Applications of graphene to cell biology 1

APPLICATIONS OF GRAPHENE TO CELL BIOLOGY NICOLAS BOICHAT BSc, MSc, EPFL A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY NUS GRADUATE SCHOOL FOR INTEGRATIVE SCIENCES AND ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2014 Declaration I hereby declare that this thesis is my original work and it has been written by me in its entirety. I have duly acknowledged all the sources of information which have been used in the thesis. This thesis has also not been submitted for any degree in any university previously. Nicolas Boichat 13th March, 2015 ii Contents Table of Contents iii List of Figures ix List of Tables xiii Introduction 1.1 Graphene . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.1 Fabrication . . . . . . . . . . . . . . . . . . . . . . . 1.1.2 Electrical properties . . . . . . . . . . . . . . . . . . 1.2 Graphene in cell biology . . . . . . . . . . . . . . . . . . . . 11 1.3 Use of graphene as a sensor . . . . . . . . . . . . . . . . . . 12 1.4 Force sensing . . . . . . . . . . . . . . . . . . . . . . . . . . 14 1.5 Cell counting . . . . . . . . . . . . . . . . . . . . . . . . . . 16 1.5.1 Electrical methods . . . . . . . . . . . . . . . . . . . 17 Graphene and cells 2.1 21 Cells on fibronectin-coated graphene . . . . . . . . . . . . . 22 2.1.1 Materials and methods . . . . . . . . . . . . . . . . . 22 2.1.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . 25 2.1.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . 27 iii 2.1.4 2.2 2.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . 29 Graphene as a substrate modifier . . . . . . . . . . . . . . . 30 2.2.1 Materials and methods . . . . . . . . . . . . . . . . . 31 2.2.2 Results and discussion . . . . . . . . . . . . . . . . . 32 2.2.3 Potential future work . . . . . . . . . . . . . . . . . . 33 Graphene functionalization . . . . . . . . . . . . . . . . . . . 40 2.3.1 Materials and methods . . . . . . . . . . . . . . . . . 40 2.3.2 Results and discussion . . . . . . . . . . . . . . . . . 41 2.3.3 Potential future work . . . . . . . . . . . . . . . . . . 47 Early sensor attempts 3.1 49 Capacitive . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.1.1 Numerical values for PDMS dielectric . . . . . . . . . 53 3.1.2 Sample device . . . . . . . . . . . . . . . . . . . . . . 55 3.1.3 Potential future work . . . . . . . . . . . . . . . . . . 57 3.2 Piezoresistive film . . . . . . . . . . . . . . . . . . . . . . . . 58 3.3 Graphene as strain gauge . . . . . . . . . . . . . . . . . . . . 60 3.4 Piezoelectric film . . . . . . . . . . . . . . . . . . . . . . . . 61 3.4.1 PVDF . . . . . . . . . . . . . . . . . . . . . . . . . . 62 3.4.2 Experimental results . . . . . . . . . . . . . . . . . . 63 3.4.3 Potential future work . . . . . . . . . . . . . . . . . . 63 3.5 Quartz crystal micro-balance (QCM) . . . . . . . . . . . . . 65 3.6 Electrical interface . . . . . . . . . . . . . . . . . . . . . . . 70 Cell sensing device 4.1 73 First device design . . . . . . . . . . . . . . . . . . . . . . . 74 4.1.1 Materials and methods . . . . . . . . . . . . . . . . . 74 iv 4.2 4.3 4.1.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . 87 4.1.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . 103 Inverted device design — cell counting . . . . . . . . . . . . 110 4.2.1 Material and Methods . . . . . . . . . . . . . . . . . 110 4.2.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . 113 4.2.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . 115 Conclusion and future work . . . . . . . . . . . . . . . . . . 120 Conclusion 123 Bibliography 127 A Cell migration analysis framework 139 A.1 Segmentation and tracking . . . . . . . . . . . . . . . . . . . 139 A.2 Motion analysis . . . . . . . . . . . . . . . . . . . . . . . . . 140 A.2.1 Motion characterization . . . . . . . . . . . . . . . . 143 B Large cells: Amoeba 149 B.1 Motility and substrate affinity . . . . . . . . . . . . . . . . . 150 B.2 Forces exerted on the surface . . . . . . . . . . . . . . . . . . 153 B.3 Fixed staining . . . . . . . . . . . . . . . . . . . . . . . . . . 155 B.4 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 C Effect of localized forces on cells 159 C.1 First device design . . . . . . . . . . . . . . . . . . . . . . . 160 C.1.1 Experiments with cells . . . . . . . . . . . . . . . . . 163 C.2 Second device design . . . . . . . . . . . . . . . . . . . . . . 165 C.2.1 Experiments with cells . . . . . . . . . . . . . . . . . 167 C.2.2 AFM characterization . . . . . . . . . . . . . . . . . 168 v C.3 Conclusion and future work . . . . . . . . . . . . . . . . . . 173 vi Summary In this thesis, I investigate potential uses of graphene in cell biology. Graphene is a novel 2-dimensional material, composed of carbon atom arranged in a honeycomb lattice structure. Graphene has a number of exciting properties, and, in this work, I make use of its transparency, surface properties, and ability to sense, electronically, molecules on its surface. I first look into graphene as a substrate for epithelial, mammalian cells. This is an important step in order to establish if graphene can be used for sensing applications, which is our ultimate goal. Transferring graphene onto a flexible polymer substrate (PDMS), I show that cell motility on graphene, coated with fibronectin, is not significantly different from the baseline PDMS substrate. However, when graphene is transferred to glass, and left uncoated, cells show a dramatic preference for glass, probably due to the hydrophobic nature of graphene. I then show how it is possible to attach molecules onto the graphene sheet using an existing pyrene-based method, and quantify the number of target molecules attached as a function of concentration. Knowing that graphene does not perturb cells in a significant manner, I move on to the original idea of this thesis, which consists in creating a graphene-based force sensor. Measuring forces exerted by cells on their vii substrate is an important biological question, and current approaches all have limitations. Using graphene’s transparency and remarkable electronic properties, I hoped to build a device that would provide electrical readout of force information, while allowing for optical imaging of cells. Five different approaches were considered, some did not leave the design phase, while large prototypes were built for others. However, all of these approaches had significant issues, especially when scaled to lower sizes. Despite this drawback, the techniques I developed allowed to create a much simpler device, that produces interesting results: a graphene-based device could be used as a simple cell counter. A large piece of graphene is transferred to a coverslip, connected with electrodes, and put in a Petri dish with a platinum gating electrode. By sweeping the gate voltage to measure electrical parameters such as Dirac peak and motility, a large shift in Dirac peak is observed when live cells are added onto the device. I proceed to eliminate possible reasons for this device response, and hypothesize that the device is detecting charged proteins produced by cells, that get adsorbed onto the graphene surface. Finally, I show that the device response depends on the number of live cells in the dish. This means that the device could be used as a simple cell counter, that could measure cell metabolism and viability without any manipulation of the cells (such as splitting, staining), or requiring direct contact with the cells. viii List of Figures 1.1 Graphene gate voltage vs resistance/conductance . . . . . . 1.2 Graphene back-gating 1.3 Graphene gate voltage vs resistance/conductance curve, with . . . . . . . . . . . . . . . . . . . . . fitted parameters. . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Electrolyte gating of graphene . . . . . . . . . . . . . . . . . 10 1.5 Effect of charges on graphene vs bulk material . . . . . . . . 13 2.1 Glass bottom dish with PDMS and graphene . . . . . . . . . 23 2.2 IEC-6 cells on graphene/PDMS . . . . . . . . . . . . . . . . 24 2.3 Average speed on graphene vs PDMS vs glass . . . . . . . . 26 2.4 Immunostaining of IEC-6 cells on graphene vs PDMS . . . . 27 2.5 Immunostaining of IEC-6 cells on graphene vs PDMS — data analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . 28 2.6 Patterned graphene design to be written with electron beam. 32 2.7 Timelapse of cell growth and motion on patterned graphene. 2.8 HeLa cells after 32h on graphene pattern on glass. . . . . . . 36 2.9 Cells on a 5µm glass/graphene pattern . . . . . . . . . . . . 37 35 2.10 Fixed HeLa cells after 48h on pattern. . . . . . . . . . . . . 38 2.11 Fixed HeLa cells after 48h on high-resolution pattern . . . . 39 2.12 Emission spectrum of pyrene . . . . . . . . . . . . . . . . . . 42 ix 2.13 Emission spectrum of streptavidin with Alexa 647. . . . . . . 42 2.14 Functionalized graphene fluorescence images, 10x. . . . . . . 44 2.15 Functionalized graphene fluorescence images, 40x. . . . . . . 45 2.16 Pyrene concentration vs Pyrene fluorescence. . . . . . . . . . 46 2.17 Pyrene concentration vs Streptavidin fluorescence. . . . . . . 47 3.1 Basic layer grid sensor design. . . . . . . . . . . . . . . . . 50 3.2 3D-printed “table” to apply a controlled pressure on the device. 55 3.3 Capacitive readout on sample device. . . . . . . . . . . . . . 56 3.4 Capacitive design allowing measurements of shear forces. . . 57 3.5 PDMS mixture with Carbon Black . . . . . . . . . . . . . . 59 3.6 Graphene as a strain gauge . . . . . . . . . . . . . . . . . . . 61 3.7 Sample PVDF shock sensor from Piezotech. . . . . . . . . . 64 3.8 Charge amplifier circuit . . . . . . . . . . . . . . . . . . . . . 64 3.9 Sample output from the sample shock sensor . . . . . . . . . 64 3.10 Frequency response of a quartz crystal. . . . . . . . . . . . . 66 3.11 4.433619 Mhz quartz crystal picture. . . . . . . . . . . . . . 68 3.12 Interface between the device and measurement equipments. . 71 4.1 Device fabrication steps, after graphene transfer to a coverslip. 76 4.2 Electrolyte gating of graphene . . . . . . . . . . . . . . . . . 77 4.3 Custom-built Processing software screenshot . . . . . . . . . 78 4.4 Measurement circuit setup . . . . . . . . . . . . . . . . . . . 79 4.5 Sample gate-voltage vs resistance curves for one experiment 4.6 Graphene gate voltage vs conductance curve, with fitted pa- 81 rameters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 4.7 Sample processed results for one experiment . . . . . . . . . 84 x appears that the cell anchors to both sides of a graphene line (i.e. the cell anchors to the more preferable glass lines), leading to an elongated shape. After the cell divides, both daughter cells quickly regain a similar polarity. Finally, Figures 2.10 and 2.11 show fixed staining of cells, 48 hours after seeding. Figure 2.10a shows cells extending above a line of graphene, attaching to other cells on top, and creating focal adhesions at the bottom, on the glass. The effect of higher resolution patterns (1, 3, µm lines) is less clear, but some alignment of actin fibers and focal adhesion sites can be seen (Figure 2.11). 2.2.3 Potential future work Techniques such as nanoimprint lithography [42] already exist for patterning hydrophobic and hydrophilic surfaces. However, the method presented here has the advantage of not requiring any mold, making it easy to change the pattern, while providing a high resolution of micron or less, potentially down to few nanometers, as I am using electron beam lithography [46]. However, electron beam lithography suffers from the fact that only small areas can be written (usually a cm edge square), at a very slow speed. This can be circumvented by using laser writing technologies that can write quickly over much larger areas [75], at the expense of an inferior resolution. As it currently stands, this technique has limited advantages over established ones, and is not as specific as stamping adhesion proteins. Furthermore, HeLa cells prefer attaching to glass, which makes it hard to combine this technique with other properties of graphene, for example for electrical stimulation/sensing. Using other cell types, that prefer hydrophobic 33 substrates (e.g. macrophages), or that behave differently on graphene (e.g. stem cells), might prove of more interest. Alternatively, the graphene could be functionalized to favor cell adhesion, for example with RGD peptides. 34 Figure 2.7: Timelapse of cell growth and motion on patterned graphene after 0, 6, 12, 18, 24 and 27 hours. A: Straight lines; B: High resolution pattern; C: 100µm squares (see Figure 2.6). Some alignment can be observed after hours already (especially on the lines). At later timepoints, more cells can be seen on graphene, probably because of higher density. 35 Figure 2.8: HeLa cells after 32h on pattern. Red overlay shows pattern of graphene (light red corresponds to glass), acquired before seeding cells (also showing PMMA residues). 36 Figure 2.9: Cells on a 5µm glass/graphene pattern. The cell on top of the image strongly polarizes, divides, and daughter cells keep this polarity. 37 (a) Cells on 50µm glass/graphene lines: some cells can clearly be seen “stretching” over the graphene strip, tied down by cell-cell-junction on top, and by a higher density of focal adhesions on the glass area at the bottom. (b) Cells on 10 and 20µm glass/graphene lines. (c) Cells on a 100µm square. Figure 2.10: Fixed HeLa cells after 48h on pattern. Left: Bright field image. Darker area: graphene; Lighter area: glass. Right: Blue: nuclei (DAPI); Green: vinculin (immunostaining); Red: actin (phalloidin) 38 (a) Cells on 5µm and 3µm glass/graphene lines. (b) Cells on 1µm glass/graphene lines. Figure 2.11: Fixed HeLa cells after 48h on high-resolution pattern. The effect of such high frequency patterns is not obvious at first, but some alignment of the actin cytoskeleton and focal adhesion can be observed. 39 2.3 Graphene functionalization Reagents and valuable input from Chenghan Yu, MechanoBiology Institute Graphene functionalization makes it possible to modify the surface properties of graphene, as well as to use graphene as a sensor for specific biomolecules. As a first proof of concept, I decided to functionalize graphene with fluorescent streptavidin. I followed a method presented by Huang et al. [53], where CVD graphene is functionalized with pyrene, through pi-pi interactions. This simple method is an extension of a well-known functionalization technique for carbon nanotubes [49]. In this work, focused on sensing applications, I want to maintain the electrical properties of CVD graphene: This eliminates other approaches, making use of graphene oxide, or graphene flakes suspension. Additionally, covalent binding of molecules to the graphene substrate is not desired as it disrupts graphene structure [38]. 2.3.1 Materials and methods A 10 mm by mm piece of CVD graphene is transferred to a glass slide [97]. Then, the technique presented by Huang et al. [53] is fol- lowed: Graphene is incubated with 1-Pyrenebutanoic acid, succinimidyl ester (Pyrene-NHS, AnaSpec 81238) in Dimethylformamide (DMF). Pyrene binds to the graphene, leaving the NHS group free for further functionalization. Streptavidin, tagged with Alexa Fluor 647 (Invitrogen S21374), is then incubated on the graphene device in a sodium bicarbonate buffer 40 (Na2 CO3 − NaHCO3 buffer solution, pH 9.0), binding with the NHS groups on the surface. Following that, the device was rinsed in PBS, then DI water, and dried for measurements. Pyrene is naturally fluorescent, with an absorption and emission peaks at 345nm/390nm respectively, while streptavidin is conjugated with an Alexa dye, with peaks at 640nm/675nm. I then image the device using a Olympus BX-61 upright wide-field microscope, at 10x or 40x magnification. I use a 365nm excitation to try to observe pyrene, and a 635nm for streptavidin. As images were fairly inconclusive, I look at the fluorescence spectrum of the graphene sheet using a spectrophotometer (Tecan Inifinite M200 Pro, Professor Kini’s lab at DBS). I vary the concentration of Pyrene-NHS in DMF (ranging from to 10 mg/mL), but keep the concentration of Streptavidin fixed (1 µg/mL: more than enough to cover the graphene sheet). For each sample, to measurements are performed, varying their position in the plate reader to minimize errors, and avoid repeating measurements on areas that could be poorly covered with graphene. For pyrene, an emission wavelength of 345nm is chosen, and fluorescence is measured at 390nm (sample spectrum see Figure 2.12). For streptavidinAlexa 647, an emission wavelength of 640nm is selected, and fluorescence is measured at 675nm, see Figure 2.13. 2.3.2 Results and discussion Optical images (Figure 2.14) vary in appearance: In some area, a clear red fluorescence signal is seen (Figure 2.14a), while, at the interface between graphene and glass (Figure 2.14b), the graphene is clearly darker. Light 41 1000 900 800 600 700 Intensity (AU) 380 390 400 410 420 430 440 450 Emission wavelength (nm) 200 150 50 100 Intensity (AU) 250 Figure 2.12: Emission spectrum of pyrene on graphene, at 345nm excitation wavelength. A clear fluorescence peak can be observed at 390nm. 680 700 720 740 Emission wavelength (nm) Figure 2.13: Emission spectrum of streptavidin with Alexa 647 on functionalized graphene, at 640nm excitation wavelength. In this case the peak overlaps significantly with the excitation wavelength, and only the decreasing part of the curve can be observed. Therefore, we quantify the emission at the shortest possible wavelength: 675nm. 42 absorption from the graphene is not likely to explain this phenomenon (especially considered that I am imaging using an upright microscope). Most likely, graphene is quenching the fluorophores, which is known to happen from the literature [62]. Figure 2.15 shows images at higher magnification, that probably reveal pyrene fluorescence. Both images shows interesting “speckles” in the bright field image, possibly corresponding to islands of multi-layer graphene, which are known imperfections of CVD graphene (those cannot be seen on non-functionalized graphene). The top image possibly shows ripples of graphene in the bottom-right corner of the red fluorescence image. The bottom image seems to confirm the good binding between rolled-up graphene and streptavidin, in areas where the graphene does not seem to be able to quench the fluorescence. Images are fairly inconclusive on whether or not the functionalization is working. Since graphene is quenching fluorescence, it makes it hard to know whether streptavidin is present on the surface of the graphene, and if so, if it is properly conjugated with pyrene, or if it was just adsorbed onto the surface. Therefore, I move to a spectrophotometer, that allows to observe the full spectrum of fluorescence, providing higher sensitivity and specificity. For each experiment, a number of different pyrene concentrations are tested, and multiple measurements are obtained at different locations on each sample. For pyrene fluorescence, results are shown in Figure 2.16: First, one has to note that there is significant variability across a single experiment, and even more across multiple experiments. Reasons could include variable quality of graphene, residues on graphene, or slight variations when 43 (a) In few areas, a large red fluorescence signal is observed. (b) Interface between glass and graphene, showing possible quenching of the Alexa fluorophore. Figure 2.14: Functionalized graphene, taken at 10x magnification (top left: bright field, top right: 365nm excitation, bottom left: 635nm). Not much signal is seen using 365nm. 44 Figure 2.15: Images at 40x magnification, that probably reveal pyrene fluorescence in the blue image. Both images shows interesting “speckles” in the bright field image, possibly corresponding to “islands” of multi-layer graphene, which are known imperfections of CVD graphene. The top image possibly shows “ripples” of graphene in the bottom-right corner of the red fluorescence image. The bottom image seems to confirm the good binding between rolled-up graphene and streptavidin, in areas where the graphene does not seem to be able to quench the fluorescence. 45 performing the functionalization (e.g. during washing). However, when looking at the data, a trend seems to appear (shown in red): Fluorescence intensity increases with concentration in a somewhat linear fashion, possibly saturating at higher concentration. Figure 2.17 shows streptavidin fluorescence versus pyrene concentration. Again, I observe a lot of variability, but the data exhibits some proportionality between pyrene concentration and the amount of streptavidin bound on the surface. 1500 ● Data "Eyeball" fit Set Set Set Set Set 1000 ● ● ● ● ● 500 Fluorescence intensity at 390 nm (AU) 2000 Pyrene fluorescence intensity ● ● ● ● ● ● ● ● ●● ● ● ● ● 0.0 1.0 2.0 5.0 10.0 Pyrene concentration (mg/mL Pyrene−NHS/DMF) Figure 2.16: Pyrene concentration vs Pyrene fluorescence. For each of the experiments, different concentrations are tested, and multiple measurements are obtained for each sample, at different locations. Some proportionality between pyrene concentration and its fluorescence can be observed, possibly saturating at higher concentrations. 46 Streptavidin fluorescence intensity Data "Eyeball" fit 100 150 200 250 300 Set Set Set 50 Fluorescence intensity at 675 nm (AU) 350 ● 0.0 1.0 2.0 5.0 10.0 Pyrene concentration (mg/mL Pyrene−NHS/DMF) Figure 2.17: Pyrene concentration vs Streptavidin fluorescence. Only sets to from Figure 2.16 are presented here, as the goal of sets and was to evaluate pyrene functionalization only (no Streptavidin was added). Several measurements are obtained for each sample. Again, some proportionality appears between the concentration of pyrene used during functionalization, and the amount of streptavidin on the surface. 2.3.3 Potential future work The data I collected here, despite its important variability, shows a trend that gives us a good indication that the functionalization is successful. The variability of the spectroscopic data, as well as the optical images, however, does indicate that the functionalization may not be uniform: it is possible that edges, and other defects in the graphene sheet, are more favorable to functionalization. Huang et al. demonstrate functionalization by scanning a small area us47 ing AFM [53], but larger scale microspectroscopic techniques (either using fluorescence, or Raman spectra) would give better insight on the quality of the coverage. From these results, the next step is to pick a good concentration of Pyrene-NHS (between to mg/mL), and bind useful biotin-linked molecules to the streptavidin. One could use biotin-RGD to pattern cell adhesion favorable proteins on graphene (RGD is a minimal unit required for integrins in cells to bind to a substrate), extending the work presented in Section 2.2. When it comes to sensing applications, one drawback of this method is the use of strepatividin, which is a fairly large molecule (52.8 kDa), with a diameter around 5nm [29]. Therefore, any bound molecule will only be about 5nm from the graphene sheet, which reduces the doping effect on the graphene device. As a workaround, one can rely on indirect detection, functionalizing graphene with an enzyme, and detecting variations in its substrates or products concentration, as done by Huang et al. to detect glucose, using a glucose oxydase enzyme [53]. In that case, the usefulness of functionalization is doubtful, as using bare graphene, and adding the enzyme directly in solution would be far simpler. I originally believed that this kind of functionalization would be necessary for any sensing application. However, Chapter shows that bare graphene already provides good sensitivity to the presence of cells in solution, so the simpler scheme, without functionalization, was preferred for the rest of this work. In future work, functionalization might prove useful if it can increase specificity, while maintaining an acceptable sensitivity. 48 [...]... precision of the cell counting device 11 7 A .1 Example of cell tracking using nuclei staining 14 0 A.2 Example of Mean Square Displacement curve 14 2 A.3 IEC-6 cells, graphene substrate 14 4 A.4 IEC-6 speed for 14 points, on 3 substrates 14 6 A.5 Average speed on 3 substrates 14 8 B .1 Images of Chaos cells on 3 different substrates 15 1 B.2... 10 2 4.28 Analysis of device response to different densities of cells 10 3 4.29 Probable explanation for mobility change after adding serum 10 6 4.30 Probable explanation for Dirac peak after adding cells 10 6 xi 4. 31 Inverted device design 11 1 4.32 Inverted device photo 11 2 4.33 Results of a number of experiments on an inverted device 11 4 4.34 Computed... pulses have been applied to the device 16 8 xii C.9 Deflection of the AFM tip when a pulse is applied to the device 17 0 C .10 Deflection of the AFM tip vs current applied 17 1 C .11 Initial deflection and acceleration of the AFM tip 17 2 xiii xiv List of Tables 1. 1 Comparison of commercial cell counting techniques 20 3 .1 Comparison of force sensor approaches... lead to the discovery of the effects of cells on graphene devices, described in Chapter 4 1. 5 Cell counting Many protocols in cell biology require counting the number of cells in a flask or dish, and a variety of methods is available (see Table 1. 1, [34]) The standard, and oldest, method, is to use a hemocytometer: cells are detached from the flask, and a small amount of the suspension is inserted into... dipping into a liquid containing ions (e.g salt buffer) 10 1. 2 Graphene in cell biology Graphene has only been the focus of limited interest as a substrate in the context of cell biology, with most work investigating toxicity or general cell behavior and differentiation Graphene nanosheets have been shown to be harmful to bacteria [2], and small graphene oxide sheet cause damage to red blood cells and... spectroscopy of graphene on glass 88 4 .10 Device response to live cells 89 4 .11 Control experiment: increase pH 90 4 .12 Control experiment: decrease pH 91 4 .13 Control experiment: pH vs Dirac peak position 91 4 .14 Device response to Poly-lysine 92 4 .15 Device response to Poly-glutamic acid 93 4 .16 Device response to. .. 93 4 .17 Device response to cells, in serum-free medium 95 4 .18 Device response to FBS, then cells 95 4 .19 Device response to dead cells 96 4.20 Experimental setup to verify device response to cells that are not in direct contact with graphene 97 4. 21 Device response to cells that are not in direct contact with graphene ... 15 1 B.2 Images of a Chaos cell at higher magnification 15 2 B.3 Chaos Carolinensis on 1: 80 PDMS with fluorescent beads 15 4 B.4 Displacement of a single bead due to substrate deformation cause by Chaos Carolinensis 15 5 B.5 Fixed staining of Chaos Carolinensis 15 6 C .1 First design of PVDF device to apply forces on cells 16 1 C.2 Z displacement of the piezoelectric... from a block of graphite [87] This enabled the authors to perform electrical measurement on the material, observing a gate voltage dependence of the graphene sheet conductance Graphene has a number of remarkable electrical, optical and mechanical properties [37, 66, 82], and this thesis makes uses of a number of them, in an attempt to uncover possible applications of graphene to cell biology 1 First, it... time Advantages • Cheap • Easy to detect clumps • Can examine cells • Simple and fast • Does not require to resuspend cells • Real-time monitoring of cell viability • Provides cell cycle stage information • Does not require to resuspend cells • Does not require contact with cells • Can detect viability Table 1. 1: Comparison of commercial cell counting techniques with the graphene- based device presented . Boichat 13 th March, 2 015 ii Contents Table of Contents iii List of Figures ix List of Tables xiii 1 Introduction 1 1 .1 Graphene . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1 .1. 1 Fabrication. . . . . . . . . 11 2 4.33 Results of a number of experiments on an inverted device. . 11 4 4.34 Computed precision of the cell counting device. . . . . . . . 11 7 A .1 Example of cell tracking using. . . 17 0 C .10 Deflection of the AFM tip vs current applied. . . . . . . . . 17 1 C .11 Initial deflection and acceleration of the AFM tip. . . . . . . 17 2 xiii xiv List of Tables 1. 1 Comparison of