An analytical tool that quantifies cellular morphology changes from three-dimensional fluorescence images

The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology(1) even in complex tissue sections(2). Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells(3), however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.

A multi-scaled approach for simulating chemical reaction systems

In this paper we give an overview of some very recent work, as well as presenting a new approach, on the stochastic simulation of multi-scaled systems involving chemical reactions. In many biological systems (such as genetic regulation and cellular dynamics) there is a mix between small numbers of key regulatory proteins, and medium and large numbers of molecules. In addition, it is important to be able to follow the trajectories of individual molecules by taking proper account of the randomness inherent in such a system. We describe different types of simulation techniques (including the stochastic simulation algorithm, Poisson Runge-Kutta methods and the balanced Euler method) for treating simulations in the three different reaction regimes: slow, medium and fast. We then review some recent techniques on the treatment of coupled slow and fast reactions for stochastic chemical kinetics and present a new approach which couples the three regimes mentioned above. We then apply this approach to a biologically inspired problem involving the expression and activity of LacZ and LacY proteins in E coli, and conclude with a discussion on the significance of this work. (C) 2004 Elsevier Ltd. All rights reserved.

The dynamics of cellular automata on 2-manifolds is affected by topology

In this paper, we demonstrate that the distribution of Wolfram classes within a cellular automata rule space in the triangular tessellation is not consistent across different topological general. Using a statistical mechanics approach, cellular automata dynamical classes were approximated for cellular automata defined on genus-0, genus-1 and genus-2 2-manifolds. A distribution-free equality test for empirical distributions was applied to identify cases in which Wolfram classes were distributed differently across topologies. This result implies that global structure and local dynamics contribute to the long term evolution of cellular automata.

Infection and cellular defense dynamics in a novel 17beta-estradiol murine model of chronic human group B streptococcus genital tract colonization reveal a role for hemolysin in persistence and neutrophil accumulation

Genital tract carriage of group B streptococcus (GBS) is prevalent among adult women; however, the dynamics of chronic GBS genital tract carriage, including how GBS persists in this immunologically active host niche long term, are not well defined. To our knowledge, in this study, we report the first animal model of chronic GBS genital tract colonization using female mice synchronized into estrus by delivery of 17β-estradiol prior to intravaginal challenge with wild-type GBS 874391. Cervicovaginal swabs, which were used to measure bacterial persistence, showed that GBS colonized the vaginal mucosa of mice at high numbers (106–107 CFU/swab) for at least 90 d. Cellular and histological analyses showed that chronic GBS colonization of the murine genital tract caused significant lymphocyte and PMN cell infiltrates, which were localized to the vaginal mucosal surface. Long-term colonization was independent of regular hormone cycling. Immunological analyses of 23 soluble proteins related to chemotaxis and inflammation showed that the host response to GBS in the genital tract comprised markers of innate immune activation including cytokines such as GM-CSF and TNF-α. A nonhemolytic isogenic mutant of GBS 874391, Δcyle9, was impaired for colonization and was associated with amplified local PMN responses. Induction of DNA neutrophil extracellular traps, which was observed in GBS-infected human PMNs in vitro in a hemolysin-dependent manner, appeared to be part of this response. Overall, this study defines key infection dynamics in a novel murine model of chronic GBS genital tract colonization and establishes previously unknown cellular and soluble defense responses to GBS in the female genital tract.

Computational fluid dynamics for improved bioreactor design and 3D culture

The complex relationship between the hydrodynamic environment and surrounding tissues directly impacts on the design and production of clinically useful grafts and implants. Tissue engineers have generally seen bioreactors as 'black boxes' within which tissue engineering constructs (TECs) are cultured. It is accepted that a more detailed description of fluid mechanics and nutrient transport within process equipment can be achieved by using computational fluid dynamics (CFD) technology. This review discusses applications of CFD for tissue engineering-related bioreactors -- fluid flow processes have direct implications on cellular responses such as attachment, migration and proliferation. We conclude that CFD should be seen as an invaluable tool for analyzing and visualizing the impact of fluidic forces and stresses on cells and TECs.

Analyzing real-time video microscopy : the dynamics and geometry of vesicles and tubules in endocytosis

With the advent of live cell imaging microscopy, new types of mathematical analyses and measurements are possible. Many of the real-time movies of cellular processes are visually very compelling, but elementary analysis of changes over time of quantities such as surface area and volume often show that there is more to the data than meets the eye. This unit outlines a geometric modeling methodology and applies it to tubulation of vesicles during endocytosis. Using these principles, it has been possible to build better qualitative and quantitative understandings of the systems observed, as well as to make predictions about quantities such as ligand or solute concentration, vesicle pH, and membrane trafficked. The purpose is to outline a methodology for analyzing real-time movies that has led to a greater appreciation of the changes that are occurring during the time frame of the real-time video microscopy and how additional quantitative measurements allow for further hypotheses to be generated and tested.

Parallel implementation of stochastic simulation for large scale cellular processes

Experimental and theoretical studies have shown the importance of stochastic processes in genetic regulatory networks and cellular processes. Cellular networks and genetic circuits often involve small numbers of key proteins such as transcriptional factors and signaling proteins. In recent years stochastic models have been used successfully for studying noise in biological pathways, and stochastic modelling of biological systems has become a very important research field in computational biology. One of the challenge problems in this field is the reduction of the huge computing time in stochastic simulations. Based on the system of the mitogen-activated protein kinase cascade that is activated by epidermal growth factor, this work give a parallel implementation by using OpenMP and parallelism across the simulation. Special attention is paid to the independence of the generated random numbers in parallel computing, that is a key criterion for the success of stochastic simulations. Numerical results indicate that parallel computers can be used as an efficient tool for simulating the dynamics of large-scale genetic regulatory networks and cellular processes

An approximate Bayesian computation approach for estimating parameters of complex environmental processes in a cellular automata

Modelling an environmental process involves creating a model structure and parameterising the model with appropriate values to accurately represent the process. Determining accurate parameter values for environmental systems can be challenging. Existing methods for parameter estimation typically make assumptions regarding the form of the Likelihood, and will often ignore any uncertainty around estimated values. This can be problematic, however, particularly in complex problems where Likelihoods may be intractable. In this paper we demonstrate an Approximate Bayesian Computational method for the estimation of parameters of a stochastic CA. We use as an example a CA constructed to simulate a range expansion such as might occur after a biological invasion, making parameter estimates using only count data such as could be gathered from field observations. We demonstrate ABC is a highly useful method for parameter estimation, with accurate estimates of parameters that are important for the management of invasive species such as the intrinsic rate of increase and the point in a landscape where a species has invaded. We also show that the method is capable of estimating the probability of long distance dispersal, a characteristic of biological invasions that is very influential in determining spread rates but has until now proved difficult to estimate accurately.

Cellular settings mediating Src Substrate switching between Focal Adhesion Kinase Tyrosine 861 and CUB-domain-containing protein 1 (CDCP1) Tyrosine 734

Reciprocal interactions between Src family kinases (SFKs) and focal adhesion kinase (FAK) are critical during changes in cell attachment. Recently it has been recognized that another SFK substrate, CUB-domain-containing protein 1 (CDCP1), is differentially phosphorylated during these events. However, the molecular processes underlying SFK-mediated phosphorylation of CDCP1 are poorly understood. Here we identify a novel mechanism in which FAK tyrosine 861 and CDCP1-Tyr-734 compete as SFK substrates and demonstrate cellular settings in which SFKs switch between these sites. Our results show that stable CDCP1 expression induces robust SFK-mediated phosphorylation of CDCP1-Tyr-734 with concomitant loss of p-FAK-Tyr-861 in adherent HeLa cells. SFK substrate switching in these cells is dependent on the level of expression of CDCP1 and is also dependent on CDCP1-Tyr-734 but is independent of CDCP1-Tyr-743 and -Tyr-762. In HeLa CDCP1 cells, engagement of SFKs with CDCP1 is accompanied by an increase in phosphorylation of Src-Tyr-416 and a change in cell morphology to a fibroblastic appearance dependent on CDCP1-Tyr-734. SFK switching between FAK-Tyr-861 and CDCP1-Tyr-734 also occurs during changes in adhesion of colorectal cancer cell lines endogenously expressing these two proteins. Consistently, increased p-FAK-Tyr-861 levels and a more epithelial morphology are seen in colon cancer SW480 cells silenced for CDCP1. Unlike protein kinase Cδ, FAK does not appear to form a trimeric complex with Src and CDCP1. These data demonstrate novel aspects of the dynamics of SFK-mediated cell signaling that may be relevant during cancer progression.

Expression of PTRF in PC3 cells modulates cholesterol dynamics and the actin cytoskeleton impacting secretion pathways

Expression of caveolin-1 is up-regulated in prostate cancer metastasis and is associated with aggressive recurrence of the disease. Intriguingly, caveolin-1 is also secreted from prostate cancer cell lines and has been identified in secreted prostasomes. Caveolin-1 is the major structural component of the plasma membrane invaginations called caveolae. Co-expression of the coat protein Polymerase I and transcript release factor (PTRF) is required for caveolae formation. We recently found that expression of caveolin-1 in the aggressive prostate cancer cell line PC-3 is not accompanied by PTRF, leading to noncaveolar caveolin-1 lipid rafts. Moreover, ectopic expression of PTRF in PC-3 cells sequesters caveolin-1 into caveolae. Here we quantitatively analyzed the effect of PTRF expression on the PC-3 proteome using stable isotope labeling by amino acids in culture and subcellular proteomics. We show that PTRF reduced the secretion of a subset of proteins including secreted proteases, cytokines, and growth regulatory proteins, partly via a reduction in prostasome secretion. To determine the cellular mechanism accounting for the observed reduction in secreted proteins we analyzed total membrane and the detergent-resistant membrane fractions. Our data show that PTRF expression selectively impaired the recruitment of actin cytoskeletal proteins to the detergent-resistant membrane, which correlated with altered cholesterol distribution in PC-3 cells expressing PTRF. Consistent with this, modulating cellular cholesterol altered the actin cytoskeleton and protein secretion in PC-3 cells. Intriguingly, several proteins that function in ER to Golgi trafficking were reduced by PTRF expression. Taken together, these results suggest that the noncaveolar caveolin-1 found in prostate cancer cells generates a lipid raft microenvironment that accentuates secretion pathways, possibly at the step of ER sorting/exit. Importantly, these effects could be modulated by PTRF expression.

Stroma regulates increased epithelial lateral cell adhesion in 3D culture : a role for actin/cadherin dynamics

BACKGROUND: Cell shape and tissue architecture are controlled by changes to junctional proteins and the cytoskeleton. How tissues control the dynamics of adhesion and cytoskeletal tension is unclear. We have studied epithelial tissue architecture using 3D culture models and found that adult primary prostate epithelial cells grow into hollow acinus-like spheroids. Importantly, when co-cultured with stroma the epithelia show increased lateral cell adhesions. To investigate this mechanism further we aimed to: identify a cell line model to allow repeatable and robust experiments; determine whether or not epithelial adhesion molecules were affected by stromal culture; and determine which stromal signalling molecules may influence cell adhesion in 3D epithelial cell cultures. METHODOLOGY/PRINCIPAL FINDINGS: The prostate cell line, BPH-1, showed increased lateral cell adhesion in response to stroma, when grown as 3D spheroids. Electron microscopy showed that 9.4% of lateral membranes were within 20 nm of each other and that this increased to 54% in the presence of stroma, after 7 days in culture. Stromal signalling did not influence E-cadherin or desmosome RNA or protein expression, but increased E-cadherin/actin co-localisation on the basolateral membranes, and decreased paracellular permeability. Microarray analysis identified several growth factors and pathways that were differentially expressed in stroma in response to 3D epithelial culture. The upregulated growth factors TGFβ2, CXCL12 and FGF10 were selected for further analysis because of previous associations with morphology. Small molecule inhibition of TGFβ2 signalling but not of CXCL12 and FGF10 signalling led to a decrease in actin and E-cadherin co-localisation and increased paracellular permeability. CONCLUSIONS/SIGNIFICANCE: In 3D culture models, paracrine stromal signals increase epithelial cell adhesion via adhesion/cytoskeleton interactions and TGFβ2-dependent mechanisms may play a key role. These findings indicate a role for stroma in maintaining adult epithelial tissue morphology and integrity.

Intrinsics and dynamics of fat grafts : an in vitro study

Background Despite a revived interest in fat grafting procedures, clinicians still fail to demonstrate clearly the in vivo behavior of fat grafts as a dynamic tissue substitute. However, the basic principles in cellular biology teach us that cells can survive and develop, provided that a structural matrix exists that directs their behavior. The purpose of this in vitro study was to analyze that behavior of crude fat grafts, cultured on a three-dimensional laminin-rich matrix. Methods Nonprocessed, human fat biopsy specimens (approximately 1 mm) were inoculated on Matrigel-coated wells to which culture medium was added. The control group consisted of fat biopsy specimens embedded in medium alone. The cellular proliferation pattern was followed over 6 weeks. Additional cultures of primary generated cellular spheroids were performed and eventually subjected to adipogenic differentiation media. Results A progressive outgrowth of fibroblast-like cells from the core fat biopsy specimen was observed in both groups. Within the Matrigel group, an interconnecting three-dimensional network of spindle-shaped cells was established. This new cell colony reproduced spheroids that functioned again as solitary sources of cellular proliferation. Addition of differentiation media resulted in lipid droplet deposition in the majority of generated cells, indicating the initial steps of adipogenic differentiation. Conclusions The authors noticed that crude, nonprocessed fat biopsy specimens do have considerable potential for future tissue engineering-based applications, provided that the basic principles of developmental, cellular biology are respected. Spontaneous in vitro expansion of the stromal cells present in fat grafts within autologous and injectable matrices could create "off-the-shelf" therapies for reconstructive procedures.

On the effect of topology on cellular automata rule spaces

This thesis presents an empirical study of the effects of topology on cellular automata rule spaces. The classical definition of a cellular automaton is restricted to that of a regular lattice, often with periodic boundary conditions. This definition is extended to allow for arbitrary topologies. The dynamics of cellular automata within the triangular tessellation were analysed when transformed to 2-manifolds of topological genus 0, genus 1 and genus 2. Cellular automata dynamics were analysed from a statistical mechanics perspective. The sample sizes required to obtain accurate entropy calculations were determined by an entropy error analysis which observed the error in the computed entropy against increasing sample sizes. Each cellular automata rule space was sampled repeatedly and the selected cellular automata were simulated over many thousands of trials for each topology. This resulted in an entropy distribution for each rule space. The computed entropy distributions are indicative of the cellular automata dynamical class distribution. Through the comparison of these dynamical class distributions using the E-statistic, it was identified that such topological changes cause these distributions to alter. This is a significant result which implies that both global structure and local dynamics play a important role in defining long term behaviour of cellular automata.