7.胃管アレルギーに於ける腸粘膜スメアーの研究(第二報)(第415回千葉医学会例会,第63回日本小児科学会千葉地方会総会)

Extended representative data set of lysosomal positioning. (a) Schematic representation of the feature “MAX Contour Position” used to quantify lysosomal positioning. (b) Representative LAMP1 immunofluorescence images for different ranges of the feature “LAMP1 MAX Contour Position” in HeLa cells treated as in Fig. 6. (JPG 3911 kb

Sensitivity analysis of the full model.

<p>(A) Effect of parameters perturbation on the full model. Bar graph represents Partial Rank Correlation Coefficient values for each parameter-output response pairing resulting from a Latin-hypercube sampling of 500 parameter value sets (parameter ranges are described in section “Energetic sensing, mitophagy and mitochondrial biogenesis are integrated processes”). For each parameter set the model was performed over 24 hours. (B) Results of the eFast method used to partition variance in simulation results between parameters. Solid Bars: sensitivity index (Si)–the fraction of output variance explained by the value assigned to that parameter when parameter of interest; Dashed Bars: total sensitivity index (STi)–the variance caused by higher-order non-linear effects between that parameter and the other explored (includes value of Si). Error bars are standard error over four resample curves. Parameter values sets were generated using the sinusoidal sampling approach. 65 parameters were obtained from each of the 4 resampling curves, producing 3120 parameter value sets (260 per parameter).</p

Sensitivity analysis of the transmission dynamics model.

<p>(A) Effect of parameters perturbation on transmission dynamic. Bar graph represents Partial Rank Correlation Coefficient values for each parameter-output response pairing resulting from a Latin-hypercube sampling of 500 parameter value sets (parameter ranges are described in section “Transmission dynamics of mitochondrial network connectivity”). For each parameter set the model was performed over 6 hours. (B) Results of the eFast method used to partition variance in simulation results between parameters. Solid Bars: sensitivity index (Si)–the fraction of output variance explained by the value assigned to that parameter when parameter of interest; Dashed Bars: total sensitivity index (STi)–the variance caused by higher-order non-linear effects between that parameter and the other explored (includes value of Si). Error bars are standard error over four resample curves. Parameter values sets were generated using the sinusoidal sampling approach. 65 parameters were obtained from each of the 4 resampling curves, producing 2080 parameter value sets (260 per parameter).</p

In silico photoactivation to quantify transmission dynamics in mitochondrial networks.

<p>(A) Schematic representation of an <i>in silico</i> photoactivation. 10% of mitochondrial mass is assigned a GFP label, which transmit through the cell upon a fusion event: fusion of a mitochondrion with a GFP-labeled mitochondrion, results in a parent GFP-labeled mitochondrion, which upon fission results in two GFP-labeled daughter mitochondria. (B) Transmission dynamic of photoactivated GFP across the mitochondria population moving with free motion (ϑ₁ ϵ [0°, 360°]), starting from 10% of labeled mitochondria (green). Simulations were performed with total mitochondrial masses of 100 and 300 and three different fusion/fission probability rates: F_p/f_p = 20%/80% (dotted line), F_p/f_p = 50%/50% (solid line) and F_p/f_p = 80%/20% (dashed line). 100 simulations were performed each and plots represent the average values normalized to the total mass at time point 0. Blue regions indicate the time to 50% network transmission with fusion/fission probability rates of 50%/50%. (C) Same as (B) but with restricted movement, ϑ₁ ϵ [0°, 10°]. Pink regions indicate the time to 50% network transmission with fusion/fission probability rates of 50%/50%. (D) Effect of the mitochondria mobility on transmission dynamics in the case of free movement (blue circles, line) and restricted movement (pink triangles, line). Detailed representation of the time needed to the GFP labeled mitochondrial population to exceed the unlabeled population for an initial total mitochondrial mass of 300 with a fixed fusion/fission probability rate of 50%/50% and three different velocities: v_l ϵ [0, 0.44] μms^-1, v_h ϵ [0, 1] μms^-1 and v, equal to v_l in the perinuclear region and to v_h outside.</p

Impact of fusion and fission probabilities and mitochondrial mass on mitochondrial subpopulations.

<p>(A) Time course response of mitochondrial subpopulations for low total mass (<i>M</i> = 100; 5% of the whole cell area). Three mitochondrial subpopulations are considered: small mass (orange line), medium mass (blue line) and large mass (green line). The partial mass reports the sum of the masses from all mitochondria in a given subpopulation divided by the total mitochondrial mass. Lines display the mean among 100 simulations, and shaded regions display the standard deviation. Small graphs underneath show the evolution of the first derivative of mitochondria with large mass (green line). Three different fusion/fission probability rates are used: 20%/80%, 50%/50% and 80%/20%. Pie charts report the partial mass (in terms of percentages) for the subpopulations at the final simulation time (2 hours). (B) Same as (A) but with a total mitochondrial mass of 200 (10% of the whole cell area). (C) Same as (A) but with a total mitochondrial mass of 300 (15% of the whole cell area).</p

Integration of mitochondrial damage sensing and mitophagy through parameter fitting.

<p>(A) Schematic representation of mitochondrial fusion and fission cycles, damage and mitochondrial degradation events. Degradation is represented by frequency (D_f) parameter and damage (d_T) and receptor (MR_T) thresholds. (B) Basic flow chart of the model representing fusion, fission, biogenesis and degradation events. Shaded boxes indicate the main processes of the model (fusion, fission, biogenesis, <i>low/high</i> damage, degradation and increments). Time step used in all the simulation, Δt = 1 sec. (C) Spatial model representation. Highly-damaged mitochondria are represented in black and mitochondria with low damage in brown. The yellow circle indicates an autolysosome and the black circle and semicircle indicate stages of autophagosome formation. (D) Maximization of the fitness function O_D within 100 iterations, reaching a value of -0.02, using a classic genetic algorithm. Algorithm (settings described in the Methods section). (E) Mean of 100 simulations of degradation of damaged mitochondria over 24 hours, beginning with 50% <i>low</i> damaged and 50% <i>high</i> damaged mitochondria and using the parameters obtained from the optimization (D), receptor threshold = 12 minutes, damage threshold = 12.4 minutes and degradation frequency = 5.7 minutes. The initial total mass consists of two equal parts of high-damaged and low-damaged mitochondria.</p

An agent-based model of mitochondrial dynamics determined by organelle mobility and fusion-fission cycles.

<p>(A) Model representation. The model consists of a two-dimensional grid (elements of 1 μm × 1 μm) in which the cell is represented by a circle with a diameter of 50 μm, and a nucleus with a diameter of 16.6 μm. The dashed circle (diameter, 25 μm) divides the cell in two regions, perinuclear (red arrow) and cytosolic (blue arrow), with different mitochondrial mobility. The mitochondrial population consists of agents with masses ranging continuously from a minimum value M_min of 0.5 μm² to a maximum value Mmax of 3 μm². The mitochondria population is in turn subdivided into three groups: small (mass smaller or equal 1 μm², orange), medium (mass between 1 μm² and 2 μm², blue) and large (mass greater than 2 μm², green). (B) Schematic describing mitochondrial dynamics, consisting of fusion (<i>f</i>) and fission (<i>F</i>) cycles occurring with temporal frequencies (f_f, F_f) of minutes. Mitochondria of all masses are able to undergo fusion and fission events according to fusion and fission probabilities (f_p, F_p). Time step used in all the simulation, Δt = 1sec. (C) Schematic describing mitochondrial movement and unfeasible actions. Each mitochondrion checks, with an internal control, the surrounding area with a radius of 1.0 μm in order to avoid unfeasible actions such as moving outside the cell or inside the nucleus and overlapping other mitochondria. If the area is free, the mitochondrion first move one step forward, with a velocity <i>v</i>, and than rotates by a random angle ϑ₁ ϵ [0°, 360°]. If the mitochondrion encounters either another mitochondrion (and no fusion occur), the nucleus, or the cell border, the mitochondrion rotates by a random angle ϑ₂ ϵ[0°, 90°]. (D) Basic flow chart of the model representing the fusion-fission cycle and main components of the model. Shaded boxes indicate the main processes of the model (fusion and fission) with the respective governing equations.</p

Impact of mitochondrial directionality on mitochondrial mass subpopulation distributions.

<p>(A) Mitochondrial movements are indicated by projecting 25 images, one every 100 time steps, representing a total of ~40 minutes of a simulation. Time points are indicated according to color-code. Line graphs display mean values and standard deviation (shaded regions) of 100 simulations for mitochondrial population with free movement. The initial mass value was fixed to 300 and the angle ϑ₁ ϵ [0°, 360°]. The plot represents the evolution of three mitochondrial subpopulations, small mass (orange line), medium mass (blue line) and large mass (green line), normalized to the total mass at time point 0. Small graphs underneath show the evolution of the first derivative of mitochondria with large mass (green line). The simulations were performed for a total time of 2 hours. (B) Same as (A) but with restricted movement, ϑ₁ ϵ [0°, 10°].</p

Interaction between mitochondrial health and cellular energetic state, based on the energetic stress.

<p>(A) Evolution of mitochondrial mass (grey lines) over time subjected to four different damage signals (black line). Line graphs display mean value and standard deviation (shaded regions) of 100 simulations for an initial total mitochondrial mass of 300 normalized to the total mass at time point 0. Parameter values obtained from the optimization were used, in particular, fusion probability = fission probability = 50%, fusion frequency = fission frequency = 5 minutes, biogenesis probability = 22.1%, biogenesis frequency = 28.9 minutes, receptor threshold = 12 minutes, damage threshold = 12.4 minutes, degradation frequency = 5.7 minutes and damage probabilities: 0%, 10%, 30% and 50%. Simulations were performed for a total of 12 hours. Blue region indicates the area in which biogenesis is dominant while red region indicates the area in which degradation is dominant. (B) Schematic representation of the link between the number of healthy and damaged mitochondria with the energetic stress (E_S) of the cell. (C) Schematic representation of the connection between energetic (red line) stress and fission (dark green line) and biogenesis (orange line) probabilities. (D) Line graphs display mean value and standard deviation (shaded regions) of 100 simulations of probabilities of fusion (dark green line), fission (light green line), biogenesis (orange line) and damage signal (black line). Initial values assigned to the model: fusion probability = fission probability = 50%, fusion frequency = fission frequency = 5 minutes, biogenesis probability = 22.1%, biogenesis frequency = 28.9 minutes, receptor threshold = 12 minutes, damage threshold = 12.4 minutes, degradation frequency = 5.7 minutes. All the simulations were performed for a total time of 24 hours. (E) Line graphs display mean value and standard deviation (shaded area) of 100 simulations for an initial mitochondrial mass of 300 of the total mitochondrial mass (grey line) and three mitochondria subpopulations: small mass (orange line), medium mass (blue line) and big mass (green line) subjected to five different damage signals (10% and 20%) every two hours for one hour. The plot represents the evolution of the total mass and of three mitochondrial subpopulations normalized to the total mass at time point 0. Initial values assigned to the model: fusion probability = fission probability = 50%, fusion frequency = fission frequency = 5 minutes, biogenesis probability = 22.1%, biogenesis frequency = 28.9 minutes, receptor threshold = 12 minutes, damage threshold = 12.4 minutes, degradation frequency = 5.7 minutes. All the simulations were performed for a total time of 24 hours. (F) Line graphs display mean value and standard deviation (shaded regions) of 100 simulations of bioenergetics stress (red line). Initial values assigned to the model: fusion probability = fission probability = 50%, fusion frequency = fission frequency = 5 minutes, biogenesis probability = 22.1%, biogenesis frequency = 28.9 minutes, receptor threshold = 12 minutes, damage threshold = 12.4 minutes, degradation frequency = 5.7 minutes. All the simulations were performed for a total time of 24 hours. (G) Same as (D) but with mitochondria subjected to five different damage signals (40%) every two hours for one hour. (H) Same as (E) but with mitochondria subjected to five different damage signals (40%) every two hours for one hour. (I) Same as (F) but with mitochondria subjected to five different damage signals (40%) every two hours for one hour.</p

Integration of mitochondrial biogenesis through parameter fitting.

<p>(A) Schematic representation of mitochondrial fusion, fission and biogenesis events. Biogenesis is represented by frequency (B_f) and probability (B_p) parameters, and can occur in all mitochondria with a mass less than M_max = 3.0 μm². (B) Basic flow chart of the model representing fusion, fission and biogenesis events. Shaded boxes indicate the main processes of the model (fusion, fission and biogenesis) with governing equation of the biogenesis process. Time step used in all the simulation, Δt = 1 sec. (C) Maximization of the fitness function O_B within 100 iterations, reaching a value of -0.049, using a classic genetic algorithm (settings described in the Methods section). (D) Mean of 100 simulations of mitochondrial mass growth over 48 hours, beginning with a mitochondrial mass of 1 and using the parameter values obtained from the optimization (C), biogenesis probability = 22.1% and biogenesis frequency = 28.9 minutes.</p