Additional file 2: Figure S2. of Automatic detection of diffusion modes within biological membranes using back-propagation neural network

- Comparison of the percentage of decision using the BPNN, Hidden Markov Modeling (HMM)-Bayes, Bayesian Information Criterion (BIC) or Support Vector Machines (SVM) algorithms. 200 simulated trajectories of 300 frames mimicking diffusion within plasma membranes, including one directed motion segment with velocity randomly ranging from 1 to 3 μm/s and one confinement segment with diameters ranging from 0.5 and 1.2 μm, were analyzed with BPPN, HMM-Bayes, BIC or SVM. Within a trajectory each 50 frames segment is always localized at the same position. The diffusion coefficient D is 0.25 μm2/s and the integration time 100 ms. A 30 nm localization noise Pn was added to the trajectory (see Material and Methods section). The percentage of decision based on BPNN corresponds to the number of positive decision for a specific motion mode detected for a given frame over 200 trajectories and normalized to 1 or-1 for confined (light grey) or directed (dark grey) trajectories, respectively. The HMM-Bayes and the BIC algorithms can only detect directed or confined segments within a trajectory, respectively. The tables at the bottom detail the performance of the 4 algorithms in terms of sensitivity and specificity for detecting confined and directed motion modes in the range of parameters tested in this study (D = 0.25 μm2/s, 1 μm/s < v < 3 μm/s, 0.5 μm < L < 1.2 μm). (PDF 400 kb

Characterization of Phospholipid Bilayer Formation on a Thin Film of Porous SiO₂ by Reflective Interferometric Fourier Transform Spectroscopy (RIFTS)

Classical methods for characterizing supported artificial phospholipid bilayers include imaging techniques such as atomic force microscopy and fluorescence microscopy. The use in the past decade of surface-sensitive methods such as surface plasmon resonance and ellipsometry, and acoustic sensors such as the quartz crystal microbalance, coupled to the imaging methods, have expanded our understanding of the formation mechanisms of phospholipid bilayers. In the present work, reflective interferometric Fourier transform spectrocopy (RIFTS) is employed to monitor the formation of a planar phospholipid bilayer on an oxidized mesoporous Si (pSiO₂) thin film. The pSiO₂ substrates are prepared as thin films (3 μm thick) with pore dimensions of a few nanometers in diameter by the electrochemical etching of crystalline silicon, and they are passivated with a thin thermal oxide layer. A thin film of mica is used as a control. Interferometric optical measurements are used to quantify the behavior of the phospholipids at the internal (pores) and external surfaces of the substrates. The optical measurements indicate that vesicles initially adsorb to the pSiO₂ surface as a monolayer, followed by vesicle fusion and conversion to a surface-adsorbed lipid bilayer. The timescale of the process is consistent with prior measurements of vesicle fusion onto mica surfaces. Reflectance spectra calculated using a simple double-layer Fabry–Perot interference model verify the experimental results. The method provides a simple, real-time, nondestructive approach to characterizing the growth and evolution of lipid vesicle layers on the surface of an optical thin film

Interaction of Antibiotics with Lipid Vesicles on Thin Film Porous Silicon Using Reflectance Interferometric Fourier Transform Spectroscopy

The ability to observe interactions of drugs with cell membranes is an important area in pharmaceutical research. However, these processes are often difficult to understand due to the dynamic nature of cell membranes. Therefore, artificial systems composed of lipids have been used to study membrane properties and their interaction with drugs. Here, lipid vesicle adsorption, rupture, and formation of planar lipid bilayers induced by various antibiotics (surfactin, azithromycin, gramicidin, melittin and ciprofloxacin) and the detergent dodecyl-<i>b</i>-d-thiomaltoside (DOTM) was studied using reflective interferometric Fourier transform spectroscopy (RIFTS) on an oxidized porous silicon (pSi) surface as a transducer. The pSi transducer surfaces are prepared as thin films of 3 μm thickness with pore dimensions of a few nanometers in diameter by electrochemical etching of crystalline silicon followed by passivation with a thermal oxide layer. Furthermore, the sensitivity of RIFTS was investigated using three different concentrations of surfactin. Complementary techniques including atomic force microscopy, fluorescence recovery after photobleaching, and fluorescence microscopy were used to validate the RIFTS-based method and confirm adsorption and consequent rupture of vesicles to form a phospholipid bilayer upon the addition of antibiotics. The method provides a sensitive and real-time approach to monitor the antibiotic-induced transition of lipid vesicles to phospholipid bilayers

Mimicking Influenza Virus Fusion Using Supported Lipid Bilayers

Influenza virus infection is a serious public health problem in the world, and understanding the molecular mechanisms involved in viral replication is crucial. In this paper, we used a minimalist approach based on a lipid bilayer supported on mica, which we imaged by atomic force microscopy (AFM) in a physiological buffer, to analyze the different steps of influenza fusion, from the interaction of intact viruses with the supported bilayer to their complete fusion. Our results show that sialic acid recognition and priming upon acidification are sufficient for a complete fusion with the host cell membrane. After fusion, a flat and continuous membrane was observed. Because of the fragility of the viral membrane that was removed by the tip, most probably due to the disorganization of the matrix layer at acidic pH, fine structural details of ribonucleoproteins (RNP) were obtained. In addition, AFM topography of intact virus in interaction with the supported lipid bilayer confirms that hemeagglutinin and neuraminidase can form isolated clusters within the viral membrane

(A) Distribution of the ADC of CD9, CD55, and CD46 treated or not treated with MβCD (∼50% of the membrane Chl was removed)

CD55 is a raft marker, and CD46 is excluded from rafts and TEAs. Mean values of ADC of all the molecules are available in . (B) Comparison of trajectories (thin white lines) in living PC3 cells before (left) or after (right) MβCD treatment. Bars, 7.5 μm.<p><b>Copyright information:</b></p><p>Taken from "Single-molecule analysis of CD9 dynamics and partitioning reveals multiple modes of interaction in the tetraspanin web"</p><p></p><p>The Journal of Cell Biology 2008;182(4):765-776.</p><p>Published online 25 Aug 2008</p><p>PMCID:PMC2518714.</p><p></p

(left) ADC distribution of CD9 in control cells (CD9), cells treated with MβCD (CD9 MβCD), cells treated with MβCD loaded with Chl (CD9 MβCD–Chl), or cells transfected with nonpalmitoylated CD9 (CD9)

50% of the membrane Chl was removed by MβCD treatment, and MβCD–Chl treatment increased the Chl content to 130% as compared with control cells. All of the palmitoylation sites have been mutated in CD9 cells. (right) Histograms (open boxes) representing the percentage of each diffusion mode of the molecules as compared with the total number of trajectories (B, Brownian; C, confined; M, mixed). The gray part corresponds to the proportion of trajectories associated with TEAs (identified with the ensemble membrane labeling) for each diffusion mode.<p><b>Copyright information:</b></p><p>Taken from "Single-molecule analysis of CD9 dynamics and partitioning reveals multiple modes of interaction in the tetraspanin web"</p><p></p><p>The Journal of Cell Biology 2008;182(4):765-776.</p><p>Published online 25 Aug 2008</p><p>PMCID:PMC2518714.</p><p></p

(A) ADC distribution and mean value (±SD) of CD55 molecules labeled with Atto647N-conjugated mAb 12A12

D is the mean value of the ADC calculated from a linear fit of the MSD-τ plot, and the dashed line delineates two different populations corresponding to pure confined trajectories (lower ADC) or mixed and Brownian trajectories. (B) Histograms (open boxes) representing the percentage of each CD55 diffusion mode as compared with the total number of trajectories. The gray part corresponds to the proportion of trajectories associated with TEAs (identified with the ensemble membrane labeling) for each diffusion mode (B, Brownian; C, confined; M, mixed). Compare with . (C) Trajectories of a single CD55 molecule. The inset is a magnification of the transient confinement area delineated by the boxed area.<p><b>Copyright information:</b></p><p>Taken from "Single-molecule analysis of CD9 dynamics and partitioning reveals multiple modes of interaction in the tetraspanin web"</p><p></p><p>The Journal of Cell Biology 2008;182(4):765-776.</p><p>Published online 25 Aug 2008</p><p>PMCID:PMC2518714.</p><p></p

(A) Immunoprecipitation experiments in WT PC3 cells or in cells overexpressing CD9 (PC3/CD9) or a nonpalmitoylated form of CD9 (PC3/CD9)

Biotin-labeled cells were lysed in Brij97 and incubated with anti-CD9, anti-CD81, or anti-α5 antibodies (the latter is used as a negative control). Immunoprecipitated proteins were detected using peroxidase-coupled streptavidin. (B) Immunofluorescence images of PC3/CD9 living cell basal membrane by TIRF microscopy at 37°C. Cells were incubated with the anti-CD9 Cy3B-conjugated antibody SYB-1 (middle; green in the merge image) and with various antibodies labeled with Atto647N (left; red in the merge images) and raised against (top to bottom) CD81, CD9P-1, the α5 chain of integrin, CD55, or CD46. Bars, 10 μm.<p><b>Copyright information:</b></p><p>Taken from "Single-molecule analysis of CD9 dynamics and partitioning reveals multiple modes of interaction in the tetraspanin web"</p><p></p><p>The Journal of Cell Biology 2008;182(4):765-776.</p><p>Published online 25 Aug 2008</p><p>PMCID:PMC2518714.</p><p></p

(A) Time lapse showing a simultaneous single-molecule tracking of two differentially labeled CD9 molecules with a Fab fragment conjugated with Atto647N (red) or with Cy3B (green); see Video 2 (available at )

(B) Representative trajectory of CD9 dynamic colocalization. The parts of trajectories where the fluorescence signal of two particles overlap at least for one pixel (160 nm) are encircled in gray and magnified in the ellipse underneath (colored arrows indicate the trajectory direction). (C) Quantitative analysis of single-molecule colocalization. Two particles were considered spatially colocalized when at least one pixel of their fluorescence signals was overlapped during at least seven frames corresponding to 700 ms (the two molecules were colocalized during 24 frames in the time lapse shown in A). Different combinations of proteins were tested: CD9/CD9 on cells treated or not treated with MβCD, CD9/CD9, and irrelevant pairs such as CD9/CD55, CD55/CD55, and CD46/CD46.<p><b>Copyright information:</b></p><p>Taken from "Single-molecule analysis of CD9 dynamics and partitioning reveals multiple modes of interaction in the tetraspanin web"</p><p></p><p>The Journal of Cell Biology 2008;182(4):765-776.</p><p>Published online 25 Aug 2008</p><p>PMCID:PMC2518714.</p><p></p