the SAA1, Saa3, and Mcp-‐1 mRNA levels correlates with the in vivo response, for establishment of an in vitro model that ranks NMs according to their effect on SAA1, Saa3, Mcp-‐1 mRNA. 9 Hypothesis Ø A549 and J774A.1 cells exposed to different NMs will have increased expression of SAA1, Saa3 and Mcp-‐1 mRNA levels and increased SAA1 and SAA3 protein levels. Ø Establishment of an assay, that ranks the NMs according to their effect on SAA1, Saa3 and Mcp-‐1 mRNA expression levels, can be used to predict and assess in vivo. 10 Background Inhalation of NMs The development of new materials based on nanotechnology has resulted in a greater risk of human exposure, primarily in occupational settings and through inhalation. The material’s surface area increases exponentially when the size decreases (Figure 1) and the larger surface area of NMs may increase their toxicological effect [6]. Figure 1. The surface area increased with decreasing in material size (nm) [7]. Inhaled particles deposit in different parts of the respiratory system, depending on their size. Larger materials deposit in the nasopharyngeal compartment, whereas materials with diameters less than 100 nm will mainly deposit in the alveolar region (Figure 2) [7, 20]. 11 Figure 2. Predicted size-‐dependent deposit of NMs in the respiratory system. Larger materials deposit in the upper airway, whereas smaller materials deposit deeper in the lungs [7]. Clearance from the Lung There are a number of defence mechanisms in the respiratory tract, which keep the mucosal surfaces free from foreign materials. In the upper airway, the mucociliary escalator is an effective defence system which is composed of mucus producing goblet cells and ciliated epithelium. Foreign materials get caught in the mucus and are moved towards the pharynx where they are either exhaled by coughing or ingested with mucus into the gastrointestinal tract [21,22]. The main deposit site of NMs is the alveolar region, which doesn’t contain mucociliated cells [23]. Materials caught in the mucociliary escalator are normally cleared within 24 hours after exposure, whereas the alveolar clearance has a half-‐life greater than 100 days [24]. In the alveoli, the clearance of NMs is primarily mediated by successful phagocytose by alveolar macrophages [8, 25]. The alveolar macrophages engulf the NMs by forming an intracellular vesicle, a phagosome, with the NMs inside. Some NMs have been shown to escape the vesicles and become free in the cytosol, where they can pierce through the nuclei membrane and cause genotoxicity [23,26]. Phagocytosis of NMs is a length-‐dependent process with an optimum size range of 1-‐3 µm. If the length of the NMs exceeds 1-‐3 µm, it can result in frustrated phagocytosis, which can lead to an inflammatory response. This has especially been observed after exposure to carbon nanotubes (CNTs) because of their high length-‐to-‐width ratio [27]. 12 A high number of NMs in the alveoli can cause impaired clearance and increase in pro-‐
inflammatory cytokine productions, leading to inflammation [26]. Because of inadequate phagocytose and slow macrophage-‐mediated clearance, NMs may interact with cells of the epithelium or translocate from the lungs [28,29]. Inflammation and Acute Phase Response Epidemiological studies have proposed a link between exposure to particulate air pollution and risk of CVD [30,31,32]. Furthermore, studies have reported a strong induction of a pulmonary APR after exposure to NMs with close to no hepatic APR in vivo [15,33,34]. Induction of a pulmonary APR has been shown to be associated with increasing Saa mRNA expression levels in the lungs in vivo [14,15,35,36]. After being inhaled and deposited in the lungs, the NMs create a local inflammation. The first stage of the inflammatory response is activation of macrophages. The macrophages will, upon encounter with NMs, begin to secrete pro-‐inflammatory cytokines and chemokines such as interleukin-‐6 (IL-‐6), interleukin-‐1 (IL-‐1), and tumour necrosis factor-‐α (TNF-‐α). IL-‐1 and TNF-‐α induce the expression of the chemokine Mcp-‐1 in different cells, which play a key role in recruiting monocytes to the site of inflammation [37,38]. IL-‐1, IL-‐6, and TNF-‐α promote vasodilation, activate endothelial cells, and increase vascular permeability and chemotactic factors. The pro-‐inflammatory cytokine IL-‐6 promotes the APR. The APR is defined as an up-‐ or downregulation of blood levels of APPs. APPs are grouped as either positive or negative APPs. During an APR, the positive APPs increase and the negative APPs decrease. The positive APPs are thought to play a role in opsonization and activation of the complement system [39]. Some positive APPs increase only 1.5-‐ to 10-‐fold, while others increase 10-‐ to 1000-‐fold [40]. The most sensitive positive APPs in humans are C-‐reactive protein (CRP) and SAA. SAA consists of several isotypes; human SAA is encoded by three different loci: SAA1, SAA2, and SAA3. SAA1 and SAA2 are expressed both hepatic and extra-‐hepatic. In humans, SAA3 is believed to be a pseudogene. In mice, Saa1 and Saa2 are expressed in the liver, whereas Saa3 is expressed in various tissues [15,41,42]. SAA is released into circulation in response to inflammation and acts to recruit cells to the site of inflammation. This recruitment has been observed in animal studies as increased neutrophil influx in bronchoalveolar lavage (BAL) fluid after inhalation of NMs [43,44]. 13 SAA and Atherosclerosis SAA and MCP-‐1 are both considered risk markers for the development of Atherosclerosis [11,33,45,46]. High concentrations of SAA can affect the cholesterol homeostasis through binding to high-‐density lipoprotein (HDL) [15,47]. MCP-‐1 exhibits powerful chemoattractant properties by recruiting monocytes and macrophages to the vessel wall [45]. Atherosclerosis is the most common underlying process which can result in CVD. Atherosclerosis is a disease where the artery wall thickens in response to accumulation of cholesterol, fatty material, and inflammatory cells. The accumulation results in plaque formation, which can reduce the blood flow through the artery (Figure 3a-‐b) [10]. Figure 3. Atherosclerosis. a) Normal artery, b) Plaque formation. The arrows indicate the blood flow through the artery [modified 48]. SAA promotes the development of Atherosclerosis by affecting the reverse cholesterol transport (RCT). Cholesterol is an insoluble molecule that is transported in circulation by binding to lipoproteins. Lipoproteins maintain homeostasis by removing excess cholesterol from the tissue to excretion by the liver [49]. Five classes of lipoproteins exist: chylomicrons, very low-‐density lipoprotein (VLDL), intermediate-‐density lipoprotein (IDL), low-‐density lipoprotein (LDL), and high-‐
density lipoprotein (HDL). The lipoproteins all contain a large complex of lipids and apolipoproteins which function as a ligand for cell membranes. Apoplipoprotein A-‐I (ApoA-‐I) is produced by the liver and interacts with phospholipids to form nascent HDL (Pre-‐β HDL) (Figure 4) [50]. SAA has apolipoprotein properties and replaces 95% of ApoA-‐I as the primary apolipoprotein binding to HDL under an APR [51]. One of the earliest events of atherosclerosis is accumulation of LDL inside the vessel wall. Exposure of oxidative waste products from vascular cells oxidizes the LDL particle (ox-‐LDL) inside the artery. The accumulation of ox-‐LDL promotes an inflammatory response [52,53]. The HDL 14 particle can inhibit the LDL oxidation by serum paraoxonase, which degrades oxidized phospholipids. Levels of serum paraoxonase are inversely correlated with SAA levels. SAA can inhibit the effect of serum paraoxonase resulting in increased concentrations of ox-‐LDL, which in turn enhances the pro-‐inflammatory response [53]. The endothelium functions as a selective permeable barrier for blood and tissues [52]. Changed permeability of the endothelium, allows monocytes to travel inside the artery in response to inflammation. SAA has been reported to increase the MCP-‐1 production, resulting in an enhanced translocation of monocytes into the artery in vivo [54]. Inside the artery, the monocytes differentiate into macrophages and begin to engulf ox-‐LDL. The binding and uptake of ox-‐LDL is especially mediated by a member of the scavenger receptor (SR) family: Lectin-‐like oxidized LDL receptor-‐1 (LOX-‐1), expressed on the macrophages cell membrane [55,56]. The binding and uptake of ox-‐LDL by macrophages results in foam cell formation. SAA has been observed to promote the foam cell formation primarily be upregulating the expression of LOX-‐1 in vitro [57]. The foam cells begin to express the ATP-‐binding cassette receptor G1 (ABCG1) and ATP-‐binding cassette receptor 1 (ABCA1) (Figure 4) [10]. The receptor ABCA1 unloads cholesterol to Pre-‐β HDL particles and ABCG1 unloads cholesterol to mature the HDL particle (Figure 4) [57,58]. Under normal conditions, the HDL particle will reduce the foam cell formation by RCT. ApoA-‐I is a co-‐factor for lecithin-‐cholesterol acyltransferase (LCAT) activity, which esterifies free cholesterol unloaded from the foam cells. The free cholesterol on the surface of β-‐HDL particle is converted to cholesteryl esters (CE) by LCAT, which matures the 𝛽 -‐HDL particle. The esterifying allows packages of CE into the interior of the lipoproteins, thereby enhancing its carrier capacity [59,60]. When binding to HDL, SAA depresses LCAT activity resulting in accumulation of free cholesterol and insufficient cholesterol transport [61]. Under normal conditions, The HDL particle, rich in cholesterol, goes into circulation for delivery of CE to the liver for excretion. The SR-‐BI receptor on hepatocytes mediates the CE uptake for excretion. The lipid-‐poor HDL particle can return to the periphery and begin the cycle again (Figure 4). 15 Figure 4. Reverse cholesterol transport: Apo-‐I (ApoA-‐I), synthesized by the intestine, associates with β-‐HDL and come into circulation. HDL travels to the artery wall were it comes in contact with foam cells. The foam cells express ATP-‐
cassette binding transporters ABCA1 and ABCG1 that mediate the uptake of cholesterol from macrophages to HDL. Cholesterol is esterified to CE. CE is removed from the HDL particle by SR-‐BI expressed on hepatocytes. SR-‐BI delivers cholesterol to the liver for excretion [modified from 62]. SAA is a high affinity ligand for SR-‐BI expressed on hepatocytes [46,57]. SAA has been shown to inhibit the binding of HDL to SR-‐BI in vivo, resulting in a decreased delivery of CE for excretion [63]. If the RCT is not functioning properly it can result in an accumulation of foam cells inside the artery resulting in plaque formation. Rupture of the plaque can trigger thrombus formation, which can impede the blood flow (Figure 3b) [10]. 16 Principles of the Methods used Cell Culture Cells can be obtained from normal or diseased tissue. Cells that are grown directly from healthy tissue are called primary cells. Primary cells are heterogeneous and more representative of the tissue from which they are derived. The limitations using primary cells are their slow growth rate and limited lifespan. Whereas cells obtained from diseased tissue are homogenous and can divide indefinitely. When cells are initially seeded they enter the lag phase, where cells recover from the sub culturing and adjust to the new environment. When the cells begin double again they are in the log or exponential phase of growth. Sub culturing is preferred to be done when cells are in the log phase, which reduces the lag phase. In the stationary phase the growth reaches a plateau, leading the cells into the death phase [64] (Figure 5). Figure 5. Standard cell growths curve. When cells are seeded they enter a lag phase where no grow occur. After the lag phase the cells go into the exponential phase. They reach a stationary phase because of limitations in the environment, which results in decreased proliferation and viability [65]. RNA Purification RNA purification was performed using the AS2000 Maxwell 16 instrument (Promenga, Sweden). The Maxwell 16 cell reagent kit contains prefilled reagent cartridges (Figure 6a-‐b). The kit is designed to use the magnetic particles method, where RNA binds to silica-‐paramagnetic particles (MagneSil PMPs). The particles contain a paramagnetic core surrounded by a shell modified to bind nucleic acid with a high affinity. 17 Before loading on the machine, cells are treated with homogenization solution and lysis buffer to homogenize the sample and destroy the cell membrane, respectively. The samples are loaded into the wells, where RNA binds to the surface of the silica-‐paramagnetic particles. A magnetic rod is lowered into the samples, which creates a magnetic field. When the magnetic field is shut of the magnetic rods led go of the silica-‐paramagnetic particles. The particles are washed and incubated with deoxyribonuclease (DNase) solution to degrade all DNA contamination in the sample. The silica-‐paramagnetic particles go through several washing steps to remove impurities, resulting in concentrated and eluted RNA. The RNA is eluted in nuclease free water [66]. Well Well content number 1 RNA lysis buffer 2 MagneSil PMPs 3 RNA lysis Buffer 4 Yellow wash solution (DNase treatment) a) b
) 5 RNA Alcohol wash B 6 RNA Alcohol wash B 7 RNA Alcohol wash B 8 Empty Figure 6. Illustration of reagents used in the RNA purification kit. a) Cartridge containing 8 wells. b) Well content of the cartridge [67]. 18 qRT-‐PCR The real time quantitative reverse transcriptase polymerase chain reaction (qRT-‐PCR) is a technique used for gene expression analysis and the quantification of mRNA. The method has a high sensitive, specificity and gives fast result [68]. The first step is synthesis of complementary DNA (cDNA) from mRNA mediated by reverse transcriptase and a primer. Random hexamer was chosen as primer instead of oligo(dT). Random hexamer are oligonucleotides of a short random sequence, which covers all possible RNA regions. The reference gene, 18S ribosomal RNA (rRNA) does not contain a poly(A)tail and can therefore not be amplified with oligo(dT) [69]. The PCR products are synthesized from cDNA. The primers and probe anneal to the target sequence. The probe is labeled with a reporter dye at the 3` and a quencher molecule at the 5`. As long as the reporter dye and quencher molecule are close to each other very little florescent is emitted. This phenomenon is called Fluorescent resonance energy transfer (FRET), where the reporter dye is reduced by the presence of the quencher. The reporter dye has a higher energy of emission than the quencher. The energy is transferred from a higher to a lower level, when they are close to each other, resulting in the reporter dye being suppressed by the quencher [71]. Figure 7. Principe’s of qRT-‐PCR. A PCR cycle contains three steps: denature, annealing and extension. Under denature the strands separates (step 1). Primer and probe anneal to the target sequence (step 2). The DNA polymerase extends the primer and thereby separating the reporter dye and quencher from each other. The fluorescence emitted from the reporter dye can now be detected [70]. 19 In the first step the strands are separated from each other upon heating, which allows for the primer and probe to anneal to the DNA strand. The AmpliTaq GOLD DNA polymerase extends the primer and the 5`nuclease activity of the polymerase cleaves the probe and thereby separating the reporter dye and quencher (Figure 7). FRET cannot occur when the reporter dye and quencher are separated, resulting in an increase in fluorescence. If the florescence exceeds a certain threshold it is detected by the Viia-‐7-‐machine [71]. The increase in fluorescence is proportional with the increase in amplicon concentration. The signal for each cycle results in an amplification curve (Figure 8). The baseline of the amplification curves is the signal level, where there is little change in fluorescent signal. For 18S rRNA is the baseline normally cycle 3-‐7. The baseline is set for each qRT-‐PCR run to remove the background. The threshold is the level of signal reflecting a significant increase over the calculated baseline signal. The threshold cycle (Ct) is the cycle number at which the fluorescent signal crosses the threshold. The Ct-‐values increases with decreasing amounts of template [71]. Figure 8. Example of an amplification curve. The curve has indication of threshold, baseline and Ct-‐values [71]. Standard Curve Errors in RNA purification, cDNA synthesis, PCR procedure and primer transcription efficiency may occur during analysis. Therefore qRT-‐PCR data must be normalized using a reference gene to remove technical variation. The reference gene 18S rRNA was chosen because of its expression level being very stable and unaffected by experimental factors. Furthermore constitutes 18S rRNA 80-‐90% of the total RNA amount in cells [72]. Normalization of data is done by subtracting the Ct-‐ 20 value of the reference gene (CtRef) from the Ct value of the target gene (CtTarget); ∆Ct =CtTarget –CtRef. The relative mRNA expression level is then calculated by 2-‐∆Ct [71,83]. The use of this method presupposes that the difference between the amplification values of the target gene and the reference gene (∆Ct) are close to equal, which is assessed by constructing a standard curve (Figure 9). The standard curve was made by a 2 x fold serial dilution of a template with a known concentration. The dilution was run on a 384-‐well micro-‐Amp optical plate. Every dilution was set in triplicates. A standard deviation of 15 % was accepted for each set of triplicates. Three controls were used: a sample with no reverse transcriptase (NRT), no template control (NTC), and a plate control. The plate control was a sample with a known Ct-‐value used to address plate differences. The PCR reaction is quantitative if the slope is close -‐3.32, which is equivalent to 100 % efficiency. The efficiency is determined by E=10(-‐1/slope). The standard curve is accepted if the slope values are between -‐3.58 and -‐3.10 (Figure 9). My standard curves for SAA1, Saa3 and Mcp-‐1 were shown to be quantitative over a range of 32-‐, 64-‐ or 128-‐ fold dilution. 35,000 30,000 y = -‐3,3344x + 26,718 R² = 0,98825 25,000 Ct 20,000 15,000 y = 0,0641x + 14,207 R² = 0,03726 VIC 10,000 5,000 -‐2 -‐1,8 -‐1,6 -‐1,4 -‐1,2 -‐1 -‐0,8 -‐0,6 -‐0,4 0,000 -‐0,2 0 FAM y = -‐3,3985x + 12,51 R² = 0,99936 0,2 0,4 Delta Ct 0,6 Log cDNA Figure 9. Example of an accepted standard curve. The standard curve was made by a serial dilution of cDNA using Saa3 (FAM) and 18S (VIC). Sandwich Enzyme-‐linked Immunosorbent Assay (ELISA) I used mouse SAA3 specific sandwich Enzyme-‐Linked Immunosorbent Assay (ELISA) in my experiments. All the wells in the microplate were pre-‐coated with rabbit anti-‐mouse SAA3 antibody. The samples are added to the microplate with the pre-‐coated SAA3 antibody. Present 21 SAA3 antigens in the samples bind to the SAA3 antibodies. The wells are washed to get rid of unbound materials. A biotinylated anti-‐mouse SAA3 antibody is added to the wells, which binds to the captured mouse SAA3. The wells are washed. The enzyme horseradish peroxidase is added to the wells, which binds to the biotinylated antibodies. The wells are washed to remove unbound enzyme. The visualizing reagent 3,3`5,5`-‐tetramethylbenzidine is added causing the solutions to take on a blue color, which intensity corresponds to the amount of SAA3 protein in wells (Figure 10). A stop solution containing HCL is added, which converts the blue color into yellow. The enzyme activity is measured by a spectrophotometer at absorbance 450nm [73,74]. Figure 10. Principe`s of the sandwich ELISA method. Wells are pre-‐coated with SAA3 antibody. Present SAA3 antigen in the samples binds to the SAA3 antibody. The wells are washed. A biotinylated anti-‐mouse SAA3 antibody is added, which binds the captured mouse SAA3. The wells are washed. Horseradish is added, which binds the biotinylated antibodies. The wells are washed. 3,3`5,5`-‐tetramethylbenzidine is added to the wells, which convert the enzyme into a blue color. The color of the wells is increasing in intensity corresponding to increasing amounts of captured SAA3 protein. Stop solution is added, which converts the blue color into yellow and the absorbance can be read at 450 nm [Modified from 75] Standard Curve A standard curve is made by a serial 2x fold dilution of SAA3 standards in assay buffer. The SAA3 standards consist of purified recombinant GST-‐tagged mouse SAA3. The concentration of the SAA3 protein (µg/ml) is plotted against the mean absorbance (OD450). The concentration of the positive control must be in the linear section of the standard curve to be valid. The standard curve is used to determine the SAA3 protein concentration (µg/ml) in each sample (Figure 11). 22 OD450 2 1 0 0 1 2 3 4 5 6 Mouse SAA3 (μg/ml) Figure 11: Standard curve made by a serial dilution of a reconstructed SAA3 standards. Cell Cycle Analysis The cell cycle is a complex process involved in growth and proliferation of cells. The DNA content of the cells differs throughout the cell cycle. Cells have 23 pairs of chromosomes in the G1/G0 phase, whereas they in the S phase have varies amounts of DNA. In the G2 /M phase, the cells are containing duplicated pairs of chromosomes (Figure 12) [76]. Figure 12: The different stages of cell cycle and the distribution of DNA [76]. The NucleoCounter (NC-‐250) measures the DNA content of cells. The cells are fluorescently stained with 365 nm LED and DAPI. DAPI binds strongly to A-‐T rich regions of the DNA. The 23 fluorescence intensity of stained cells will therefore correlate with the amount of DNA. The fluorescence intensity of the DNA content in G2/M phase will be twice as high as the DNA content in G0/G1 phase. The result is given as a histogram, which gives the percentage of cells in the different phases of the cell cycle (Figure 13) [76]. Figure 13: Histrogram plot of cell cycle analysis. The plot shows that 40 % of the cells are in G0/G1 phase (M1), 41 % are in S-‐phase (M2) and 17 % are in G2 phase (M3) [76]. 24 Materials and Methods Nanomaterial and LPS Four different NMs were used for exposure experiments: the Carbon black (CB) nanoparticle (NP) Printex-‐90, the multi-‐walled carbon nanotube (MWCNT) Mitsui, UV Titanium dioxide (UV-‐TiO2) and GO. Their physical and chemical characteristics are listed in Table 1. Table 1: Physical and chemical characteristics of the NMs [35, 36, 43, 77, 78, 79]. Name NM Manufacturer/ Distributor Length (µm) Diameter Surface (nm) area, BET (m2/g) Chemical composition Printex-‐
90 Carbon black Evonic(Degusa), Frankfurt,Germany -‐-‐-‐ 14 295-‐
338 99% C 0.8% N 0.01% H Mitsui MWCNT Mitsui/Hadoga/Evo
nik, Tokyo, Japa 3-‐5 74 (29-‐173) 26 UV-‐TiO2 L181 TiO2 (rutile) Kemira, Pori, Finland -‐-‐-‐-‐ 17c 70-‐
107.7 GO Graphene Graphenea, San Sebastian, Spain 2-‐3 -‐-‐-‐-‐ -‐-‐-‐ 0.3% Fe 0.4% Na 470 ppm S 20 ppm Cl 0.60%Na2O, 12.01% SiO2, 4.58% Al2O3, 1.17 % ZrO2 49-‐56% C 0-‐1% H 0-‐1% N 41-‐50% O 0-‐2% S Ø Carbon black (CB) is a carbonaceous core particle that consists of less than 1% organic and inorganic impurities (Table 1) [43]. It has a characteristic grape-‐like structure of aggregates that clusters into large sized agglomerates, which can exceed 100 nm in diameter (Figure 14a) [80]. Ø CNTs can be grouped into either single-‐walled carbon nanotube (SWCNT) or MWCNT. SWCNT is nanosized tubes or fibers composed of a single rolled up layer of graphene. Whereas MWCNT are composed of multiple layers of graphene rolled into each other (Figure 14b). The SWCNT does not naturally exist as separate tubes, but tend to aggregate into fibers because of strong van der Wall forces between the molecules. The van der Wall forces between MWCNT are weaker than between SWCNT [78]. 25 Ø TiO2 is a white odorless metal oxide, which both exits as fine (<1µm) and nanosized (<0.1µm) [81]. TiO2 occur in two tetragonal crystalline structures (Figure 14c): anatase and rutile, with anatase being the most reactive [82]. Ø Graphene is constructed from single-‐atom two-‐dimensional sheets of hexagonally arranged carbon atoms [80]. GO are graphene layers containing functional oxygen groups (Figure 14d). a
) b) d
c
) (SEM) images of the four NMs: a) Printex-‐90, b) Mitsui, c) TiO , and d) GO ) 14: Scanning electronic microscopy Figure 2
[36,43,77,90]. Dose Selection The dose selection of the NMs was based on previous studies [81,84,85]. The doses: 50, 100, and 200µg/ml correspond to a very high, high, and medium dose. Table 2 compares the in vitro doses used in my experiment with the in vivo doses. The In vivo doses: 162, 54, and 18µg/animal are a high, medium, and low, corresponding to 1, 3, and 9 days of exposure (8 hours/day) assuming a 33 % deposition rate at the Danish occupational exposure limit of 3.5 mg/m3 (Printex-‐90) [36]. The average lung of a female mouse (C57BL/6, 20g) weighs 274 mg with an average surface area on 82 cm2. Using surface area of exposure as a parameter the in vivo doses correspond to 1.98, 0.66, and 0.22 µg/cm2. The cells were exposed to 3 ml media/NMs suspension in 6-‐well culture plates with a surface of 9.5 cm2. The in vitro concentrations correspond to 63.16, 26.31, and 15.79 µg/cm2 (Table 2). 26 Table 2. Comparison of In vivo and In vitro doses [Modified from 36] In vivo exposure dose µg/animal 162 54 18 mg/kg 8.1 2.7 0.9 (Assuming an average mouse weighs 20g) In vitro exposure dose µg/ml 200 100 50 * mg/kg NR
NR NR -‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐ mg/kg 591 197 65.7 mouse lung (Assuming an average lung weighs 274 mg) mg/kg µg/cm2 1.98 (lung surface 82 cm2) *NR=Not relevant. µg/cm2 (6-‐
well petri dish 9.5 cm2, 3 ml) 0.66 0.22 NR NR NR -‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐ 63.16 26.31 15.79 Before cell culture exposure, 8-‐12 mg of NMs were dissolved in 4-‐6 ml cell culture media to obtain a stock concentration of 2 mg/ml. GO was purchased as suspended in water. GO concentration was 4 mg/ml. 2 ml of GO was added to 2 ml of cell culture media. All suspensions were homogenized using a sonicator (Branson, Digital Sonifier). The suspension of NM and culture media were placed on ice and sonicated for 16 minutes. The size distribution of the NM suspension was assessed by Zetasizer-‐Nano DLS machine to evaluate the quality of the homogenization. The positive control, LPS, was phenol extracted from E. coli serotype O55:B5 (Sigma-‐Aldrich, L2880). The dose selection of LPS was based on previous studies [86,87,88,89]. The LPS solution was not sonicated to avoid contamination of other experiments. Mycoplasma Test Before the beginning of experiments, A549 and J774A.1 cells were tested for contamination of mycoplasma bacteria. This was tested with MycoAlertTM mycoplasma detection kit (LONZA, LT07-‐
118). The test exploits the activity of Mycoplasma enzymes, which are not present in eukaryote cells. The enzyme reacts with the MycoAlert substrate by catalyzing the conversion of ADP to ATP. ATP is then transferred into a light signal by the MycoAlert substrate. The samples are run on a Luminometer (Packard Lumicount BL10000), which detects difference in ATP levels before and after addition of the MycoAlert substrate. The result of the test was negative (data not shown). 27 Reagents Preparation of MycoAlert reagents was done by adding 600µL of assay buffer to the MycoAlert substrate and reagent (Table 3). Table 3. Reagents for Mycoplasma analysis. Reagents MycoAlertTM Reagent MycoAlertTM Assay Buffer MycoAlertTM Substrate LOT number (LT27-‐217) (LT27-‐218) (T27-‐221) Steps in Mycoplasma Detection Test 1. Cells were spun down at 200 g for 5 minutes. 2. 100 µL of supernatant was transferred to a cuvette. 3. 100 µL of reagent, which lyse cells, was then added to the cuvette and incubated at room temperature in 5 minutes. 4. The cuvette was run on the Luminometer, which gave a measured value (A). 5. 100 µL of substrate was then added to the cuvette and incubated 10 minutes at room temperature. 6. The cuvette was run on the Luminometer, which gave a measured value (B). 7. The ratio between A and B (B/A) should be lower than 0.9 for a negative test. Cell Cultures Cell Types Two cell types were used in the experiments, J774A.1 (ATCC, TIB-‐67) macrophages obtained from reticulum cell sarcoma from female mice (stain BALB/cN) (Figure 15a) and human adenocarcinoma alveolar basal epithelial type II cell line A549 (ATCC, CCL-‐185) (Figure 15b). In humans are epithelial type II cells responsible for diffusion of water and electrolyte over the alveoli of the lungs. 28 a) b) Figure15. Pictures of the J774A.1 cells (a) and A549 cells (b). Both pictures w ere taken with 10 x optic zoom. Culturing A549 and J774A.1 cells were seeded at 6*105 cells in culture flasks (Nunc, Denmark) with surface areas of 150 cm2 (T150). To the culture flask was added 30 ml of cell media (Table 4). J774A.1 cells were cultured in Dulbecco`s Modified Eagle culture medium (DMEM) (ATCC, 30-‐2002™) and A549 cells were cultured in F12 nutrient mix (HAM (1x)) cell culture media (Table 4) (Life technologies, 11765-‐054). Cells were grown in a CO2 incubator of 37°C, 5 % CO2 and 95% humidity. Culture media was changed twice a week to ensure proper growing conditions. Table 4. Preparation of cell culture media. Fetal Bovine Serum (FBS) Penicillin 10000 IU/ml/Streptomycin 10000 µg/ml (Pen/Strep) Per 500 ml of DMEM media (ml) 10 % (not heat inactivated) 1 % Per 500 ml of HAM (1x) media 10% (heat inactivated) 1% 29 The cells were subcultured when they had reached 80-‐90 % of confluence. Confluence of 80-‐90% for J774A.1 cells was obtained after 7 days and for A549 cells after 4 days. Steps in Subculturing 1. The culture media was removed from the flask and the cells were washed twice with 5ml of phosphate buffered saline (PBS). 2. The J774A.1 cells were loosened by scraping with a sterile cell scraper (Sigma-‐Aldrich, C5981-‐
100EA). 3. The A549 cells were loosened by trypsinization: 3.1. To the culture flask was added 3-‐5 ml of trypsin/EDTA (trypsin 0.05%-‐EDTA 0.02%) (In vitro, BI-‐03-‐053-‐1B) and incubated for 3-‐5 minutes. 3.2. The cells were loosened from the surface by placing a few horizontal slaps to the flask. 3.3. To the culture flask was added 10 ml of cell culture media, which inhibits the effect of the trypsin. 4. Cell count and viability was measured on the Nucleocounter 2000 (Chemometec). 5. In new T150 culture flasks were seeded 6*105 cells and placed in incubator. Cell Exposures Setup The culture flasks (Nunc, Denmark) were harvested according to section 3 (Steps in Subculturing). The cells were seeded in the concentration 1*105 cells in 24-‐wells plates (Nunc) with a surface area of 1.9 cm2 (Thermo Scientific, 142475). However, because of a too low RNA yield after purification the experiment was optimized and 5*105 cells were grown in 6-‐well culture plates (Nunc) with a surface area of 9.5 cm2 (Thermo Scientific, 140685) (Figure 16). The culture plates were incubated for 24 hours. 30 5
Figure 16. Example of sample setup in 6-‐well culture plate. J774A.1 cells were seeded in concentration 5*10 in 6-‐
well culture plates and exposed to three different concentrations: 0, 100, and 200 µg/ml of printex-‐90. Each concentration was set in duplicates. Exposure After incubation, the medium was removed from the wells and different concentrations of NMs were added (Table 5). LPS was used as the positive control. The treatment was done in duplicates and the same amount of sonicated medium was added to each well (Table 5). Cells were after exposure incubated for 24 hours. Table 5. Example of exposure design. Conc.Nano (µg/ml) 0 50 100 200 Conc. LPS (µg/ml) 5 Media (µl) Sonicated nano (µl) 2500 -‐-‐-‐ 2500 125 2500 250 2500 500 Media (µl) LPS (µl) 493.75 6.25 Sonicated media (µl) 500 375 250 -‐-‐-‐-‐ Sonicated medium 500 Total volume (µl) 3000 3000 3000 3000 Total volume (µl) 3000 Harvest The supernatant was collected from wells and stored at -‐ 80oC for SAA protein quantification with ELISA. The surfaces of the wells were either scraped or trypsinized (section 2-‐3, Steps in Subculturing) and 1000 µl of culture media was added to every well. The 1000 µl of media, containing the cells, were removed to a 1.5 ml Eppendorf tube. The cell count and viability were measured by the Nucleocounter 2000 (Chemotec). The Eppendorf tubes containing the cell suspension were used for RNA purification for further qRT-‐PCR analysis. 31 Time Experiment1 To confirm that the optimal incubation time after exposure was 24 hours [36,84,91,92] a time experiment was performed. A549 and J774A.1 cells were seeded at 5*105 in 6-‐well culture plates and grown for 24 hours according to section 1-‐3 (Steps in Subculturing). After 24 hours of incubation the cells were exposed to NMs in concentration: 100µg/ml and LPS 5 µg/ml, according to Table 3. The wells were harvested after 2, 4, 6, and 24 hours of incubation. All concentrations were set in duplicates. Priming with LPS Previous studies have reported that priming with LPS in samples exposed to NMs could induce a higher inflammatory response than the same concentration of LPS alone [93,94,95]. J774A.1 cells were seeded and harvested according to section 1-‐3 (steps in subculturing). Cells were after 24 hours of incubation exposed to UV-‐TiO2 and primed with 1µg/ml LPS (Table 6). Table 6. Setup design for priming experiment. Nanomaterial (µg/ml) Media (µl) LPS (µl) (1µg/ml) Sonicated media + Nano (µl) Sonicated media (µl) Total volume 0 50 100 2498.75 1.25 LPS (µg/ml) Media (µl) LPS (µl) 2498.75 1.25 500 2498.75 1.25 1 2498.75 1.25 125 250 -‐-‐-‐-‐-‐ -‐-‐-‐-‐ -‐-‐-‐ 375 250 500 3000 3000 3000 Sonicated media (µl) Total volume 3000 32 ELISA ELISA analysis (Merck Millipore, EZMSAA3-‐12K) was used for measuring of mouse SAA3 protein in supernatant collected from exposed samples. Reagents The kit was run on a 96-‐well microplate using the reagents listed in Table 7. Table 7 Reagents for ELISA analysis. Reagent 10 X HRP wash buffer concentrate Mouse SAA3 standard Substrate 10 x concentrate of 50mM Tris Buffered Saline containing Tween 20 Recombinant GST-‐tagged mouse SAA3, Lyophilized Mouse SAA3 Quality control 1 Mouse SAA3 at two different levels and 2 Assay Buffer 0.05M PBS, pH 7.4, containing 0.025M EDTA, 0.08%Sodium Azide, 1% BSA and 0.05% Triton X-‐100 Mouse SAA3 Detection Antibody Pre-‐titered Biotinylated Mouse SAA3 Antibody Enzyme Solution Streptavidin-‐Horseradish Peroxidase conjugate in buffer Substrate 3,3`5,5`-‐tetramethylbenzidine Stop solution 0.3 HCL LOT number EWB-‐HRP E8012-‐K E6012-‐K EABTR E1012 EHRP ESS-‐TMB ET-‐TMB Mouse SAA3 control 1 and 2 preparation To each of mouse SAA3 quality control was added 0.25mL of distilled water and mixed by inverting. Standard Curve A standard curve was made by serial dilutions of SAA3 standards. To each SAA3 standard 0.25 mL of distilled water was added (reconstituted standard) and 0.1 mL assay buffer was added to the six tubes. The serial dilutions were prepared by adding 0.1 mL of reconstituted standard to tube 1. The rest of the serial dilutions were made according to Table 8. Table 8. Serial dilution of SAA3. Tube # Tube 1 Volume of assay buffer To add 0.1 mL Tube 2 Tube 3 Tube 4 Tube 5 Tube 6 0.1 mL 0.1 mL 0.1 mL 0.1 mL 0.1 mL Volume of Standard To add 0.1 mL of reconstituted standard 0.1 mL of tube 1 0.1 mL of tube 2 0.1 mL of tube 3 0.1 mL of tube 4 0.1 mL of tube 5 Standard concentration (µg/mL) X/2 X/4 X/8 X/16 X/32 X/64 33 Assay Procedure 1. The wash buffer (10x concentrate of 50 mM tris Buffered Saline containing tween 20) was diluted 10 fold with distilled water. 2. 300 µL of the diluted wash buffer was added to the wells. 3. The wash buffer was decanted and 90 µl of Assay buffer (0,05M PBS, pH 7.4, containing 0.025M EDTA, 0.08% sodium azide, 1 % BSA and 0.05 % Triton X-‐100) was added to every well. 4. 100 µl of assay buffer was added to the two blank wells. The assay buffer was not decanted and 10µL of the SAA3 mouse standards, the quality controls and the samples were added in duplicates. 5. The plate was incubated at room temperature in two hours on an orbital microtiter plate shaker (400-‐500 rpm). 6. The content of the wells was removed, after incubation, and the wells were washed three times with 300 µl of wash buffer. The wash buffer was decanted after each wash to remove residual buffer. 7. 100 µl of detection antibody was added to the wells and incubated at room temperature for one hour on an orbital microtiter plate shaker (400-‐500 rpm). 8. The wells were washed, after incubation, three times with 300 µl of wash buffer and decanted after each wash. 9. 100 µl of enzyme solution was added to the wells. 10. The plate was placed on microtiter plate shaker (400-‐500 rpm) at room temperature. 11. After 30 minutes the residual fluid was removed and wells were washed six times with 300 µl of wash buffer. 12. 100 µl of substrate solution to the wells and the plate was placed on the microtiter plate shaker for 5-‐20 minutes. 13. A blue color was formed, after 5-‐20 minutes, in the wells of SAA3 standard with intensity proportional to increasing concentrations of SAA3. When the blue color was observed the plate was taken of the microtiter plate shaker. 14. 100 µl of stop solution was added to the wells and the plate was shaken by hand to ensure proper mixing of solution in all wells. 15. The absorbance was read at 450 nm and 590 nm in a plate reader. 34 RNA purification Maxwell 16 LEV simplyRNA purification cells kit (Promega, AS1270) was used for assessment of total RNA extraction. The samples were run on AS2000 Maxwell 16 instrument. Preparation of reagents The reagents for RNA purification are listed in Table 9. Table 9. Reagents for RNA purification. Reagent Homogenization solution Lysis buffer 1-‐Thioglycerol DNase -‐1 Per ml of homogenization solution was added 20 µL of 1-‐thioglycerol and stored on ice. To the lyophilized DNase were added 275 µl of nuclease-‐free water and 5 µl of blue dye. To the elution tubes were added 50 µL of nuclease free water. RNA Purification Steps 1. Eppendorf tubes, containing cells, were spun down in 5 minutes at 300g and the supernatant was removed. 2. The pellet was dissolved in 200 µl of homogenization solution. 3. 200 µl of lysis buffer were added to the samples and vortexed for 15 seconds. 4. 400 µl of lysate was added to well 1. 5. To well 4 (Figure 6a) was added 5µl of DNase I solution. 6. The machine was run for 60 minutes. 7. RNA concentrations (ng/µl) were determined using a NanoDrop 2000C Spectrometer (Thermo Scientific). 8. 1 µl of the purified RNA was placed under the arm and the optical density (OD), at 260 nm, was measured to determine the RNA concentration. 9. An OD260/OD280 close to 2.0 was general considered as being pure for RNA. 10. The samples were stored at -‐ 80°C until use in cDNA synthesis. 35 cDNA Synthesis The purified RNA was reverse transcribed into cDNA. To prepare cDNA synthesis a master mix was made with reverse transcription reagents kit (ThermoFisher, N8080234) (Table 10). Table 10. Reagent distribution for Master Mix Reagent 10X RT buffer Per sample (µl) LOT number 1.8 P14192 MgCl2 (25 mM) 3.9 S17272 dNTP mix (10 mM) 3.6 T03667 Random hexamers 0.9 T03166 0.4 T04144 0.4 T03635 0000117791 (50 mM) RNA`se inhibitor (20 units/µl) Reverse transcriptase (50 units/µl) Nuclease free water cDNA Synthesis Steps 1. 11 µl of the master mix was added to tubes corresponding to the total number of samples. 2. A total of 7 µl of RNA and Milli-‐Q water was added to obtain the concentration 100ng/10µl for every sample. 3. Two negative controls were made: NTC and NRT. 4. The samples were mixed by inverting and run in a PTC-‐100, programmed thermal controller (MJ research INC). The program runs three steps: 25oC in 10 minutes, 48oC in 30 minutes and 95oC in 5 minutes. 5. The samples were stored at -‐20°C. 36 qRT-‐PCR For assessment of SAA1, Saa3 and Mcp-‐1 mRNA levels qRT-‐PCR analysis was preformed. Table 11. Reagents for qRT-‐PCT analysis Reagents Sequence Manufacture , Lot number 2*PCR mix -‐-‐-‐-‐-‐-‐ LifeTechnologies, 4364338 Mili-‐Q water -‐-‐-‐-‐-‐-‐ -‐-‐-‐ Primer/probe: -‐-‐-‐ Human SAA1 primer/probe -‐-‐-‐-‐-‐-‐ LifeTechnologies, HS00761940-‐S1 mix Mouse Saa3 Reverse primer 5`TGC TCC ATG TCC CGT GAA C 3` TAG, Copenhagen, 140909 Mouse Saa3 Forward primer 5`GCC TGG GCT GCT AAA GTC AT 3` TAG, Copenhagen , 140909 Mouse Saa3 probe 5`-‐FAM-‐ TCT GAA CAG CCT CTC TAG, Copenhagen TGG CAT CGCT –TAMRA`3 Mouse Mcp-‐1 primer/probe -‐-‐-‐-‐-‐-‐-‐ Applied biosystems, mix Mm99999056_m1 Reference gene: -‐-‐-‐ Human 18S rRNA -‐-‐-‐-‐-‐-‐-‐ LifeTechnologies, 4333760T Mouse 18S rRNA -‐-‐-‐-‐-‐-‐-‐ Applied Biosystems, 4310893E-‐
1405055 Steps in qRT-‐PCR 1. A master mix was made by adding 41.9 µl of 2*PCR mix per sample and mixed with 33.1 µl of Mili-‐Q water per sample. 2. To every PCR tube, corresponding to the number of samples was transferred 75 µl of the master mix. 3. 10 µl of cDNA were added to the tubes. 4. The content of the PCR tubes were split into two portions of 36 µl, one for the target gene and one for the reference gene (Table 11). 5. 1.8 µl of the primer/probe mix was added to the tubes for the target gene. 6. 1.8 µl of 18S rRNA was added to the tubes for the reference gene. 7. The PCR analyses were run on a 384-‐well optical reaction plate (Thermofisher, 4309849) in triplicates (3 x 10µl). 8. For every run were used three controls: NCT, NRT and a plate control. 37 Cell cycle analysis Cell cycle analysis was performed by the use of the Nucleocounter NC-‐250 machine (Chemometec, 900-‐0251). The Nucleocounter NC-‐250 quantifies the DNA content of the cells to determine G0/G1, S and G2/M cell cycle phases. Preparation of Reagents The reagents used in cycle analysis are listed in Table 12. Table 12.Reagents for cell cycle analysis. Reagent PBS Lysis buffer Stabilization buffer DAPI Lot number -‐-‐-‐-‐ 910-‐0003 910-‐0002 910-‐3012 Prior to analysis, 20 µl of DAPI was added to 980 µl of Lysis buffer and mixed. Steps in Cell Cycle Analysis 1. An Eppendorf tube, containing 5*105-‐4*106 cells, was centrifuged down for 5 minutes at 400 g in room temperature. 2. The supernantant was discarded and the pellet was washed with PBS. 3. The cell pellet was resuspended in 250 μl and 10 μg/ml of DAPI. 4. The cell suspension was incubated at 37°C in 5 minutes. 5. 250 μl of stabilization buffer was added after incubation. 6. 30 μl of the cell suspension was loaded on a NC-‐slide and run on the Nucleocounter NC-‐250 machine (Chemoetec). Statistics All statistics were done with Minitab15. Comparisons of groups were done with a parametric one-‐
way ANOVA with a post hoc Dunnett`s test comparison. Not normally distributed data were log-‐
transformed to reach normality. 38 Results Cell culture Human alveolar A549 cells and mouse alveolar J774A.1 cells were in the beginning grown in 24-‐
well culture plates, but because of too low RNA yield, below 30ng/μl (data not shown), the experiment was scaled up and cells were grown in 6-‐well culture plates. Both cell lines were to begin with subcultured by trypsinization. J774A.1 cells adhere very firmly to the bottom of the flask and the trypsin was not effective enough to detach the cells. The cell count after trypsinization was too low to be detected by the Nucleocounter2000. Cell scraping was chosen as the alternative subculturing method for J774A.1 cells. Experiment 1 (Pilot Experiment) A pilot experiment was performed to see if there was any SAA1 or Saa3 mRNA response when A549 and J774A.1 cells were exposed to different concentrations of UV-‐TiO2 or LPS. 5*105 cells were seeded in 6-‐well culture plates and exposed to UV-‐TiO2 in five different concentrations: 12.5, 25, 50, 100, and 200µg/ml. For LPS, cells were exposed to the following concentrations: 0.1, 0.5, 1, 5, and 10µg/ml. After 24 hours of exposure, cells were harvest and the Nucleocounter 2000 measured cell count and viability in each sample. The experiment was repeated two times. 39 Proliferation and Viability Before qRT-‐PCR measurements, the viability and proliferation were respectively measured and calculated. The proliferation was calculated on the basis of the total cell count. Viability The percentage of living cells, after 24 hours of exposure to UV-‐TiO2, is illustrated in Figure 17-‐18 (a-‐b). 100 50 0 Viability (%) Viability (%) 100 a) 0 0.1 0.5 1 LPS (µg/ml) 5 10 50 0 b) 0 12.5 25 50 100 200 UV-‐TiO2 (µg/ml) Figure 17 (a-‐b). A549 cells showed no statistically significant decrease in viability when exposed to UV-‐TiO2 or LPS. (Red= experiment 1, blue= experiment 2). Viability of A549 cells stimulated with LPS (a): 0.1, 0.5, 1, 5, and 10 µg/ml or UV-‐TiO2 (b): 12.5, 25, 50, 100, and 200µg/ml. No statistically significant difference in viability in cells exposed to LPS or UV-‐TiO2, when compared to the unexposed control values. Every dot represents a mean of two samples. n=2. The viability of the A549 cells was close to 100 % for all the concentrations of both UV-‐TiO2 and LPS exposed cells (Figure 17(a-‐b)). No statistically significant difference in viability was observed, when compared to the unexposed samples. In contrast, the viability of both exposed and unexposed J774A.1 cells was under 50 % (Figure 18 (a-‐b)). Since there is no statistically significant difference between the exposed and unexposed samples, for UV-‐TiO2 or LPS, the low viability values are likely to be linked to difference in subculturing. J774A.1 cells are subcultured by use of a cell scraper, whereas A549 cells are subcultured by trypsinization. The risk of damaging cells is greater when using a cell scraper compared to trypsin. 40 100 Viability (%) Viability (%) 100 50 0 a) 50 0 0
0.1 0.5 1
5 10 0
12.5 25 50 100 200 b) LPS ( µg/ml) UV-‐TiO2 ( µg/ml) Figure 18 (a-‐b). Decrease in viability for J774A.1 cells exposed to LPS or UV-‐TiO2. (Red= experiment 1, blue= experiment 2). J774A.1 cells were stimulated with LPS (a): 0.1, 0.5, 1, 5, and 10 µg/ml or UV-‐TiO2 (b): 12.5, 25, 50, 100, and 200µg/ml. No statistically significant decrease in viability compared to unexposed samples. Every dot represents a mean of two samples. n=2. Proliferation Proliferation was calculated based on the measured cell count values. The control values were set to 100%. 200,00 Proliferaoon (%) Proliferaoon (%) 200,00 100,00 0,00 a) 100,00 0 0.1 0.5 1 LPS (µg/ml) 5 10 0,00 b) 0 12.5 25 50 100 200 UV-‐TiO2 (µg/ml) Figure 19. A549 cells showed no statistically significant decrease or increase in the proliferation when exposed to LPS or UV-‐TiO2. (Red= experiment 1, blue= experiment 2). A549 cells were exposed to LPS (a): 0, 0.1, 0.5, 1, 5, and 10µg/ml or UV-‐TiO2 (b): 0, 12.5, 25, 50, 100, and 200µg/ml. No statistically significant decrease or increase, compared to the unexposed samples, was observed. The control values were set to 100 %. Every dot represents a mean of two samples. n=2. No statistically significant effect was observed on the proliferation for both A549 and J774A.1 cells when exposed to UV-‐TiO2 or LPS (figure 19 (a-‐b) & figure 20 (a-‐b)). No increase or decrease in the proliferation was observed when compared to the unexposed control values. 41 200 Proliferaoon (%) Proliferaoon (%) 200 100 0 0 0.1 0.5 1 5 10 LPS (µg/ml) 100 0 b) 0
12.5 25 50 100 200 UV-‐TiO2(µg/ml) Figure 20 (a-‐b): J774A.1 cells showed no statistically significant decrease or increase in proliferation after exposure LPS or UV-‐TiO2. (Red= experiment 1, blue= experiment 2). The proliferation of J774A.1 cells exposed to LPS (a): 0, 0.1, 0.5, 1, 5 and 10µg/ml or UV-‐TiO2 (b): 0, 12.5, 25, 50, 100 and 200µg/ml. No statistically significant decrease or increase in proliferation after exposure compared to the unexposed control values. The control values were set to 100 %. Every dot represents a mean of two samples. n=2. qRT-‐PCR qRT-‐PCR measurements were preformed to evaluate the expression level of SAA1 and Saa3 mRNA in respectively J774A.1 and A549 cells. The results are given as a fold change in relative SAA1 or Saa3 mRNA expression level when compared to the unexposed control value. The fold change was calculated based on the normalized Ct-‐values. All data was normalized with 18S as reference gene. The experiment was repeated twice. A549 A549 cells showed a statistically significant increase in the relative SAA1 mRNA expression level when exposed to LPS (Figure 21). The highest concentration of LPS (10µg/ml) surprisingly didn’t show a statistically significant increase in the fold change, after exposure. A dose-‐response relationship was expected when exposed to LPS. The response levels for A549 cells exposed to LPS were low compared to J774A.1 cells (Figure 21 & Figure 23). 42 Fold Change (Relaove SAA1 mRNA) 20 * * * 10 * 0 0 2 4 6 8 10 12 LPS (µg/ml) Figure 21. A statistically significant correlation between SAA1 mRNA fold change and different LPS concentrations. A549 cells were exposed to LPS: 0.1, 0.5, 1, 5, and 10 µg/ml. All the concentrations, besides 10µg/ml, showed a statistically significant increase in fold change values when compared to the unexposed control value. Data were normalized to 18S reference gene. The unexposed control value was set to 1 on the y-‐axis. Every dot represents a mean of four samples. *=P≤0.05, **=P≤0.01, ***=P≤ 0.001. n=2. The error bars represent the SD. A549 cells showed no statistically significant relationship between the relative SAA1 mRNA expressions levels and different concentrations of UV-‐TiO2 (Figure 22). The fold change was close to zero, compared to the unexposed control value. This indicates that A549 cells didn’t response to UV-‐TiO2 on a SAA1 mRNA level. 43 Fold change (Relaove SAA1 mRNA) 20 10 0 0 50 100 150 200 UV-‐TiO2 Figure 22. No statistically significant correlation between the relative SAA1 mRNA expression levels when exposed to different concentrations of UV-‐TiO2. A549 cells were exposed to UV-‐TiO2: 12.5, 25, 50, 100, and 200µg/ml. No observed statistically significant correlation between different concentrations of UV-‐TiO2, compared to the unexposed control value. Data was normalized to 18S reference gene. The unexposed control value was set to 1 on the y-‐axis. Every dot represents a mean of four samples. n=2. The error bars represent the SD. J774A.1 J774A.1 cells were exposed to different concentration of LPS or UV-‐TiO2. A statistically significant upregulation of the relative Saa3 mRNA expression level in J774A.1 cells was observed. Figure 22 shows a correlation tendency between the different concentrations of LPS and the Saa3 mRNA fold change. In particular the concentrations 0.1 and 0.5µg/ml showed a very high increase on 35000-‐fold compared to the unexposed control value (Figure 23). All the fold change values were statistically significantly different compared to the unexposed sample. 44 Fold change (Relaove Saa3 mRNA) 40000 *** *** *** 20000 *** *** 0 0 2 4 6 LPS (µg/ml) 8 10 12 Figure 23. A statistically significant upregulation of Saa3 mRNA in J774A.1 cells after LPS exposure. J774A.1 cells were exposed to LPS in different concentrations: 0.1, 0.5, 1, 5, and 10µg/ml. A statically significant increase in the fold change values, when compared to the unexposed control, was observed. Every dot represents a mean of four samples. Data were normalized to 18S reference gene. The unexposed control value was set to 1 on the y-‐axis. *=P≤0.05, **=P≤0.01, ***=P≤ 0.001. n=2. Error bars represent the SD. The SD values were too small to be seen on the graph. The normalized Ct-‐values for J774A.1 cells exposed to UV-‐TiO2 were all high, indicating that the amount of Saa3 mRNA was very low. Although a low amount of Saa3 mRNA, a statistically significant tendency was observed (Figure 24). All concentrations had a statistically significant increase in the relative Saa3 mRNA level, when compared to the control value, besides the lowest concentration 12.5µg/ml. 45 Fold change (Relative Saa3 mRNA) 20 10 * * *
*
0 0 50 100 150 UV-‐TiO (µg/ml) 200 250 Figure 24. A statistically significant increase in the fold change values of relative Saa3 mRNA in J774A.1 after exposure to UV-‐TiO2. J774A.1 cells were exposed to five different concentrations of UV-‐TiO2: 12.5, 25, 50, 100, and 200µg/ml. A statistically significant tendency was observed for all concentrations besides 12.5µg/ml, compared to the unexposed control value. The unexposed control value was set to 1 on the y-‐axis. Every dot represents a mean of four samples. *=P≤0.05, **=P≤0.01, ***=P≤ 0.001. n=2. All values were normalized to 18S reference gene. Error bars represent the SD. Conclusion (Experiment 1) Because of a low relative SAA1 mRNA expression level in A549 cells, exposed to either UV-‐TiO2 or LPS, compared to the unexposed samples, only J774A.1 cells were used for ELISA analysis. Furthermore, J774A.1 cells were primed with LPS to investigate if it could induce a higher Saa3 mRNA expression or SAA3 concentration in J774A.1 cells exposed to UV-‐TiO2, than the same concentration of LPS alone. 46 ELISA The greatly induced Saa3 mRNA levels (Figure 25), as a consequence of exposure to LPS, indicate that a high response in protein level may also be observed. ELISA analyzes were therefore preformed to measure the level of SAA3 protein after exposure to UV-‐TiO2 or LPS. SAA3 (µg/ml) 5 2,5 *** *** *** *** *** 0 0 2 4 6 LPS (µg/ml) 8 10 12 Figure 25. The ELISA analysis showed a statistically significant high secretion of SAA3 proteins when stimulated with LPS. J774A.1 cells exposed to LPS: 0.1, 0.5, 1, 5, and10µg/ml, showed a statistically significant correlation between the amount of SAA3 (µg/ml) and increasing LPS concentrations. Every dot represents a mean of four samples. *=P≤0.05, **=P≤0.01, ***=P≤ 0.001. n=2. Error bars represent the SD. LPS treated samples showed a statistically significant correlation, which reaches a plateau after 5 µg/ml, between LPS concentrations and SAA3 (µg/ml) levels in supernatant from exposed J774A.1 cells. When analyzing the SAA3 protein level in samples exposed to UV-‐TiO2 only the three highest concentrations were chosen: 50, 100, and 200µg/ml. It was hypothesized that the highest response of SAA3 would be found in those samples. 47 SAA3(µg/ml) 5 2,5 0 0 50 100 150 200 250 UV-‐TiO2 (µg/ml) Figure 26. No SAA3 proteins detected by ELISA analysis. J774A.1 cells exposed to different concentrations of UV-‐TiO2: 50, 100, and 200µg/ml, didn’t show any detection of SAA3 protein. Every dot represents a mean of four samples. n=2. The absorbance values for the samples stimulated with UV-‐TiO2 all were lower than the blank values and therefore set to 0.0µg/ml SAA3 (Figure 26). In “reality” the samples may contain a very little amount of SAA3 and not precisely 0.0 µg/ml. 48 Priming with LPS The priming experiment was analyzed both on protein and mRNA level. For ELISA, J774A.1 cells exposed to UV-‐TiO2 in the two highest concentrations: 100 and 200µg/ml, were primed with 1µg/ml of LPS. qRT-‐PCR is considered a more sensitive testing method than ELISA, therefore some lower concentrations of UV-‐TiO2 were chosen as well: 12.5, 25, 50, 100, and 200µg/ml. SAA3 (µg/ml) 2 100 (UV-‐TiO2)+ 1 (LPS) 1 200 (UV-‐TIO2)+1(LPS) 1(LPS) 0 µg/ml Figure 27. Priming with LPS showed no statistically significant decrease or increase in the amount of SAA3 protein. J774A.1 cells exposed to UV-‐TiO2 in two different concentrations: 100 and 200 µg/ml and primed with 1µg/ml LPS. The values were compared to samples only treated with 1 µg/ml LPS. Every bar represents a mean of four samples. n=2. Error bars represent the SD. The SD values were too low to be seen on the graph. No statistically significant increase in the SAA3 protein concentrations and the relative Saa3 mRNA fold change values when priming with LPS was observed (Figure 27 & Figure 28). 49 Fold changes (relaove Saa3 mRNA) 40000 12.5 (TiO2+LPS) 25 (TiO2 +LPS) 50 (TiO2 +LPS) 20000 100 (TiO2 +LPS) 200 (TiO2 +LPS) 1 (LPS) 0 µg/ml Figure 28. Priming with LPS showed no effect on Saa3 mRNA response level. J774A.1 cells exposed to UV-‐TiO2: 12.5, 25, 50, 100, and 200µg/ml, were primed with 1µg/ml LPS. No statistically significant decrease or increase in Saa3 mRNA expression level was observed in J774A.1 cells, compared to samples only stimulated with only 1µg/ml LPS. Every bar represents a mean of four samples. All values were normalized to 18S reference gene. *=P≤0.05, **=P≤0.01, ***=P≤ 0.001. n=2. Error bars represent the SD. The SD values were too low to be seen on the graph. Conclusion (ELISA) ELISA assay is not sensitive enough for this study design. Therefore it was decided to only use qRT-‐
PCR in further experiments. Experiment 2 Three new NMs were tested: Printex-‐90, Mitsui and GO. The cells were exposed to the NMs in only the three highest concentrations: 50, 100, and 200µg/ml. 5 µg/ml of LPS were used as positive control in all the experiments (Appendix, Table 15). All experiments were repeated twice. Time Experiment First a time experiment was conducted to make sure that the most optimal was 24 hours of incubation after exposure. Cells were exposed to Printex-‐90, Mitsui and GO in concentration 100µg/ml and harvested after 3, 6, and 24 hours. 50 10 Graphene oxide 5 0 0 a) Printex-‐90 Mitsui Fold change (Relaove Saa3 mRNA) Fold change (Relaove SAA1 mRNA) Printex-‐90 5 10 15 Time (hours) 20 25 10 Mitsui Graphene oxide 5 0 0 b) 10 20 Time (hours) Figure 29(a-‐b). A549 (a) and J774A.1 (b) cells exposed to Printex-‐90, Mitsui, and GO. The cells were harvested at 3, 6, and 24 hours after exposure to the 100 µg/ml of different NMs. No statistically significant difference was found between the different time points, compared to the unexposed control values. The unexposed control values were set to 1 on the y-‐axis. The experiments were run with 5µg/ml of LPS as the positive control (Appendix, Table 15). Values were normalized to 18S reference gene. All values are a mean of 4 samples. n=2. Error bars represent SD. No statistically significant difference in fold change values were found at the different time points compared to the unexposed control values. Although not statistically significant, SAA1 and Saa3 mRNA yield was in general higher for samples harvest 24 hours after exposure (Figure 29). Therefore it was decided to proceed with 24 hours of incubation time after exposure. 51 Viability and Proliferation The viability and proliferation were measured and calculated for A549 and J774A.1 cells after exposure. The cells were exposed to Printex-‐90, Mitsui and GO. 100 *** 50 *** *** Viability (%) Viability (%) 100 50 0 0 50 100 150 * 50 100 * 0 200 Printex-‐90 (µg/ml) a) * b) 0 150 200 Mitsui (µg/ml) Viability (%) 100 50 0 c) 0 50 100 150 200 GO (µg/ml) Figure 30(a-‐c). A decrease in viability for J774A.1 cells after exposure to NMs. (Blue=Experiment 1, Red=Experiment2). J774A.1 cells exposed to Printex-‐90 (a) and Mitsui (b) showed a statistically significant decrease in viability compared to the unexposed control values. J774A.1 cells exposed to GO showed no statistically significant decrease in the viability compared to the unexposed control values. NMs were given in three different concentrations: 50, 100, and 200µg/ml. 5 µg/ml of LPS were used as the positive control (Appendix, Table 16). Every dot represents a mean of two samples. n=2. *=P≤0.05, **=P≤0.01, ***=P≤ 0.001. The viability of J774A.1 cells decreased statistically significantly for cells exposed to Printex-‐90 and Mitsui compared to the unexposed control values (Figure 30 (a-‐b)). No statistically significant 52 decrease was observed when cells were exposed to GO (Figure 30 (c)). A statistically significant decrease in the proliferation was also observed after exposure (Figure 31(a-‐c)). 100 *** 50,00 *** *** Proliferaoon (%) Proliferaoon (%) 100,00 0,00 0 a) 50 100 150 ** 50 ** ** 0 200 b) Printex-‐90 (µg/ml) 0 50 100 150 200 Mitsui (µg/ml) Proliferaoon (%) 100 *** 50 *** *** 0 0 c) 50 GO (µg/ml) 100 150 200 Figure 31 (a-‐c). The proliferation of J774A.1 cells was statistically significantly decreased when exposed to NMs. (Blue=Experiment 1, Red=Experiment2). J774A.1 stimulated with Printex-‐90 (a) showed a significant decrease in proliferation compared to control values. b) J774A.1 cells exposed to Mitsui showed a statistically significant decrease in proliferation. c) J774A.1 cells exposed to GO showed a statistically significant decrease in the proliferation compared to the unexposed control values. NMs were given in three different concentrations: 50, 100, and 200 (µg/ml). The experiments were run with LPS (5 µg/ml) as the positive control (Appendix, Table 16). The control value was set to 100%. Every dot represents a mean of 2 samples. n=2. *=P≤0.05, **=P≤0.01, ***=P≤ 0.001. In contrast to the J774A.1 cells, A549 cells didn’t alter proliferation rates or viability when exposed to the different NMs (Table 13). This finding is in correlation with the results from the pilot experiment, where A549 cells were stimulated with UV-‐TiO2 (Figure 17 (a-‐b) & Figure 19 (a-‐b)). 53 Table 13. No statistically significant decrease in viability or proliferation for A549 cells exposed to NMs. A549 cells were exposed to three different NMs: Printex-‐90, Mitsui, and GO. No statistically significant difference was found either for viability or proliferation, when compared to the unexposed control. The experiments were run with 5 µg/ml of LPS as the positive control. The values are a mean of 4 samples. The control values for the proliferations data were set to 100%. n=2. NMs Printex-‐90 LPS Mitsui LPS GO LPS Concentration (µg/ml) 0 50 100 200 5 0 50 100 200 5 0 50 100 200 5 Mean viability (%) 87.1 77.7 84.2 85.0 87.9 85.0 81.0 86.3 88.0 88.7 89.3 91.2 94.7 93.4 97.5 SD (Viability) 3.3 3.7 1.3 0.9 1.2 3.0 4.6 7.5 1.4 0.6 0.8 1.3 3.9 1.4 0.8 Mean proliferation (%) 100.0 117.9 91.5 93.8 94.2 100.0 90.4 94.2 110.1 97.2 100.0 104.8 75.9 89.2 89.1 SD (Proliferation) 0.6 6.3 1.6 3.4 2.5 0.9 3.3 1.1 6.5 2.4 1.4 3.2 4.3 1.6 0.3 qRT-‐PCR A549 cells exposed to Printex-‐90, Mitsui, and GO showed no statistically significant increase in the relative expression level of SAA1 mRNA (Figure 32). In general the fold change values for J774A.1 cells were higher compared to fold changes values for A549 cells, which also was observed in experiment 1 (Figure 22 & Figure 24). 54 Fold chamge (SAA1 mRNA) 10 Printex-‐90 5 Mitsui Graphene oxide 0 0 50 100 150 200 µg/ml Figure 32. A549 cells showed no statistically significant increase in the fold change compared to the unexposed samples. A549 cells were exposed to Pritex-‐90, Mitsui and GO in concentrations: 50, 100, and 200µg/ml. No statistically significant increase in the fold change compared to the unexposed samples. The unexposed control values were set to 1 on the y-‐axis. The experiment was run with 5 µg/ml of LPS as the positive control (Appendix, Table 17). Every dot represents a mean of four samples. All values were normalized to 18S reference gene. n=2. Error bars represent the SD. Of the three tested NMs only Mitsui statistically significantly induced an increase in Saa3 mRNA expression in the J774A.1 cells at concentrations 100 and 200µg/ml. The fold change was increased five times compared to the control value (Figure 33). The fold increase seems to reach plateau between 100 and 200µg/ml, none of the other concentrations or NMs showed a statistically significant fold change compared to the unexposed samples. 55 Fold change (relaove Saa3 mRNA) 10 *
*
5 Printex-‐90 Mitsui Graphene oxide 0 0 50 100 150 200 µg/ml Figure 33. Only J774A.1 cells exposed to Mitsui had a statistically significant increase in fold change. J774A.1 cells were exposed to Printex-‐90, Mitsui, and GO. Only cells exposed to Mitsui in the concentrations: 100 and 200µg/ml, showed a statistically significant increase in the fold change compared to the unexposed control values. The unexposed control values were set to 1 on the y-‐axis. The experiments were run with LPS (5 µg/ml) as the positive control (Appendix, Table 17). *=P≤0.05, **=P≤0.01, ***=P≤ 0.001. Every dot represents a mean of four samples. All values were normalized to 18S reference gene. n=2. Error bars represent the SD. Conclusion (Experiment 2): Despite the generally low expression levels, J774A.1 cells showed a positive tendency after exposure compared to the unexposed samples. Further experiments with A549 cells were therefore stopped due to a general low SAA1 mRNA expression level. J774A.1 cells were tested for Mcp-‐1 mRNA expression level after exposure to the four NMs. Mcp-‐1 Mcp-‐1, like Saa, has been implicated in the pathogenesis of atherosclerosis [136]. I therefore measured Mcp-‐1 in J774A.1 cells after exposure to: Printex-‐90, Mitsui, GO, and UV-‐TiO2 (Figure 34). 5µg/ml of LPS was used as the positive control (Appendix, Table 17). 56 Fold change (Mcp-‐1 mRNA) 10 Printex-‐90 Mitsui Graphene oxide 5 TiO2 0 0 50 100 µg/ml 150 200 Figure 34. No statistically significant increase in the expression of Mcp-‐1 mRNA after exposure. J774A.1 cells were exposed to: Printex-‐90, Mitsui, GO, and UV-‐TiO2. The NMs were given in three different concentrations: 50, 100, and 200µg/ml. No statistically significant difference in the fold change values of relative Mcp-‐1 mRNA compared to the unexposed samples for all NMs. The unexposed control values were set to 1 on the y-‐axis. The experiment was run with 5 µg/ml of LPS as the positive control (Appendix, 17). Every dot represents a mean of four samples. All values were normalized to 18S reference gene. n=2. The error bars represent SD. The SD values were too low to be seen on the graph. No statistically significant increase or decrease in the Mpc-‐1 fold change was found after exposure to all four NMs (Figure 34). For GO and UV-‐TiO2 there was a decrease in the fold change values after exposure. Although not statistically significant, this tendency was also observed for GO when testing for Saa3 mRNA fold change (Figure 33). The normalized Ct-‐values for Mcp-‐1 were all quite low, meaning that there was generally a high Mcp-‐1 mRNA expression level in the cells. The unexposed and the exposed samples all had the same normalized Ct-‐ values indicating that the exposure of NMs was not the reason for the high expression level. The positive control had a 10.2-‐fold, fold change in J774A.1 cells compared to the unexposed values (Appendix, Table 17). 57 Cell Cycle Analysis Due to a limited access to the cell cycle machine (Nucleocounter NC-‐250) only the A549 and J774A.1 cells exposed to Printex-‐90 and Mitsui at concentration 100 µg/ml were analyzed. Printex-‐90 and Mitsui were chosen because of a statistically significant decrease in both viability and proliferation after exposure in J774A.1 cells (Figure 30(a-‐b) & Figure 31(a-‐b)). Figure 35. J774A.1 cells exposed to Printex-‐90 and Mitsui stop dividing. J774A.1 cells were exposed to Printex-‐90 (CB) and Mitsui (CNT) in the concentration 100µg/ml. A stop in cell cycle was observed when exposed to NMs compared to the unexposed sample. n=1. An alteration in the cell cycle was seen when cells were exposed to Printex-‐90 or Mitsui (Figure 35). No new cells started dividing after the exposure. The result is in correlation with the statistically significant decrease in proliferation and viability, observed in J774A.1 cells after exposure (Figure 30(a-‐b) & Figure 31 (a-‐b)). 58 In contrast, A549 cells didn’t show any alterations in the cell cycle. After exposure, they were not affected by the NMs on a cell cycle level (Figure 36). This finding was also in correlation with observed proliferation and viability data form A549 cells (Table 13), where no statistically significant difference in the proliferation was observed when exposed to NMs. Figure 36. Cell cycle analysis showed no alternations in the cell cycle after exposure of Printex-‐90 and Mitsui in A549 cells. A549 cells were exposed to Printex-‐90 (CB) and Mitsui (CNT) in the concentration 100 µg/ml. The NMs had no effect on the cell cycle of A549 cells. n=1. 59 Discussion Previous studies have linked the exposure of particles to the risk of the development of CVD [2-‐4]. Inhalation of NMs has been reported to induce a strong pulmonary APR associated with increasing levels of SAA [14-‐16]. SAA is considered a risk marker for the development of atherosclerosis, but the cellular origin of SAA is still not understood The high production volume of many different NMs has presented a problem in risk assessment. Risk assessment of NMs in vivo is both costly in time and money [17]. Although in vitro experiments are less time-‐consuming and expensive, poor accordance between the two systems has been reported [36,96,97]. Development of an in vitro assay, which predicts the effect of NMs in vivo, could save time, money, and laboratory animals. Due to this, I wanted to the measure the expression levels of SAA1, Saa3 and Mcp-‐1 mRNA after exposure to different NMs. Furthermore, I wanted to rank the NMs according to their effect on SAA1, Saa3, and Mcp-‐1 mRNA levels, which were considered biomarkers for CVD. LPS-‐Induced mRNA Expression Levels Throughout my experiments, LPS was used as the positive control based on previous studies that have reported it to be a potent inducer of SAA and MCP-‐1 in vitro [86-‐88,98]. In general, A549 and J774A.1 cells showed large differences` in mRNA expression levels after exposure to LPS (Figure 21 & Figure 23). Previous studies have reported LPS to be a potent inducer of SAA3 secretion in macrophages [86-‐88]. I obtained similar results, showing a high upregulation of both Saa3 mRNA and SAA3 protein levels after exposure to LPS in J774A.1 cells, compared to the unexposed samples. As with Saa3, Mcp-‐1 mRNA expression levels were also statistically significantly increased after exposure to LPS in J774A.1 cells (Appendix, Table 17). My result is in agreement with other studies that have reported LPS as inducing the transcription of Mcp-‐1 both in vivo and in vitro [99,100]. In my experiments, the SAA1 mRNA expression levels after exposure to LPS were modest in A549 cells compared to J774A.1 cells. It has been reported that 10 µg/ml of LPS induces necrotic insult in A549 cells, which was in contrast to my findings where no changes in viability were observed (Figure 17a). Bozinovski et al. (2011) [101] reported that A549 cells stimulated with 10-‐9 M of SAA had a statistically significant increase in IL-‐8 production. If I were to carry out further experiments, I would grow A549 and J774A.1 cells in co-‐cultures to assess whether LPS-‐induced release of SAA3 60 from J774A.1 cells could stimulate A549 cells to secrete IL-‐8, which in turn enhances the pro-‐
inflammatory response. I observed a difference in Saa3 mRNA expression levels between J774A.1 cells exposed to LPS or NMs (Figure 23, Figure 24, and Figure 33). This indicates that LPS and NMs may induce pulmonary APR through different receptors. It is well established that LPS stimulates an immune response by interacting with tools like receptor 4 (TLR4) on the cell surface membrane [102]. Poulsen et al. (2015) [85] reported an up-‐regulated expression of many different receptors, including Tlr2, Tlr5, and Tlr13, in lung tissue from mice after exposure to MWCNT. This indicates that the NM-‐induced pulmonary APR is more likely to be mediated through several different receptors and not just TLR4. NM-‐induced mRNA Expression Levels In general, the normalized Ct-‐values for SAA1 and Saa3 were high, in both A549 and J774A.1 cells, indicating a low expression level of mRNA after exposure. Analysing the SAA3 protein levels, the protein concentrations were too low to be detected by ELISA (Figure 26) after exposure to UV-‐
TiO2. The ability of qRT-‐PCR to detect a signal compared to ELISA reflects differences in the sensitivity of the two methods. The average mRNA fold change values were approximately 3-‐fold higher compared to the unexposed samples, with only J774A.1 cells exposed to UV-‐TiO2 and Mitsui showing a statistically significant increase (Figure 24 & Figure 33). A549 cells showed no statistically significant effect on SAA1 mRNA level after exposure compared to the unexposed samples (Figure 22 & Figure 32). Mitsui and UV-‐TiO2 were the only NMs that gave a statistically significant increased Saa3 mRNA fold change value in J774A.1 cells. The statistically significant highest fold change values were obtained after exposure to UV-‐TiO2 (figure 24). I had expected Mitsui to be the most toxic because of it being a high-‐aspect to ratio NMs (HARN), which have a structural composition similar to asbestos [103]. In general, previous studies have reported that the Mitsui-‐induced response was greater compared to other NMs in vivo [15,104]. Saber et al. (2013) [15] exposed mice by intratracheal instillation to several NMs, including Mitsui, UV-‐TiO2, and Printex-‐90. The NMs were given in three different concentrations: 18, 54, or 162 µg/animal, and pulmonary RNA was assessed 1, 3, and 28 days after instillation. All the NMs increased pulmonary Saa3 mRNA expression level in a time-‐ and dose-‐dependent manner. Table 14 lists the mean fold change 61 values obtained in my experiments compared to Saber et al. (2013) [15]. At the early time points and at concentration 162 µg/animal, Mitsui and UV-‐TiO2 gave the strongest response with 600-‐fold and 400-‐fold increases in pulmonary Saa3 mRNA expression, respectively. Although my results also indicated that Mitsui and UV-‐TiO2 induced the highest Saa3 mRNA expression level in J774A.1 cells, the magnitude of the response was almost 240 times higher in vivo. The difference in Saa3 mRNA expression levels observed in my experiments compared to Saber et al.’s (2013) [15] results illustrates the difficulties in mimicking in vivo conditions in vitro. Table 14. Comparison of fold change values in vitro and in vivo [15]. NMs Fold change values, Difference in Fold change SAA1 (mean) Saa3 (mean) fold change values, Saa3 (my experiments, A549 (my experiments, (in vitro(mean) (Saber et al. cells) J774A.1 cells) vs. in vivo) (2013), in vivo) Mitsui 0.93 4.02 240 600 UV-‐TiO2 1.53 5.04 125 400 Printex-‐90 1.98 1.51 56.88 >100 GO 0.73 0.58 -‐-‐-‐-‐-‐-‐-‐-‐ -‐-‐-‐-‐-‐-‐-‐-‐-‐ Fold change values, The little correlation between fold change values found in my experiments compared to Saber et al.’s (2013) [15] is similar to previous studies that have investigated NMs in vivo and in vitro [96,97]. Poulsen et al. (2013) [36] investigated the effect of Mitsui in vivo and in vitro. They exposed mice for 18, 54, or 162 µg of Mitsui/animal and MutaTM mouse lung epithelial cell line (FE1) for 12.5, 25, and 100 µg Mitsui/ml medium. Samples were collected 24 hours post-‐exposure. The dose 162 µg/animal showed a statistically significant 45.6-‐fold upregulation of Saa3 mRNA and a statistically significant 4-‐fold upregulation of Mcp-‐1. The genes were upregulated in a dose-‐
dependent manner. In contrast to their in vivo observations, no statistically significant increase in Saa3 and Mcp-‐1 mRNA expression levels were found in vitro. Boucetta et al. (2013) [104] tested the effect of GO in vivo and in vitro. A549 cells were exposed to 0-‐125 µg/ml of GO and mice were intraperitoneally injected with 50 µg of GO in 0.5 ml 0.5 % BSA/saline and compared to pristine MWCNT. They reported no statistically significant increase in the inflammatory response in vitro or in vivo. Only mice exposed to MWCNTs showed and enhanced inflammatory response. These results are in agreement with my observations in J774A.1 cells. J774A.1 cells exposed to GO 62 showed no statistically significant increase in Saa3 mRNA expression levels, compared to the unexposed cells, whereas Mitsui exposure resulted in a statistically significant increase. In agreement with my findings, both Poulsen et al. (2013) [36] and Boucetta et al. (2013) [104] reported no statistically significant increase in pro-‐inflammatory cytokines in epithelial cells after exposure to either Mitsui or GO. This indicates that epithelial cells might play a more indirect role and may not be a good cell model for NM-‐induced pulmonary APR when grown in monocultures. Studies have reported that inhalation of NMs in vivo induced a pulmonary APR and close to no hepatic APR [14,15]. Weydahl (2015) [105] investigated the pulmonary and hepatic APR after exposure to Mitsui, UV-‐TiO2, Printex-‐90, and GO in vivo. She found that MWCNTs in particular was prone to induce both a hepatic and pulmonary APR in a dose-‐ and time-‐dependent manner. Furthermore, the hepatic APR was correlated with neutrophil influx in the lungs, indicating that the pulmonary exposure to MWCNTs triggers an induction of hepatic APR. Weydahl (2015) [105] results indicate that the NM-‐induced APR may be a very complex process with interactions between cells from both liver and lungs. Mimicking of this in vitro would be very complicated. J774A.1 cells have been shown to release IL-‐6 in response to exposure of NMs [106], which in turn may activate a hepatic APR. Although it`s a very simple setup, it could be interesting to investigate if exposure of alveolar macrophages stimulated with MWCNT could induce hepatocytes to secrete SAA, when grown in co-‐culture. NM-‐induced Cytotoxicity Although the NMs showed a modest effect on Saa3 and Mcp-‐1 mRNA expression levels, the viability and proliferation were statistically significantly decreased in J774A.1 cells in a dose-‐
dependent manner (Figure 30 &Figure 31). All the NMs, besides UV-‐TiO2 (Figure 18b & Figure 20b), had a cytotoxic effect on J774A.1 cells, with Printex-‐90 being the most potent (Figure 29a & Figure 30a). A549 cells exposed to NMs showed no cytotoxic effect (Figure 17b, Figure 19b, and Table 13). The variation in cytotoxic effect of NMs between A549 and J774A.1 cells may reflect the difference in sensitivity to NMs. This was tested by Kroll et al. (2008) [107] who investigated the effect of 23 different NMs in ten different cell lines, including A549 cells. They found a big difference in cytotoxic effect across cell lines, indicating the necessity in testing different cell lines in risk assessments of NMs. 63 Being cancer cell lines, I had expected both A549 and J774A.1 cells to be more resistant to the cytotoxic effect of NMs since they have defects in cell death and cell cycle-‐related pathways. Feliu et al. (2014) [108] compared the cytotoxic effect of cationic NMs in primary human bronchial epithelial cells (PBECs) and A549 cells. They observed that the cationic NMs only had a cytotoxic effect on PBECs and not A549 cells. Primary cells may be more representative of the in vivo system, but their heterogeneity and finite lifespan represent a major challenge when constructing a quantitative assay. Study Design The large difference in magnitude, of the fold change values, between my observations in vitro and previously published in vivo results is most likely due to difficulties in replicating the complexities of the in vivo system. In general, the relative mRNA expression levels were too low to conduct an actual quantitative assay that ranks the NMs according to their effect on SAA1, Saa3, and Mcp-‐1 mRNA levels. The following will be a discussion of different aspects of the study design, which could be optimized. Choice of Cell Line Alveolar type II epithelial and alveolar macrophages cell lines were chosen as cell models because they are considered as being potential early targets of inhaled NMs in the lungs [25,109,110]. Inhaled NMs will, due to their small size, deposit in the alveolar region of the lungs, where they will encounter alveolar macrophages. Alveolar macrophages are the first line of defence in the lungs. If the concentrations of NMs in the alveoli exceed the capacity of the macrophages to phagocytize, translocation from the lung into the bloodstream can occur. NMs have been reported to reach the systemic circulation [111,112]. Considering that alveoli have the most permeable epithelial layer of all, it might be the route of entry for NMs to go into circulation from the lungs. Furthermore, alveolar type II cells and tissue macrophages have both been reported to express SAA, which is considered a risk marker for development of atherosclerosis [113-‐115]. Besides their potential role in the NM-‐induced pulmonary APR, macrophages are reported to play a key role in the development of atherosclerosis [116,117]. Macrophage-‐derived foam cells are a key component of atherosclerotic plaque [118,119]. Lee et al. (2013) [57] investigated the effect of SAA on foam cell formation by stimulating Raw264.7 cells with LDL and SAA. They found that SAA 64 statistically significantly increased foam cell formation in a concentration-‐dependent manner. This indicates that the NM-‐induced release of SAA from alveolar macrophages in turn also could stimulate foam cell formation. Suzuki et al. (2014) [120] exposed human monocytic leukemia cells (THP-‐1) to metal oxide NP. The metal oxide NP increased the uptake of cholesterol by upregulating the expression of SR-‐BI resulting in foam cell formation. This was also shown by Cao et al. (2014) [121] who exposed THP-‐1a cells for Printex-‐90, which significantly increased the lipid accumulation. Based on Cao et al. (2014) [121] and Suzuki et al. (2014) [120] observations I would hypothesize that exposure of NMs to macrophages could stimulate the release of SAA, which in turn could bind to SR-‐BI and inhibit the cellular cholesterol efflux resulting in increased foam cell formation. Dose Selection and Exposure I hypothesized, based on in vivo publications that higher concentrations of NMs would induce a more potent mRNA response in vitro, but I didn’t observe this. Redoing my experiments with higher in vitro concentrations to get a higher Saa mRNA yield may result in increased cytotoxicity. Exposing J774A.1 cells to higher concentrations than 200 µg/ml might result in viability lower than 20 %. A low viability may also affect the Saa mRNA expression levels. Besides the low viability, a general problem of using high in vitro doses is that it is unrealistic compared to in vivo doses. Table 2 compares the in vitro doses used in my studies with those most commonly used in in vivo doses [15,84,85,122]. The highest dose in vitro, 200 µg/ml, is almost 32 times higher than the highest in vivo dose 100 µg/animal. Although the in vitro doses are much higher, observed Saa mRNA expression levels of target genes were low compared to previous published in vivo studies. This reflects the difficultly in establishing an in vitro model that predicts the in vivo results. The lack of different cell-‐cell interactions and cell signalling in vitro represents a big challenge. The use of lower doses and longer incubation times would be a more realistic exposure. Only a limited number of studies have compared the effect of lower doses of NMs and longer exposure times [105,123]. Comfort et al. (2014) [124] investigated the effect of very low doses (0.4-‐
400 pg/ml) of Ag-‐NP in keratinocyte cells (HaCaTs). To mimic the occupational exposure scenario, cells were exposed for 8 hours a day, 5 days a week, for 14 weeks. The amount of pro-‐
inflammatory cytokines, IL-‐6 and TNF-‐α, was analysed with ELISA. They observed that Ag-‐NP didn’t statistically significantly increase the pro-‐inflammatory cytokines after 14 weeks when compared 65 to 24 hours of exposure. Although they observed no statistically significant increase in pro-‐
inflammatory cytokines after 14 weeks compared to 24 hours of exposure, the results can vary a lot according to the use of different NMs and different cell lines. It could be interesting to investigate the effect of longer exposure times and lower doses in order to construct a screening assay that is more realistic to the in vivo doses. Even though the in vitro doses are in general considered high compared to in vivo, a major challenge lays in the submerged exposure. Determining the actually cellular dose, after adding the NMs directly to the bottom of the well, is difficult because only a fraction may actually reach the cells. Cells do in general respond to NMs by internalization and not to materials that remain suspended in media [125,126]. Processes such as diffusion and sedimentation, which are depending on size, shape, and density, can have an effect on the actual cellular dose. Smaller NMs (≤40 nm) are primarily driven by diffusion, while larger NMs (≥40 nm) are mostly driven by sedimentation. Larger materials (1000 nm) will, because of gravity, sediment more rapidly [125,127]. Teeguarden et al. (2007) [126] calculated that 1 nm NMs are, in respect to transport rate, 10 times more potent than 10-‐ and 100 nm NMs, but 10 times less potent than 1000 nm materials. In my experiments, LPS was a more potent inducer of Saa3 mRNA expression than NMs. The average size of LPS particles are 235-‐860 nm [128], indicating that LPS particles will more rapidly sediment than NMs. LPS and nano-‐TiO2 have both been shown to promote an inflammatory response through TLR4 [129,130]. Hypothesizing that all four NMs bind to TLR4, the difference in magnitude of response may be an indication of a low cellular dose when compared to LPS. As mentioned, NMs are likely to bind to several different TLRs, indicating that the low SAA1, Saa3, and Mcp-‐1 mRNA expression levels in A549 and J774A.1 cells after exposure to NMs is due to many different factors and cannot be narrowed down to just the cellular dose. Culturing Besides the different aspects already mentioned, the culturing method may constitute a big limitation. A549 and J774A.1 cells were grown in single-‐cell cultures, which is the simplest culturing method to be used. At present, although the complexity of the lungs cannot be fully mimicked by artificial cell cultures, a co-‐culture gives a more realistic mimic of the situation. Müller et al. (2010) [131] investigated the difference in cellular response in monocultures with A549 cells, human monocyte-‐derived macrophages (MDMs) as well as human monocyte-‐derived 66 dendritic cells (MDDCs), and in triple-‐cell co-‐cultures composed of all three cell types after exposure to SWCNTs and NP-‐TiO2. They found a statistically significantly higher production of TNF-‐
α in the triple-‐culture compared to the monocultures. In the monocultures, only TNF-‐α was expressed by the MDDCs, indicating that growing cells in monocultures could give misleading results. Although co-‐cultures can be used for assessing the possible cell-‐cell interactions, they still have some limitation. Adding the NMs suspensions directly to the culture plates is an unrealistic way of exposure. The disadvantages of submerged exposure are: the random diffusion of NM and the tendency of NMs to form agglomerates. An alternative is the air–liquid interface cell exposure system (ALICE) exposure system, which is a better method for mimicking the inhalation exposure conditions in the lungs. ALICE has been shown to be effective for controlling the cellular dose but still represents some challenge in the complexity of generating an aerosol [132,133]. Conclusion In summary, little correlation was found between the in vivo and in vitro fold change values for the three target genes. Mitsui and UV-‐TiO2 exposed cells gave the highest increase in fold change, which was in correlation with published in vivo results. In general, the mRNA expression levels were too low to conduct a quantitative assay that ranks the NMs according to their effect on SAA1, Saa3, and Mcp-‐1 mRNA expression levels. 67 Perspective The results of this thesis indicate to me that, at the present time, it was not possible to exchange in vivo with in vitro experiments for risk assessment of Printex-‐90, Mitsui, UV-‐TiO2, and GO according to their effect on SAA1, Saa3 and Mcp-‐1 mRNA expression level. The lack of proper in vitro culturing methods poses a major limitation. The lung consists of approximately 40 different highly specialized cells, whose interactions are lost when grown in monocultures [131]. The NM-‐
induced pulmonary APR is most likely a very complex process with interactions between many different cells in the lungs. Although co-‐culturing assesses the cell-‐cell interactions it still represents a simple cell model when compared to reality. If I was to carry out further experiments, I would seed A549 and J774A.1 cells in a co-‐culture to establish the possible interactions between them. To investigate if the release of SAA3 from J774A.1 cells, exposed to NMs, could stimulate A549 cells to secrete IL-‐8 and thus creating a positive feedback loop. Besides testing the interaction between A549 and J774A.1 cells, it would be interesting to test the effect of lower doses of NMs and longer incubation times. Although the co-‐culture might be good for assessing cell-‐cell interactions, the submerged exposure still represents a problem. If the co-‐culturing experiment of A549 and J774A.1 cells resulted in high Saa3 mRNA yield, the system could be transferred to ALICE in order to control the actual cellular dose. An alternative for in vitro toxicological assessment of NMs in the future would be by modelling/in silico approaches. The quantitative structure–activity relationship (QSAR) method is created on understanding the physicochemical properties of the NMs, which might predict its effect in vitro [134]. Despite the novel developments of the in vitro systems, they still represent some major limitations and challenges for toxicological screening of NMs. To date, the results of the in vitro experiments are still conflicting with the in vivo findings [36,135] and have therefore not earned widespread acceptance. The simplicity of the in vitro system and the lack of characterization of the in vitro dose have contributed to this problem. 68 References 1.
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