Bayesian traction force estimation using cell boundary-dependent force priors

Understanding the principles of cell migration necessitates measurements of the forces generated by cells. In traction force microscopy (TFM), fluorescent beads are placed on a substrate's surface and the substrate strain caused by the cell traction force is observed as displacement of the beads. Mathematical analysis can estimate traction force from bead displacement. However, most algorithms estimate substrate stresses independently of cell boundary, which results in poor estimation accuracy in low-density bead environments. To achieve accurate force estimation at low density, we proposed a Bayesian traction force estimation (BTFE) algorithm that incorporates cell-boundary-dependent force as a prior. We evaluated the performance of the proposed algorithm using synthetic data generated with mathematical models of cells and TFM substrates. BTFE outperformed other methods, especially in low-density bead conditions. In addition, the BTFE algorithm provided a reasonable force estimation using TFM images from the experiment.

A hybrid in silico/in-cell controller for microbial bioprocesses with process-model mismatch

Bioprocess optimization using mathematical models is prevalent, yet the discrepancy between model predictions and actual processes, known as process-model mismatch (PMM), remains a significant challenge. This study proposes a novel hybrid control system called the hybrid in silico/in-cell controller (HISICC) to address PMM by combining model-based optimization (in silico feedforward controller) with feedback controllers utilizing synthetic genetic circuits integrated into cells (in-cell feedback controller). We demonstrated the efficacy of HISICC using two engineered Escherichia coli strains, TA1415 and TA2445, previously developed for isopropanol (IPA) production. TA1415 contains a metabolic toggle switch (MTS) to manage the competition between cell growth and IPA production for intracellular acetyl-CoA by responding to external input of isopropyl β-D-1-thiogalactopyranoside (IPTG). TA2445, in addition to the MTS, has a genetic circuit that detects cell density to autonomously activate MTS. The combination of TA2445 with an in silico controller exemplifies HISICC implementation. We constructed mathematical models to optimize IPTG input values for both strains based on the two-compartment model and validated these models using experimental data of the IPA production process. Using these models, we evaluated the robustness of HISICC against PMM by comparing IPA yields with two strains in simulations assuming various magnitudes of PMM in cell growth rates. The results indicate that the in-cell feedback controller in TA2445 effectively compensates for PMM by modifying MTS activation timing. In conclusion, the HISICC system presents a promising solution to the PMM problem in bioprocess engineering, paving the way for more efficient and reliable optimization of microbial bioprocesses.

Decoding cellular deformation from pseudo-simultaneously observed Rho GTPase activities

Limitations in simultaneously observing the activity of multiple molecules in live cells prevent researchers from elucidating how these molecules coordinate the dynamic regulation of cellular functions. Here, we propose the motion-triggered average (MTA) algorithm to characterize pseudo-simultaneous dynamic changes in arbitrary cellular deformation and molecular activities. Using MTA, we successfully extract a pseudo-simultaneous time series from individually observed activities of three Rho GTPases: Cdc42, Rac1, and RhoA. To verify that this time series encoded information on cell-edge movement, we use a mathematical regression model to predict the edge velocity from the activities of the three molecules. The model accurately predicts the unknown edge velocity, providing numerical evidence that these Rho GTPases regulate edge movement. Data preprocessing using MTA combined with mathematical regression provides an effective strategy for reusing numerous individual observations of molecular activities.

Analyses of Actin Dynamics, Clutch Coupling and Traction Force for Growth Cone Advance

To establish functional networks, neurons must migrate to their appropriate destinations and then extend axons toward their target cells. These processes depend on the advances of growth cones that located at the tips of neurites. Axonal growth cones generate driving forces by sensing their local microenvironment and modulating cytoskeletal dynamics and actin-adhesion coupling (clutch coupling). Decades of research have led to the identification of guidance molecules, their receptors, and downstream signaling cascades for regulating neuronal migration and axonal guidance; however, the molecular machineries required for generating forces to drive growth cone advance and navigation are just beginning to be elucidated. At the leading edge of neuronal growth cones, actin filaments undergo retrograde flow, which is powered by actin polymerization and actomyosin contraction. A clutch coupling between F-actin retrograde flow and adhesive substrate generates traction forces for growth cone advance. The present study describes a detailed protocol for monitoring F-actin retrograde flow by single speckle imaging. Importantly, when combined with an F-actin marker Lifeact, this technique can quantify 1) the F-actin polymerization rate and 2) the clutch coupling efficiency between F-actin retrograde flow and the adhesive substrate. Both are critical variables for generating forces for growth cone advance and navigation. In addition, the present study describes a detailed protocol of traction force microscopy, which can quantify 3) traction force generated by growth cones. Thus, by coupling the analyses of single speckle imaging and traction force microscopy, investigators can monitor the molecular mechanics underlying growth cone advance and navigation.

Basic Proline-Rich Protein-Mediated Microtubules Are Essential for Lobe Growth and Flattened Cell Geometry

Complex cell shapes are generated first by breaking symmetry, and subsequent polar growth. Localized bending of anticlinal walls initiates lobe formation in the epidermal pavement cells of cotyledons and leaves, but how the microtubule cytoskeleton mediates local cell growth, and how plant pavement cells benefit from adopting jigsaw puzzle-like shapes, are poorly understood. In Arabidopsis (Arabidopsis thaliana), the basic Pro-rich protein (BPP) microtubule-associated protein family comprises seven members. We analyzed lobe morphogenesis in cotyledon pavement cells of a BPP1;BPP2;BPP5 triple knockout mutant. New image analysis methods (MtCurv and BQuant) showed that anticlinal microtubule bundles were significantly reduced and cortical microtubules that fan out radially across the periclinal wall did not enrich at the convex side of developing lobes. Despite these microtubule defects, new lobes were initiated at the same frequency as in wild-type cells, but they did not expand into well-defined protrusions. Eventually, mutant cells formed nearly polygonal shapes and adopted concentric microtubule patterns. The mutant periclinal cell wall bulged outward. The radius of the calculated inscribed circle of the pavement cells, a proposed proxy for maximal stress in the cell wall, was consistently larger in the mutant cells during cotyledon development, and correlated with an increase in cell height. These bpp mutant phenotypes provide genetic and cell biological evidence that initiation and growth of lobes are distinct morphogenetic processes, and that interdigitated cell geometry effectively suppresses large outward bulging of pavement cells.

Sensing of substratum rigidity and directional migration by fast-crawling cells

Living cells sense the mechanical properties of their surrounding environment and respond accordingly. Crawling cells detect the rigidity of their substratum and migrate in certain directions. They can be classified into two categories: slow-moving and fast-moving cell types. Slow-moving cell types, such as fibroblasts, smooth muscle cells, mesenchymal stem cells, etc., move toward rigid areas on the substratum in response to a rigidity gradient. However, there is not much information on rigidity sensing in fast-moving cell types whose size is ∼10 μm and migration velocity is ∼10 μm/min. In this study, we used both isotropic substrata with different rigidities and an anisotropic substratum that is rigid on the x axis but soft on the y axis to demonstrate rigidity sensing by fast-moving Dictyostelium cells and neutrophil-like differentiated HL-60 cells. Dictyostelium cells exerted larger traction forces on a more rigid isotropic substratum. Dictyostelium cells and HL-60 cells migrated in the "soft" direction on the anisotropic substratum, although myosin II-null Dictyostelium cells migrated in random directions, indicating that rigidity sensing of fast-moving cell types differs from that of slow types and is induced by a myosin II-related process.

Fast-crawling cell types migrate to avoid the direction of periodic substratum stretching

To investigate the relationship between mechanical stimuli from substrata and related cell functions, one of the most useful techniques is the application of mechanical stimuli via periodic stretching of elastic substrata. In response to this stimulus, Dictyostelium discoideum cells migrate in a direction perpendicular to the stretching direction. The origins of directional migration, higher migration velocity in the direction perpendicular to the stretching direction or the higher probability of a switch of migration direction to perpendicular to the stretching direction, however, remain unknown. In this study, we applied periodic stretching stimuli to neutrophil-like differentiated HL-60 cells, which migrate perpendicular to the direction of stretch. Detailed analysis of the trajectories of HL-60 cells and Dictyostelium cells obtained in a previous study revealed that the higher probability of a switch of migration direction to that perpendicular to the direction of stretching was the main cause of such directional migration. This directional migration appears to be a strategy adopted by fast-crawling cells in which they do not migrate faster in the direction they want to go, but migrate to avoid a direction they do not want to go.

Experimental comparison of classification methods for key kinase identification for neurite elongation

Kinases in a developing neuron play important roles in elongating a neurite with their complex interactions. To elucidate the effect of each kinase on neurite elongation and regeneration from a small set of experiments, we applied machine learning methods to synthetic datasets based on a biologically feasible model. The result showed the ridged partial least squares (RPLS) algorithm performed better than other standard algorithms such as naive Bayes classifier, support vector machines and random forest classification. This suggests the effectiveness of dimension reduction done in RPLS.

A single-molecule approach to DNA replication in Escherichia coli cells demonstrated that DNA polymerase III is a major determinant of fork speed

The replisome catalyses DNA synthesis at a DNA replication fork. The molecular behaviour of the individual replisomes, and therefore the dynamics of replication fork movements, in growing Escherichia coli cells remains unknown. DNA combing enables a single-molecule approach to measuring the speed of replication fork progression in cells pulse-labelled with thymidine analogues. We constructed a new thymidine-requiring strain, eCOMB (E. coli for combing), that rapidly and sufficiently incorporates the analogues into newly synthesized DNA chains for the DNA-combing method. In combing experiments with eCOMB, we found the speed of most replication forks in the cells to be within the narrow range of 550-750 nt s(-1) and the average speed to be 653 ± 9 nt s(-1) (± SEM). We also found the average speed of the replication fork to be only 264 ± 9 nt s(-1) in a dnaE173-eCOMB strain producing a mutant-type of the replicative DNA polymerase III (Pol III) with a chain elongation rate (300 nt s(-1) ) much lower than that of the wild-type Pol III (900 nt s(-1) ). This indicates that the speed of chain elongation by Pol III is a major determinant of replication fork speed in E. coli cells.

Dynamic regulation of myosin light chain phosphorylation by Rho-kinase

Myosin light chain (MLC) phosphorylation plays important roles in various cellular functions such as cellular morphogenesis, motility, and smooth muscle contraction. MLC phosphorylation is determined by the balance between activities of Rho-associated kinase (Rho-kinase) and myosin phosphatase. An impaired balance between Rho-kinase and myosin phosphatase activities induces the abnormal sustained phosphorylation of MLC, which contributes to the pathogenesis of certain vascular diseases, such as vasospasm and hypertension. However, the dynamic principle of the system underlying the regulation of MLC phosphorylation remains to be clarified. Here, to elucidate this dynamic principle whereby Rho-kinase regulates MLC phosphorylation, we developed a mathematical model based on the behavior of thrombin-dependent MLC phosphorylation, which is regulated by the Rho-kinase signaling network. Through analyzing our mathematical model, we predict that MLC phosphorylation and myosin phosphatase activity exhibit bistability, and that a novel signaling pathway leading to the auto-activation of myosin phosphatase is required for the regulatory system of MLC phosphorylation. In addition, on the basis of experimental data, we propose that the auto-activation pathway of myosin phosphatase occurs in vivo. These results indicate that bistability of myosin phosphatase activity is responsible for the bistability of MLC phosphorylation, and the sustained phosphorylation of MLC is attributed to this feature of bistability.

The period of the somite segmentation clock is sensitive to Notch activity

The number of vertebrae is defined strictly for a given species and depends on the number of somites, which are the earliest metameric structures that form in development. Somites are formed by sequential segmentation. The periodicity of somite segmentation is orchestrated by the synchronous oscillation of gene expression in the presomitic mesoderm (PSM), termed the "somite segmentation clock," in which Notch signaling plays a crucial role. Here we show that the clock period is sensitive to Notch activity, which is fine-tuned by its feedback regulator, Notch-regulated ankyrin repeat protein (Nrarp), and that Nrarp is essential for forming the proper number and morphology of axial skeleton components. Null-mutant mice for Nrarp have fewer vertebrae and have defective morphologies. Notch activity is enhanced in the PSM of the Nrarp(-/-) embryo, where the ~2-h segmentation period is extended by 5 min, thereby forming fewer somites and their resultant vertebrae. Reduced Notch activity partially rescues the Nrarp(-/-) phenotype in the number of somites, but not in morphology. Therefore we propose that the period of the somite segmentation clock is sensitive to Notch activity and that Nrarp plays essential roles in the morphology of vertebrae and ribs.

A diffusion-based neurite length-sensing mechanism involved in neuronal symmetry breaking

Shootin1, one of the earliest markers of neuronal symmetry breaking, accumulates in the neurite tips of polarizing neurons in a neurite length-dependent manner. Thus, neurons sense their neurites' length and translate this spatial information into a molecular signal, shootin1 concentration.

Quantitative live cell imaging of shootin1 dynamics combined with mathematical modeling analyses reveals that its anterograde transport and retrograde diffusion in neurite shafts account for the neurite length-dependent accumulation of shootin1.

The neurite length-dependent shootin1 accumulation and shootin1-induced neurite outgrowth constitute a positive feedback loop that amplifies stochastic shootin1 signals in neurite tips.

Quantitative mathematical modeling shows that the above positive feedback loop, together with shootin1 upregulation, constitutes a core mechanism for neuronal symmetry breaking.

Cell morphology and size must be properly controlled to ensure cellular function. Although there has been significant progress in understanding the molecular signals that change cell morphology, the manner in which cells monitor their size and length to regulate their morphology is poorly understood. Cultured hippocampal neurons polarize by forming a single long axon and multiple short dendrites (Craig and Banker, 1994; Arimura and Kaibuchi, 2007), and symmetry breaking is the initial step of this process. This symmetry-breaking step reproduces even when the neuronal axon is transected; the longest neurite usually grows rapidly to become an axon after transection, regardless of whether it is the axonal stump or another neurite (Goslin and Banker, 1989). Elongation of an immature neurite by mechanical tension also leads to its axonal specification (Lamoureux et al, 2002). These results suggest that cultured hippocampal neurons can sense neurite length, identify the longest one, and induce its subsequent axonogenesis for symmetry breaking. However, little is known about the mechanism for this process.

Shootin1 is one of the earliest markers of neuronal symmetry breaking (Toriyama et al, 2006). During the symmetry-breaking step, it undergoes a stochastic accumulation in neurite tips, and eventually accumulates predominantly in a single neurite that subsequently grows to become an axon. In this study, we demonstrated that shootin1 accumulates in neurite tips in a neurite length-dependent manner, regardless of whether it is the axonal stump or another neurite (Figure 3A, C–F). Thus, morphological information (neurite length) is translated into a molecular signal (shootin1 concentration in neurite tips).

We previously reported that shootin1 is transported from the cell body to neurite tips as discrete boluses and diffuses back to the cell body (Toriyama et al, 2006). The boluses containing variable amounts of shootin1 traveled repeatedly but irregularly along neurites, and their arrival caused large stochastic fluctuations in shootin1 concentration in the neurite tips. To understand the mechanism of length-dependent shootin1 accumulation, we performed quantitative live cell imaging of the anterograde transport and retrograde diffusion of shootin1 and fitted the obtained data into mathematical models of the anterograde transport and retrograde diffusion. The parameters of these two models were derived entirely from quantitative experimental data, without any adjustment. Shootin1 concentration at neurite tips, calculated by integrating the two models, was neurite length dependent (Figure 3B) and showed good agreement with the experimental data (Figure 3A). These results suggest that the neurite length-dependent accumulation of shootin1 is quantitatively explained by its anterograde transport and retrograde diffusion.

This length-dependent shootin1 accumulation constitutes a positive feedback interaction with the previously reported shootin1-induced neurite outgrowth (Shimada et al, 2008). To analyze the functional role of this feedback loop, we quantified shootin1 upregulation (Toriyama et al, 2006) and shootin1-induced neurite outgrowth, and integrated them, together with the above model of length-dependent shootin1 accumulation, into a model neuron (Figure 7A). Furthermore, the parameters of the model components were chosen to give the best fit to the quantitative experimental data without any adjustment. Integrating the three components into a model neuron resulted in spontaneous symmetry breaking (Figure 7B and C). Furthermore, there are a total of 15 agreements between the model predictions and the experimental data, including the neurite length-dependent axon specification and regeneration (Goslin and Banker, 1989; Lamoureux et al, 2002). These data suggest that the three components in our model—namely, diffusion-based neurite length sensing system, shootin1-induced neurite outgrowth and shootin1 upregulation—are sufficient to induce neuronal symmetry breaking.

Bolus-like transport of shootin1 caused large stochastic fluctuations in shootin1 concentration in neurite tips. Interestingly, the generation of continuous shootin1 transport in our model neuron impaired the symmetry-breaking process (Figure 7D). This is consistent with theoretical models in which feedback amplification of fluctuations in signaling can give rise to robust patterns (Turing, 1952; Meinhardt and Gierer, 2000; Kondo, 2002), and underscores the importance of the stochastic fluctuating signals in spontaneous neuronal symmetry breaking.

The combination of quantitative experimentation and mathematical modeling is regarded as a powerful strategy for attaining a profound understanding of biological systems (Hodgkin and Huxley, 1952b; Lewis, 2008; Ferrell, 2009). By focusing on a simple system involving one of the earliest markers of neuronal symmetry breaking, shootin1, we were able to evaluate here the core components of neuronal symmetry breaking on the basis of quantitative experimental data. The present model may thus provide a core mechanism of neuronal symmetry breaking, to which other possible mechanisms can be added to increase the model's complexity in future studies.

Although there has been significant progress in understanding the molecular signals that change cell morphology, mechanisms that cells use to monitor their size and length to regulate their morphology remain elusive. Previous studies suggest that polarizing cultured hippocampal neurons can sense neurite length, identify the longest neurite, and induce its subsequent outgrowth for axonogenesis. We observed that shootin1, a key regulator of axon outgrowth and neuronal polarization, accumulates in neurite tips in a neurite length-dependent manner; here, the property of cell length is translated into shootin1 signals. Quantitative live cell imaging combined with modeling analyses revealed that intraneuritic anterograde transport and retrograde diffusion of shootin1 account for its neurite length-dependent accumulation. Our quantitative model further explains that the length-dependent shootin1 accumulation, together with shootin1-dependent neurite outgrowth, constitutes a positive feedback loop that amplifies stochastic fluctuations of shootin1 signals, thereby generating an asymmetric signal for axon specification and neuronal symmetry breaking.

Sprouty4, an FGF inhibitor, displays cyclic gene expression under the control of the notch segmentation clock in the mouse PSM

BACKGROUND

During vertebrate embryogenesis, somites are generated at regular intervals, the temporal and spatial periodicity of which is governed by a gradient of fibroblast growth factor (FGF) and/or Wnt signaling activity in the presomitic mesoderm (PSM) in conjunction with oscillations of gene expression of components of the Notch, Wnt and FGF signaling pathways.

PRINCIPAL FINDINGS

Here, we show that the expression of Sprouty4, which encodes an FGF inhibitor, oscillates in 2-h cycles in the mouse PSM in synchrony with other oscillating genes from the Notch signaling pathway, such as lunatic fringe. Sprouty4 does not oscillate in Hes7-null mutant mouse embryos, and Hes7 can inhibit FGF-induced transcriptional activity of the Sprouty4 promoter.

CONCLUSIONS

Thus, periodic expression of Sprouty4 is controlled by the Notch segmentation clock and may work as a mediator that links the temporal periodicity of clock gene oscillations with the spatial periodicity of boundary formation which is regulated by the gradient of FGF/Wnt activity.

Quantification of local morphodynamics and local GTPase activity by edge evolution tracking

Advances in time-lapse fluorescence microscopy have enabled us to directly observe dynamic cellular phenomena. Although the techniques themselves have promoted the understanding of dynamic cellular functions, the vast number of images acquired has generated a need for automated processing tools to extract statistical information. A problem underlying the analysis of time-lapse cell images is the lack of rigorous methods to extract morphodynamic properties. Here, we propose an algorithm called edge evolution tracking (EET) to quantify the relationship between local morphological changes and local fluorescence intensities around a cell edge using time-lapse microscopy images. This algorithm enables us to trace the local edge extension and contraction by defining subdivided edges and their corresponding positions in successive frames. Thus, this algorithm enables the investigation of cross-correlations between local morphological changes and local intensity of fluorescent signals by considering the time shifts. By applying EET to fluorescence resonance energy transfer images of the Rho-family GTPases Rac1, Cdc42, and RhoA, we examined the cross-correlation between the local area difference and GTPase activity. The calculated correlations changed with time-shifts as expected, but surprisingly, the peak of the correlation coefficients appeared with a 6–8 min time shift of morphological changes and preceded the Rac1 or Cdc42 activities. Our method enables the quantification of the dynamics of local morphological change and local protein activity and statistical investigation of the relationship between them by considering time shifts in the relationship. Thus, this algorithm extends the value of time-lapse imaging data to better understand dynamics of cellular function.

Morphological change is a key indicator of various cellular functions such as migration and construction of specific structures. Time-lapse image microscopy permits the visualization of changes in morphology and spatio-temporal protein activity related to dynamic cellular functions. However, an unsolved problem is the development of an automated analytical method to handle the vast amount of associated image data. This article describes a novel approach for analysis of time-lapse microscopy data. We automated the quantification of morphological change and cell edge protein activity and then performed statistical analysis to explore the relationship between local morphological change and spatio-temporal protein activity. Our results reveal that morphological change precedes specific protein activity by 6–8 min, which prompts a new hypothesis for cellular morphodynamics regulated by molecular signaling. Use of our method thus allows for detailed analysis of time-lapse images emphasizing the value of computer-assisted high-throughput analysis for time-lapse microscopy images and statistical analysis of morphological properties.

Stochastic control of spontaneous signal generation for gradient sensing in chemotaxis

Chemotaxis is characterized by spontaneous cellular behavior. This spontaneity results, in part, from the stochasticity of intracellular reactions. Spontaneous and random migration of chemotactic cells is regulated by spontaneously generated signals, namely transient local increases in the level of phosphoinositol-3,4,5-triphosphate (PIP3 pulses). In this study, we attempted to elucidate the mechanisms that generate these PIP3 pulses and how the pulses contribute to gradient sensing during chemotaxis. To this end, we constructed a simple biophysical model of intracellular signal transduction consisting of an inositol phospholipid signaling pathway and small GTPases. Our theoretical analysis revealed that an excitable system can emerge from the non-linear dynamics of the model, and that stochastic reactions allow the system to spontaneously become excited, which was corresponded to the PIP3 pulses. Based on these results, we framed a hypothesis of the gradient sensing; a chemical gradient spatially modifies a potential barrier for excitation and then PIP3 pulses are preferentially generated on the side of the cell exposed to the higher chemical concentration. We then validated our hypothesis using stochastic simulations of the signal transduction.

Shootin1: A protein involved in the organization of an asymmetric signal for neuronal polarization

Neurons have the remarkable ability to polarize even in symmetrical in vitro environments. Although recent studies have shown that asymmetric intracellular signals can induce neuronal polarization, it remains unclear how these polarized signals are organized without asymmetric cues. We describe a novel protein, named shootin1, that became up-regulated during polarization of hippocampal neurons and began fluctuating accumulation among multiple neurites. Eventually, shootin1 accumulated asymmetrically in a single neurite, which led to axon induction for polarization. Disturbing the asymmetric organization of shootin1 by excess shootin1 disrupted polarization, whereas repressing shootin1 expression inhibited polarization. Overexpression and RNA interference data suggest that shootin1 is required for spatially localized phosphoinositide-3-kinase activity. Shootin1 was transported anterogradely to the growth cones and diffused back to the soma; inhibiting this transport prevented its asymmetric accumulation in neurons. We propose that shootin1 is involved in the generation of internal asymmetric signals required for neuronal polarization.

The role of short-term depression in sustained neural activity in the prefrontal cortex: a simulation study

Recent experimental researches have suggested that sustained neural activity in the prefrontal cortex is a process of memory retention in decision making. Previous theoretical studies indicate that a balance between recurrent excitation and feedback inhibition is important for sustaining the activity. To investigate a plausible balancing mechanism, we simulated a biophysically realistic network model. Our model shows that short-term depression (STD) enables the network to sustain its activity despite the presence of long-term inhibition by GABA(B) receptors and that the sustained firing rates have a bell-shaped dependence on the degree of STD. By analyzing the neural network dynamics, we show that the bell-shaped dependence on STD is formed by destabilizing the balance with either excessive or insufficient STD. We also show that the optimal degree of STD has a linear relationship with the neural network size. These results suggest that STD provides a balancing mechanism and controls levels of sustained activities of various size networks.

Local signaling with molecular diffusion as a decoder of Ca2+ signals in synaptic plasticity

Synaptic plasticity is induced by the influx of calcium ions (Ca²⁺) through N-methyl-D-aspartate receptors (NMDARs), and the direction and strength of the response depend on the frequency of the synaptic inputs. Recent studies have shown that the direction of synaptic plasticity is also governed by two distinct NMDAR subtypes (NR1/NR2A, NR1/NR2B). How are the different types of regulation (frequency-dependent and receptor-specific) processed simultaneously? To clarify the molecular basis of this dual dependence of synaptic plasticity, we have developed a mathematical model of spatial Ca²⁺ signaling in a dendritic spine. Our simulations revealed that calmodulin (CaM) activation in the vicinity of NMDARs is strongly affected by the diffusion coefficient of CaM itself, and that this ‘local CaM diffusion system' works as a dual decoder of both the frequency of Ca²⁺ influxes and their postsynaptic current shapes, generated by two NMDAR subtypes, implying that spatial factors may underlie the complicated regulation scheme of synaptic plasticity.

Stochastic resonance with differential code in feedforward network with intra-layer random connections

We examined stochastic resonance with a differential coding scheme using a multilayer feedforward neural network which is composed of intra-layer connections. We show that the network, with random synaptic connections in each layer, encodes an input signal into a spike coherence that represents temporal differences among the inputs. We also demonstrate that both internal and external noise enhance the detection of weak signals. Finally, we discuss how the feedforward network with intra-layer random connections is similar to a membrane in its sensitivity to and amplification of a change in stimulus and suggest that the intensity of internal noise may be tuned in a real brain.

A molecular model for axon guidance based on cross talk between rho GTPases

To systematically understand the molecular events that underlie biological phenomena, we must develop methods to integrate an enormous amount of genomic and proteomic data. The integration of molecular data should go beyond the construction of biochemical cascades among molecules to include tying the biochemical phenomena to physical events. For the behavior and guidance of growth cones, it remains largely unclear how biochemical events in the cytoplasm are linked to the morphological changes of the growth cone. We take a computational approach to simulate the biochemical signaling cascade involving members of the Rho family of GTPases and examine their potential roles in growth-cone motility and axon guidance. Based on the interactions between Cdc42, Rac, and RhoA, we show that the activation of a Cdc42-specific GEF resulted in switching responses between oscillatory and convergent activities for all three GTPases. We propose that the switching responses of these GTPases are the molecular basis for the decision mechanism that determines the direction of the growth-cone expansion, providing a spatiotemporal integration mechanism that allows the growth cone to detect small gradients of external guidance cues. These results suggest a potential role for the cross talk between Rho GTPases in governing growth-cone movement and axon guidance and underscore the link between chemodynamic reactions and cellular behaviors.

Purification and some properties of S-Hemolysin produced by Streptomyces sp. strain no. A-6288

A new cytolytic toxin, designated as S-Hemolysin, was found in the culture filtrate of Streptomyces sp. strain No. A-6288, isolated from a soil sample. The molecular weight of S-Hemolysin was estimated to be 10,000 by SDS-polyacrylamide gel electrophoresis and to be 20,000 by Sephadex G-100. S-Hemolysin is a glycoprotein that is composed of 102 amino acid residues with 11.6% glucose, and the isoelectric point is around pH 5.8. The phospholipase C activity of S-Hemolysin was specific for the following substrates in this order: sphingomyelin > lysophosphatidylethanolamine > lysophosphatidylcholine > phosphatidylethanolamine > phosphatidylcholine. S-Hemolysin had hemolytic activity against rabbit, human, and sheep erythrocytes, but did not cause aggregation of human platelets. These activities were accelerated with Mg2+, Mn2+, and Co2+ ions and inhibited by the addition of Ca2+, Cu2+, and Zn2+ ions. This enzyme was shown to be different from the known bacterial phospholipase C.