Bio

Bio


Silvan Türkcan grew up in Munich, Germany. He has received his BS in Physics from McGill University in Canada, a MS from Technische Universität München (TUM), Germany and a PhD in Biophysics (2010) from the Ecole Polytechnique in France. His dissertation focused on studying the architecture of the cell membrane through single-molecule tracking. As a postdoctoral fellow he was working on the analysis of molecular trajectories at the Pasteur Institute in France. In the Xing lab he is working with Dr. Pratx on microscopy techniques using radioluminescence.

Professional Education


  • Doctor of Philosophy, Ecole Polytechnique (2010)
  • Master of Science, Technische Universitat Munchen (2007)
  • Bachelor of Science, McGill University (2005)

Stanford Advisors


Research & Scholarship

Current Research and Scholarly Interests


My project aims at studying the metabolism of single tumor cells as an additional hallmark of cancer. Otto Warburg discovered in 1920s that while normal cells oxidize sugar (oxidative phosphorylation) cancer cells ferment sugar (glycolysis). We are currently developing a new imaging tool called the radioluminescence microscope, which can quantitatively measure the uptake of FDG, a sugar analog into single live cells. By studying the uptake of FDG and various cellular parameters, we hope to better understand the impact of genetic and non-genetic heterogeneities on the disease progression.

Lab Affiliations


Publications

Journal Articles


  • Seeing the invisible: Direct visualization of therapeutic radiation beams using air scintillation MEDICAL PHYSICS Fahimian, B., Ceballos, A., Tuerkcan, S., Kapp, D. S., Pratx, G. 2014; 41 (1)

    Abstract

    Purpose: To assess whether air scintillation produced during standard radiation treatments can be visualized and used to monitor a beam in a nonperturbing manner.Methods: Air scintillation is caused by the excitation of nitrogen gas by ionizing radiation. This weak emission occurs predominantly in the 300-430 nm range. An electron-multiplication charge-coupled device camera, outfitted with an f∕0.95 lens, was used to capture air scintillation produced by kilovoltage photon beams and megavoltage electron beams used in radiation therapy. The treatment rooms were prepared to block background light and a short-pass filter was utilized to block light above 440 nm.Results: Air scintillation from an orthovoltage unit (50 kVp, 30 mA) was visualized with a relatively short exposure time (10 s) and showed an inverse falloff (r(2) = 0.89). Electron beams were also imaged. For a fixed exposure time (100 s), air scintillation was proportional to dose rate (r(2) = 0.9998). As energy increased, the divergence of the electron beam decreased and the penumbra improved. By irradiating a transparent phantom, the authors also showed that Cherenkov luminescence did not interfere with the detection of air scintillation. In a final illustration of the capabilities of this new technique, the authors visualized air scintillation produced during a total skin irradiation treatment.Conclusions: Air scintillation can be measured to monitor a radiation beam in an inexpensive and nonperturbing manner. This physical phenomenon could be useful for dosimetry of therapeutic radiation beams or for online detection of gross errors during fractionated treatments.

    View details for DOI 10.1118/1.4851595

    View details for Web of Science ID 000329182200004

    View details for PubMedID 24387491

  • Bayesian Decision Tree for the Classification of the Mode of Motion in Single-Molecule Trajectories PLOS ONE Tuerkcan, S., Masson, J. 2013; 8 (12)

    Abstract

    Membrane proteins move in heterogeneous environments with spatially (sometimes temporally) varying friction and with biochemical interactions with various partners. It is important to reliably distinguish different modes of motion to improve our knowledge of the membrane architecture and to understand the nature of interactions between membrane proteins and their environments. Here, we present an analysis technique for single molecule tracking (SMT) trajectories that can determine the preferred model of motion that best matches observed trajectories. The method is based on Bayesian inference to calculate the posteriori probability of an observed trajectory according to a certain model. Information theory criteria, such as the Bayesian information criterion (BIC), the Akaike information criterion (AIC), and modified AIC (AICc), are used to select the preferred model. The considered group of models includes free Brownian motion, and confined motion in 2nd or 4th order potentials. We determine the best information criteria for classifying trajectories. We tested its limits through simulations matching large sets of experimental conditions and we built a decision tree. This decision tree first uses the BIC to distinguish between free Brownian motion and confined motion. In a second step, it classifies the confining potential further using the AIC. We apply the method to experimental Clostridium Perfingens [Formula: see text]-toxin (CP[Formula: see text]T) receptor trajectories to show that these receptors are confined by a spring-like potential. An adaptation of this technique was applied on a sliding window in the temporal dimension along the trajectory. We applied this adaptation to experimental CP[Formula: see text]T trajectories that lose confinement due to disaggregation of confining domains. This new technique adds another dimension to the discussion of SMT data. The mode of motion of a receptor might hold more biologically relevant information than the diffusion coefficient or domain size and may be a better tool to classify and compare different SMT experiments.

    View details for DOI 10.1371/journal.pone.0082799

    View details for Web of Science ID 000328745100059

    View details for PubMedID 24376584

  • Probing Membrane Protein Interactions with Their Lipid Raft Environment Using Single-Molecule Tracking and Bayesian Inference Analysis PLOS ONE Tuerkcan, S., Richly, M. U., Alexandrou, A., Masson, J. 2013; 8 (1)

    Abstract

    The statistical properties of membrane protein random walks reveal information on the interactions between the proteins and their environments. These interactions can be included in an overdamped Langevin equation framework where they are injected in either or both the friction field and the potential field. Using a Bayesian inference scheme, both the friction and potential fields acting on the ?-toxin receptor in its lipid raft have been measured. Two types of events were used to probe these interactions. First, active events, the removal of cholesterol and sphingolipid molecules, were used to measure the time evolution of confining potentials and diffusion fields. Second, passive rare events, de-confinement of the receptors from one raft and transition to an adjacent one, were used to measure hopping energies. Lipid interactions with the ?-toxin receptor are found to be an essential source of confinement. ?-toxin receptor confinement is due to both the friction and potential field induced by cholesterol and sphingolipids. Finally, the statistics of hopping energies reveal sub-structures of potentials in the rafts, characterized by small hopping energies, and the difference of solubilization energy between the inner and outer raft area, characterized by higher hopping energies.

    View details for DOI 10.1371/journal.pone.0053073

    View details for Web of Science ID 000313480000028

    View details for PubMedID 23301023

  • Receptor Displacement in the Cell Membrane by Hydrodynamic Force Amplification through Nanoparticles. Biophysical journal Türkcan, S., Richly, M. U., Bouzigues, C. I., Allain, J. M., Alexandrou, A. 2013; 105 (1): 116-26

    Abstract

    We introduce an intrinsically multiplexed and easy to implement method to apply an external force to a biomolecule and thus probe its interaction with a second biomolecule or, more generally, its environment (for example, the cell membrane). We take advantage of the hydrodynamic interaction with a controlled fluid flow within a microfluidic channel to apply a force. By labeling the biomolecule with a nanoparticle that acts as a kite and increases the hydrodynamic interaction with the fluid, the drag induced by convection becomes important. We use this approach to track the motion of single membrane receptors, the Clostridium perfringens ?-toxin (CP?T) receptors that are confined in lipid raft platforms, and probe their interaction with the environment. Under external force, we observe displacements over distances up to 10 times the confining domain diameter due to elastic deformation of a barrier and return to the initial position after the flow is stopped. Receptors can also jump over such barriers. Analysis of the receptor motion characteristics before, during, and after a force is applied via the flow indicates that the receptors are displaced together with their confining raft platform. Experiments before and after incubation with latrunculin B reveal that the barriers are part of the actin cytoskeleton and have an average spring constant of 2.5 ± 0.6 pN/?m before vs. 0.6 ± 0.2 pN/?m after partial actin depolymerization. Our data, in combination with our previous work demonstrating that the ?-toxin receptor confinement is not influenced by the cytoskeleton, imply that it is the raft platform and its constituents rather than the receptor itself that encounters and deforms the barriers formed by the actin cytoskeleton.

    View details for PubMedID 23823230

  • Observing the Confinement Potential of Bacterial Pore-Forming Toxin Receptors Inside Rafts with Nonblinking Eu3+-Doped Oxide Nanoparticles BIOPHYSICAL JOURNAL Tuerkcan, S., Masson, J., Casanova, D., Mialon, G., Gacoin, T., Boilot, J., Popoff, M. R., Alexandrou, A. 2012; 102 (10): 2299-2308

    Abstract

    We track single toxin receptors on the apical cell membrane of MDCK cells with Eu-doped oxide nanoparticles coupled to two toxins of the pore-forming toxin family: ?-toxin of Clostridium septicum and ?-toxin of Clostridium perfringens. These nonblinking and photostable labels do not perturb the motion of the toxin receptors and yield long uninterrupted trajectories with mean localization precision of 30 nm for acquisition times of 51.3 ms. We were thus able to study the toxin-cell interaction at the single-molecule level. Toxins bind to receptors that are confined within zones of mean area 0.40 ± 0.05 ?m(2). Assuming that the receptors move according to the Langevin equation of motion and using Bayesian inference, we determined mean diffusion coefficients of 0.16 ± 0.01 ?m(2)/s for both toxin receptors. Moreover, application of this approach revealed a force field within the domain generated by a springlike confining potential. Both toxin receptors were found to experience forces characterized by a mean spring constant of 0.30 ± 0.03 pN/?m at 37°C. Furthermore, both toxin receptors showed similar distributions of diffusion coefficient, domain area, and spring constant. Control experiments before and after incubation with cholesterol oxidase and sphingomyelinase show that these two enzymes disrupt the confinement domains and lead to quasi-free motion of the toxin receptors. Our control data showing cholesterol and sphingomyelin dependence as well as independence of actin depolymerization and microtubule disruption lead us to attribute the confinement of both receptors to lipid rafts. These toxins require oligomerization to develop their toxic activity. The confined nature of the toxin receptors leads to a local enhancement of the toxin monomer concentration and may thus explain the virulence of this toxin family.

    View details for DOI 10.1016/j.bpj.2012.03.072

    View details for Web of Science ID 000304091100009

    View details for PubMedID 22677383

  • A Bayesian Inference Scheme to Extract Diffusivity and Potential Fields from Confined Single-Molecule Trajectories BIOPHYSICAL JOURNAL Tuerkcan, S., Alexandrou, A., Masson, J. 2012; 102 (10): 2288-2298

    Abstract

    Currently used techniques for the analysis of single-molecule trajectories only exploit a small part of the available information stored in the data. Here, we apply a Bayesian inference scheme to trajectories of confined receptors that are targeted by pore-forming toxins to extract the two-dimensional confining potential that restricts the motion of the receptor. The receptor motion is modeled by the overdamped Langevin equation of motion. The method uses most of the information stored in the trajectory and converges quickly onto inferred values, while providing the uncertainty on the determined values. The inference is performed on the polynomial development of the potential and on the diffusivities that have been discretized on a mesh. Numerical simulations are used to test the scheme and quantify the convergence toward the input values for forces, potential, and diffusivity. Furthermore, we show that the technique outperforms the classical mean-square-displacement technique when forces act on confined molecules because the typical mean-square-displacement analysis does not account for them. We also show that the inferred potential better represents input potentials than the potential extracted from the position distribution based on Boltzmann statistics that assumes statistical equilibrium.

    View details for DOI 10.1016/j.bpj.2012.01.063

    View details for Web of Science ID 000304091100008

    View details for PubMedID 22677382

  • High Up-Conversion Efficiency of YVO4:Yb,Er Nanoparticles in Water down to the Single-Particle Level JOURNAL OF PHYSICAL CHEMISTRY C Mialon, G., Tuerkcan, S., Dantelle, G., Collins, D. P., Hadjipanayi, M., Taylor, R. A., Gacoin, T., Alexandrou, A., Boilott, J. 2010; 114 (51): 22449-22454

    View details for DOI 10.1021/jp107900z

    View details for Web of Science ID 000285447000011

  • Luminescent oxide nanoparticles with enhanced optical properties JOURNAL OF LUMINESCENCE Mialon, G., Poggi, M., Casanova, D., Nguyen, T., Tuerkcan, S., Alexandrou, A., Gacoin, T., Boilot, J. 2009; 129 (12): 1706-1710
  • New Insights into Size Effects in Luminescent Oxide Nanocrystals JOURNAL OF PHYSICAL CHEMISTRY C MIALON, G., Tuerkcan, S., Alexandrou, A., Gacoin, T., Boilot, J. 2009; 113 (43): 18699-18706

    View details for DOI 10.1021/jp907176x

    View details for Web of Science ID 000270911500039

  • Inferring Maps of Forces inside Cell Membrane Microdomains PHYSICAL REVIEW LETTERS Masson, J., Casanova, D., Tuerkcan, S., Voisinne, G., Popoff, M. R., VERGASSOLA, M., Alexandrou, A. 2009; 102 (4)

    Abstract

    Mapping of the forces on biomolecules in cell membranes has spurred the development of effective labels, e.g., organic fluorophores and nanoparticles, to track trajectories of single biomolecules. Standard methods use particular statistics, namely the mean square displacement, to analyze the underlying dynamics. Here, we introduce general inference methods to fully exploit information in the experimental trajectories, providing sharp estimates of the forces and the diffusion coefficients in membrane microdomains. Rapid and reliable convergence of the inference scheme is demonstrated on trajectories generated numerically. The method is then applied to infer forces and potentials acting on the receptor of the toxin labeled by lanthanide-ion nanoparticles. Our scheme is applicable to any labeled biomolecule and results show its general relevance for membrane compartmentation.

    View details for DOI 10.1103/PhysRevLett.102.048103

    View details for Web of Science ID 000262978600075

    View details for PubMedID 19257479

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