Workshop 1: Visualizing and Modeling Cellular and SubCellular Phenomena

(January 13,2014 - January 17,2014 )

Organizers


John Condeelis
Department of Anatomy & Structural Biology, Albert Einstein College of Medicine
Anna-Katerina Hadjantonakis
Developmental Biology Program, Memorial Sloan-Kettering Cancer Center
Paul Kulesa
Developmental Biology, Stowers Institute for Medical Research
Philip Maini
Centre for Mathematical Biology, Mathematical Institute

The frontier of biology and medicine is defined by our ability to decipher the mechanisms that underlie basic phenomena. These phenomena may include cell motility and migration, cell division, cell reprogramming, and cell communication that may be manifested in a wide range of questions in development and disease. Thus, examples from stem cell, developmental, neural, and cancer biology have the potential to allow examination of basic biological processes within the context of real, in vivo phenomena. However, a major challenge has been the lack of a means to identify biologically tractable problems and link these problems to applications-oriented experts from imaging and mathematics.

The rate at which this frontier advances depends, at least in part, on how fast technology evolves and on how data is interpreted and translated into a better understanding of basic mechanisms. In the past 10 years, dramatic advances in imaging technology and mathematics have provided new tools and models for discovery that have enabled new observations and hypotheses to be tested. These tools, which are often designed for general applications, find their way into the hands of biologists who then see ways to use them. In some cases, specific mathematical models and applications drive innovations. The mathematical methods involved include PDEs, moving boundary value problems, dynamic geometric changes, optimal transport, stochastic modeling, and the analysis of large data sets. Advances in imaging technology that will be discussed include serial block-face scanning electron microscopy, superresolution microscopy, fluorescence resonance energy transfer (FRET)-based activity biosensors, detection of forces in cells and tissue, multispectral and multiphoton deep tissue imaging, and fluorescence light-sheet microscopy.

The goal of this workshop is to encourage biologiststo describe tough questions and to jointly think about approaches that inspire new developments and interdisciplinary research collaborations. We plan to do this by combining input and discussion from experts in imaging technology and mathematics with cell, developmental and cancer biologists that share a passion for solving the riddles that underlie complex phenomena in dynamic living systems. We suggest that both groups of participants blend what is technically possible with what exists only in dream space, with the hope that together we will learn something new and be stimulated to explore new ways to visualize, model and better understand complex processes.

Accepted Speakers

Mark Alber
Applied Mathematics, University of Notre Dame
Sharon Amacher
Molecular Genetics, The Ohio State University
Maria Barna
Developmental Biology and Genetics, Stanford University
Aviv Bergman
Systems and Computational Biology,
John Condeelis
Department of Anatomy & Structural Biology, Albert Einstein College of Medicine
Mary Dickinson
Molecular Physiology & Biophysics, Baylor College of Medicine
Leah Edelstein-Keshet
Mathematics Department, University of British Columbia
Bojana Gligorijevic
systems & computational biology, albert einstein college of medicine
Clarissa Henry
Biology and Ecology, University of Maine
Samuel Isaacson
mathematics and statistics, Boston University
Hildur Knutsdottir
Mathematics, University of British Columbia
Richard Levenson
Pathology and Laboratory Medicine, University of California Davis
Michael Liebling
Electrical and Computer Engineering, University of California Santa Barbara
Karen Lipkow
Nuclear Dynamics, The Babraham Institute
Robert Murphy
Lane Center for Computational Biology, Carnegie-Mellon University
Ruth Muschel
Oncology, Oxford University
Karen Page
Mathematics, University College London
Katarzyna Rejniak
H. Lee Moffitt Cancer Center & Research Institute, H. Lee Moffitt Cancer Center & Research Institute
Badri Roysam
Electrical & Computer Engineering, University of Houston
Erik Sahai
Tumor Cell Biology Lab, London Research Institute
Sean Smart
Oncology, Oxford University
Nessy Tania
Mathematics and Statistics, Smith College
Jacco van Rheenen
Cancer biophyics, Hubrecht Institute and University Medical Center Utrecht
Kees Weijer
College of Life Sciences, University of Dundee
Monday, January 13, 2014
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:15 AM

Greetings and Info from MBI - Marty Golubitsky

09:15 AM
09:30 AM

Logistics of the Meeting/Organizers

09:30 AM
10:00 AM
John Condeelis - Motility dynamics during tumor cell dissemination in breast tumors

Multi-photon intravital imaging of single tumor cells in breast tumors has revealed that macrophage-tumor cell pairing and streaming migration occur and this requires paracrine signaling and chemotaxis. Using signals involved in this macrophage-dependent tropism, tumor cells that co-migrate with macrophages have been isolated and expression profiled thereby revealing the pathways used by tumor cells during migration and invasion (the Invasion Signature).


The motility pathways identified in the Invasion Signature converge on the RhoC/Cofilin/Mena pathway which drives both invadopodium (invasive protrusion) formation and locomotory protrusions. Markers derived from this pathway can be used to predict risk of metastasis in breast cancer patients


To understand why the RhoC/Cofilin/Mena pathway predicts metastatic risk, FRET biosensors and multiphoton imaging have been used in vitro and in vivo leading to the following conclusions for breast tumors which will be discussed:



  1. Tumor cell movement during streaming and intravasation involves coordination of locomotory protrusions (pseudopods) and invasive protrusions (invadopodia).

  2. Both protrusions involve actin polymerization at the front of each protrusion in response to macrophage produced EGF.

  3. Cofilin activation is sufficient to determine the site of actin polymerization, protrusion and cell direction.

  4. Mena activity regulates the sensitivity of the EGFR to EGF thereby increasing invadopodium assembly and streaming migration with macrophages.

  5. RhoC/LIMK, Arg kinase, integrin beta1, cortactin, and NHE1 form a signaling complex that regulates the geometry and localization of cofilin activity in both invadopodia and locomotory protrusions determining the shape, size and oscillation of these protrusions during cell migration and invasion.

  6. PI3,4P2 and PI4,5P2 regulate the signaling complex in invadopodia and locomotory protrusions, respectively, demonstrating how the separation and coordination of these two types of protrusions is achieved.

  7. This signaling complex is involved in intravasation and dissemination of tumor cells thus determining the metastatic phenotype of the tumor.

  8. The rate constants for assembly of this complex supplies detailed information that can be used to model the behavior and dynamics of locomotory and invasive protrusions used during tumor cell dissemination.


10:00 AM
10:30 AM

Discussion

10:30 AM
11:00 AM

Break

11:00 AM
11:30 AM
Leah Edelstein-Keshet - Modeling the regulation of cell motility in normal and cancer cells

Cell motility is coordinated by an intricate network of interacting proteins and lipids, that transduce signals into cytoskeletal reorganization, cell shape changes, and locomotion. Here I will survey some mathematical modeling that addresses both normal and aberrant cell motility. I will describe efforts in my group to construct and analyse mathematical models for proteins (such as Rho family GTPases) and lipids (such as phosphoinositides), their feedbacks and their effects on protrusion and contraction of the cell front and rear, as well as cell shape. The role of the cytoskeleton and its actin-associated proteins (e.g. cofilin) will be mentioned. I will describe how several projects on cell polarity and GTPase spatial patterns have contributed to some insights into cell motility.

11:30 AM
12:00 PM

Discussion

12:00 PM
02:00 PM

Lunch Break

02:00 PM
02:15 PM
Nessy Tania - Modeling the regulation of cofilin and actin based protrusion in invasive tumor cells

Modeling the regulation of cofilin and actin based protrusion in invasive tumor cells

02:15 PM
02:30 PM

Discussion

02:30 PM
02:45 PM
Angelike Stathopoulos - Caudal visceral mesoderm (CVM) cell migration in the Drosophila embryo: a model system for coordinate cell migration

How groups of migrating cells collectively navigate the dynamic, changing environment of developing embryos is not well understood. To provide insight, our studies focus on a particular group of migrating cells, originating from the caudal visceral mesoderm (CVM) of Drosophila embryos, which complete the longest migration, distance-wise, in all of Drosophila embryogenesis. We use live imaging and genetic approaches to study coordinate migration of CVM cells, as they actively migrate from the posterior towards the anterior of the embryo as two bilaterally-symmetric (left and right), synchronously-migrating groups. The role of FGF signaling as well as new genes identified in gene expression profiling experiments will be discussed.

02:45 PM
03:00 PM

Discussion

03:00 PM
03:45 PM

Break

03:45 PM
04:00 PM
Robert Murphy - Learning Generative Models of the Dynamics of Cell Shape and Organization Changes

Given the complexity of biological systems, machine-learning methods are critically needed for building systems models of cell and tissue behavior and for studying their perturbations. Such models require accurate information about the subcellular distributions of proteins, RNAs and other macromolecules in order to be able to capture and simulate their spatiotemporal dynamics. Microscope images provide the best source of this information, and we have developed tools to build generative models of cell organization directly from such images. Generative models are capable of producing new instances of a pattern that are expected to be drawn from the same underlying distribution as those it was trained with. Our open source system, CellOrganizer (http://CellOrganizer.org), currently contains components that can build probabilistic generative models of cell, nuclear and organelle shape, organelle position, and microtubule distribution. These models capture heterogeneity within cell populations, and can be dependent upon each other and be combined to create new higher level models. The parameters of these models can be used as a highly interpretable basis for analyzing perturbations (e.g., induced by drug addition), and generative models of cell organization can be used as a framework for cell simulations to identify mechanisms underlying cell behavior. Results for analysis of systems ranging from neuronal differentiation to perturbation of plant protoplast organization will be presented.

04:00 PM
04:30 PM

Discussion

04:30 PM
06:30 PM

Reception and Poster Session in MBI Lounge

06:45 PM

Shuttle pick-up from MBI

Tuesday, January 14, 2014
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:15 AM
Maria Barna - Modeling and Imaging of Bacterial Motility

Modeling and Imaging of Bacterial Motility

09:15 AM
09:30 AM

Discussion

09:30 AM
09:45 AM
Stefano Di Talia
09:45 AM
10:00 AM

Discussion

10:00 AM
10:30 AM

Break

10:30 AM
10:45 AM
Karen Lipkow - Functional and Spatial Characterisation of Chromatin States in S. cerevisiae

The DNA of all eukaryotes is present in the nucleus as chromatin, in which DNA is closely associated with hundreds of different proteins. The precise combination at a given location determines how a gene is regulated. Experimentally measuring this protein distribution results in extensive datasets that are impossible to interpret by eye. We have applied a newly developed method to analyse chromatin from the model organism S. cerevisiae (bakers yeast). By carefully reducing the complexity of the original data, we identified five distinct chromatin states. These states differ in relevant biological properties, such as enrichment of gene ontologies. They form no detectable pattern in 1D along the chromosomes, but co-localise in 3D. To our surprise, much of the chromatin is poised, ready for change, under both standard and heat stressed conditions. This highlights the great dynamic capability of gene regulation, and how much is learned when taking a Systems view.

10:45 AM
11:00 AM

Discussion

11:00 AM
11:15 AM
Badri Roysam - Computational Discovery of Events & Phenomena from Microscopy Image Data

Computationally delineating complex biological structures in fluorescence microscopy images, also known as segmentation, is increasingly maturing to the point of becoming an operational tool for rapid and accurate morphometry. Multiplexed fluorescence imaging allows associative measurements relating multiple structures. Increasingly also, the ability to track moving structures in live time-lapse microscopy data is also advancing rapidly, and emerging as a tool for quantifying dynamic processes in cells and tissue. Combining multiplex fluorescence with time-lapse allows multiple phenomena to be imaged in a manner that preserves their relative context. In addition, gene and protein arrays have matured into routine tools for measuring the molecular profile of tissue specimens. Overall, the resulting measurements of structures, molecular signatures, and activities take the form of high-dimensional multi-variate datasets that are rich in terms of trends, events, and relationships. In this talk, I will describe progress in the development and integration of multivariate analytics tools into image analysis systems, specifically, the open source FARSIGHT toolkit (www.farsight-toolkit.org), to sense and extract these patterns. These capabilities are broadly useful in advancing quantitative biology, and I will draw upon examples from neuroscience and immunology to illustrate these methods.

11:15 AM
11:30 AM

Discussion

11:30 AM
12:30 PM

Technology Discussion (Image Analysis: Murphy, Roysam, Carpenter, Levenson, Liebling etc)

12:30 PM
02:30 PM

Lunch Break

02:30 PM
02:45 PM
Bojana Gligorijevic - Tumor cell motility and invadopodia in microenvironment context

During the metastasis, tumor cells move through the primary tumor and enter blood vessels (1). Tumor cell motility has been previously investigated in details in vitro and the signaling pathways which control locomotion in 2D or invadopodia formation, which results in extracellular matrix degradation and penetration, have been dissected (2,3). However, the conditions for the onset of such movements in vivo are not yet fully understood. Using multiphoton-based intravital microscopy we previously reported that the vicinity of macrophages (4) or blood vessels (5) is essential for tumor cell locomotion to occur in primary breast tumors. Yet other studies have demonstrated that the changes in stiffness (6) and architecture (7) of extracellular matrix may lead to increased motility and subsequently, metastasis. However, each of these factors has been studied separately and no attention was given to their combinatorial effect. Here we show that multiparametric, systems-level analysis is vital to predict tumor cell motility-related behaviors in vivo. Our analysis reveals the context in which invadopodia or tumor cell locomotion appear in vivo. Direct link was found between invadopodia number and lung metastasis. To predict invadopodium formation, which leads to intravasation, we conclude, microenvironmental conditions must be studied in concert rather than in isolation. Furthermore, future development of diagnostic markers for early metastasis will most likely necessitate such multiparametric analyses

02:45 PM
03:00 PM

Discussion

03:00 PM
03:30 PM

Break

03:30 PM
03:45 PM
Aviv Bergman - Revel in the Charm of (Genotypic) Variety, Relish in the Charm of (Phenotypic) Fidelity

Revel in the Charm of (Genotypic) Variety, Relish in the Charm of (Phenotypic) Fidelity.

03:45 PM
04:00 PM

Discussion

04:00 PM
04:15 PM
Jacco van Rheenen - Intravital Microscopy of Cancer Cell Plasticity Through Imaging Windows

Complications due to metastasis, the process where cells detach from a primary tumor to form new tumors at distant sites, are the primary reason why people die from cancer. Although histological techniques have provided important information on metastasis, they only give a static image of tumor cells and their microenvironment and thus compromise interpretation of this dynamic process. To study this dynamic process, we visualize the behavior of single metastasizing cells at subcellular resolution with two-photon intravital imaging (IVM). We have recently developed a Mammary Imaging Window (MIW) to image primary mammary tumors over multiple days. By combing the MIW with fluorescent lineage tracing tools, we intravitally lineage traced mammary tumors growth. Our intravital lineage tracing experiments showed the existence of a small population of cells, referred to as cancer stem cells (CSCs), that maintains and provides growth. Moreover, our experiments illustrated existing CSCs disappear and new CSCs form during mammary tumor growth, illustrating the dynamic nature of these cells.

In order to study how tumor cells arrive, survive and grow at secondary sites, we developed a new imaging window to image abdominal organs such as the liver, which is one of the primary organs for metastasis formation. Using this abdominal imaging window, we are able to visualize how individual tumor cells that arrive at the liver grow into metastases. We observe that single extravasated tumor cells proliferate and form 'pre-micrometastases' in which cells are migratory and lack contact to neighboring tumor cells. Subsequently, the clones condense into micrometastases in which cell migration is strongly diminished, but proliferation continues. By suppressing tumor cell migration in pre-micrometastases genetically or by drugs we reduce the number of metastases, and therefore we conclude that the migration of cells within pre-micrometastases is a novel contributing step in the formation of liver metastasis.

04:15 PM
05:15 PM

Discussion

05:15 PM

Shuttle pick-up from MBI

Wednesday, January 15, 2014
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:30 AM
Ruth Muschel - Hypoxia and Radiation Therapy

Tissue oxygen concentrations are created by a balance between oxygen delivery and oxygen consumption. Tumors consistently have regions of extreme hypoxia. These areas of hypoxia are generated by inadequate oxygen delivery due to the inadequate structure of tumor vasculature leading to inadequate perfusion. Hypoxia has profound effects on cancer progression and metastasis. Radiation therapy is particularly adversely affected because hypoxia greatly reduces its effectiveness, both due to the requirement for oxygen to fix DNA damage and to the biological consequences of hypoxia. As a consequence considerable effort has been made to reduce the extent of hypoxia during radiation therapy. The most extensive efforts however have focused upon altering oxygen delivery, either by carbogen breathing or improving perfusion with limited success. Here we will discuss reduction of oxygen consumption as a means to achieve the same goal. As expected reduction in oxygen consumption leads to reduced hypoxia. We further demonstrate the possibility of improving the outcome of radiation therapy by this means.

09:30 AM
10:00 AM

Discussion

10:00 AM
10:30 AM

Break

10:30 AM
11:00 AM
Erik Sahai - Modelling cell migration in different matrix geometries

Modelling cell migration in different matrix geometries

11:00 AM
11:30 AM

Discussion

11:30 AM
01:30 PM

Pizza Lunch

01:30 PM
01:45 PM
Mary Dickinson - Imaging dynamic events in vessel remodeling during mouse development

Imaging dynamic events in vessel remodeling during mouse development

01:45 PM
02:15 PM

Discussion

02:15 PM
02:45 PM

Break

02:45 PM
03:00 PM
Michael Liebling - Decoupling morphogenetic tissue deformations from functional motion in cardiac development

Live microscopy allows observing rapidly moving samples, such as whole embryos during their development. Motion can be local (e.g. individual cells migrating, dividing, or contracting) or more global (e.g. induced by tissue growth or organ function). When the observed motion is induced by more than a single process or occurs at multiple temporal and spatial scales, subtler motions and events are often hidden among more prominent, but unrelated, motions patterns. For example, within the beating and developing heart, cells undergo both rapid, periodic motions as the heart contracts to pump blood and also slower motions as the cells rearrange during maturation of the heart. In this talk, I will discuss in vivo image acquisition, processing, and analysis tools that we developed to digitally document both the morphogenesis and the function of the developing heart. Specifically, I will present our strategy to capture and integrate heterogeneous data acquired with multiple microscopy modalities (including fluorescence microscopy and optical coherence tomography), at multiple temporal and spatial scales (from milliseconds to hours and from single cells to entire organs, respectively), and in multiple dimensions. This allowed us to observe cellular division on the surface of the beating heart without the need to ever slow or stop it, demonstrating the possibility of disentangling complex motion patterns through customized imaging and digital post-processing strategies.

03:00 PM
03:15 PM

Discussion

03:15 PM
03:30 PM
Sean Smart - In vivo Study of the Intact Mouse by Non-Invasive Tomographic Imaging

In vivo Study of the Intact Mouse by Non-Invasive Tomographic Imaging

03:30 PM
03:45 PM

Discussion

03:45 PM
05:15 PM

Technology Discussion: (Intravital Imaging: Betzig, Dickinson, Weijer, Barna, Condeelis, Smart, van Rheenan etc)

05:15 PM

Shuttle pick-up from MBI

Thursday, January 16, 2014
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:30 AM
Kees Weijer - Cellular mechanisms underlying the formation of the primitive streak formation in the chick embryo

The mechanisms controlling the formation of the primitive streak in amniote embryos are still not understood. In the chick embryo it has been shown that streak formation involves extensive large scale counter rotating cell flows in the epiblast that merge at the position of the forming streak and which transport the forming mesoderm in the midline of the embryo. Simultaneous with the formation of the streak, the hypoblast develops and extends in anterior direction. Based on experimental observations and modelling studies it has been suggested that streak formation could result from chemotaxis, local cell-cell intercalation and or oriented division. However detailed quantitative data on cell behaviours to back up any of these hypothesis are still lacking. The cells in the epiblast form a highly polarised epithelial sheet and the cells are connected through well developed apical adherens and tight junctions. It remains to be determined by which mechanisms the cells in the epiblast and forming streak move and how much relative cell movement exists. To answer some of the questions and study most cells in the embryo (3-4 mm across) we have developed a dedicated light sheet microscope that in combination with the availability of a new transgenic chick line that expresses a membrane targeted GFP now allows us to investigate cellular dynamics during streak formation in great detail. We will describe our recent findings made using these new tools. The results obtained support a novel mechanism for streak formation based on localised shape changes resulting in ingression as well as intercalation of mesendoderm cells. We will discuss our current ideas of the mechanisms underlying and coordinating these processes and discuss some of the open questions

09:30 AM
10:00 AM

Discussion

10:00 AM
10:30 AM

Break

10:30 AM
11:00 AM
Philip Maini - Modelling Collective Cell Motion in Biology

Modelling Collective Cell Motion in Biology

11:00 AM
11:30 AM

Discussion

11:30 AM
01:30 PM

Lunch Break

01:30 PM
01:45 PM
Mark Alber - Multiscale Modeling of Bacterial Swarming

The ability of animals to self-organize into remarkable patterns of movement is seen throughout nature from herds of large mammals, to flocks of birds, schools of fish, and swarms of insects. Remarkably, patterns of collective movement can be seen even in the simplest forms of life such as bacteria. M. xanthus are common soil bacteria that are among the most "social" bacteria in nature. In this talk clustering mechanism of M. xanthus will be described using combination of experimental movies obtained using a novel high-resolution, time-lapse microscopy approach and model simulations [1,2]. Population of bacteria P. aeruginosa, main infection in hospitals, will be also shown to propagate as high density waves that move symmetrically as rings within swarms towards the extending tendrils. Biologically-justified cell-based multiscale model simulations suggest a mechanism of wave propagation as well as branched tendril formation at the edge of the population that depend upon competition between the changing viscosity of the bacterial liquid suspension and the liquid film boundary expansion caused by Marangoni forces [2]. The model predictions of wave speed and swarm expansion rate as well as cell alignment in tendrils were confirmed experimentally

01:45 PM
02:00 PM

Discussion

02:00 PM
02:15 PM
Richard Levenson - Image analysis and pathology: the raw and the cooked - and some stuff on multiplexing

Image analysis and pathology: the raw and the cooked - and some stuff on multiplexing

02:15 PM
02:45 PM

Discussion

02:45 PM
03:15 PM

Break

03:15 PM
03:30 PM
Katarzyna Rejniak - Mathematical modeling and biomedical imaging of anti-cancer drug penetration

The interactions between tumor cells and their microenvironment are complex, and this complexity is leveraged when both tumor and stromal cells are exposed to anticancer therapeutic agents. We use mathematical modeling and computational simulations to systematically explore the role of tumor tissue architecture and stromal composition on the extent of drug and biomarker molecule penetration into the tissue. An integral part of our approach is the use of various biomedical imaging techniques to both parameterize the models and to validate their results. This is accomplished by close collaboration with cancer biologists and pathologists. In this talk, we present a current state of the computational model integrated with experimental data and calibrated to pancreatic tumor xenografts that aim on providing an analytical tool in designing drug properties and drug administration schedules that will optimize drug penetration into the tumor tissue and enhance their therapeutic efficacy.

03:30 PM
03:45 PM

Discussion

03:45 PM
04:00 PM
Karen Page - Mathematical modelling of vertebrate neural tube patterning

A major challenge in developmental biology is to understand the mechanisms of pattern formation. Morphogens provide the positional information that organises gene expression and cell differentiation in many developing tissues. Conventional views say they induce distinct responses in a concentration-dependent manner. But signal duration has also been implicated in determining cellular responses. Here we establish how both the level and duration of signaling by the morphogen Sonic Hedgehog (Shh) control patterning in the vertebrate neural tube. Morphogen signaling is interpreted by a transcriptional regulatory circuit that links Shh signaling to three transcription factors. We present the circuit and equations to describe the levels of the transcription factors within a cell. We show that the design of this circuit unifies the temporal and graded response to Shh signaling. It also renders cells insensitive to transient increases in Shh signalling and confers hysteresis - memory of the signal. These results are experimentally verified. We discuss alternative behaviours of the gene regulatory network.

04:00 PM
04:15 PM

Break

04:15 PM
05:15 PM

Computational Modeling Discussion: (Including Maini, Alber, and Page, et al.)

05:15 PM

Shuttle pick-up from MBI

06:00 PM
07:00 PM

Cash Bar

07:00 PM
09:00 PM

Banquet in the Fusion Room at the Crowne Plaza

Friday, January 17, 2014
Time Session
08:00 AM

Shuttle to MBI

08:15 AM
09:00 AM

Breakfast

09:00 AM
09:15 AM
Clarissa Henry - NAD+ biosynthesis ameliorates muscular dystrophy in zebrafish

NAD+ biosynthesis ameliorates muscular dystrophy in zebrafish

09:15 AM
09:30 AM

Discussion

09:30 AM
10:00 AM

Break

10:00 AM
10:15 AM
Samuel Isaacson - The Influence of Spatial Variation in Chromatin Density on the Time to Find DNA Binding Sites

We will describe our recent work investigating how volume exclusion due to the spatially varying density of DNA in the nucleus influences the time required for proteins to find DNA binding sites. A lattice master equation model will be derived to approximate the drift-diffusion process a protein undergoes as it searches for a binding site. Detailed three-dimensional simulations of the protein's search process will then be constructed using several different types of high-resolution imaging of the interior of mammalian cell nuclei. Using asymptotic expansions, we will develop a mathematical theory to explain our observed simulation results.

10:15 AM
10:30 AM

Discussion

10:30 AM
10:45 AM
Sharon Amacher - Tissue patterning with RNA oscillations: single cell resolution imaging of segmentation clock dynamics

Tissue patterning with RNA oscillations: single cell resolution imaging of segmentation clock dynamics

10:45 AM
11:00 AM

Discussion

11:00 AM
11:15 AM
Hildur Knutsdottir - Is 3 the magic number? Exploring the EGF/CSF-1 paracrine signaling between macrophages and tumor cells

Experiments have demonstrated that macrophages are directly involved in the invasion of breast tumor cells into surrounding tissues and blood vessels. The macrophages interact with tumor cells via an EGF/CSF-1 paracrine signaling loop. We developed a 3D individual cell based computational model to study the interaction between macrophages and breast tumor cells and to understand the observed streaming motility pattern. This model incorporates the paracrine signaling loop between tumor cells and macrophages and the cells are simulated as freely moving discrete deformable ellipsoids. This simplified model is sufficient to reproduce results from both in vitro and in vivo experiments (Goswami et al., Cancer Res, 2005; Wyckoff et al. Cancer Res, 2004). The model suggests that the removal of the signaling molecules, by for instance matrix metalloproteases (MMPs) and/or endocytosis, is essential to produce the noted ratio of 3 invasive tumor cells per 1 invasive macrophage. A parametric sensitivity analysis revealed that the invasive ratio between tumor cells and macrophages is robust to changes in most model parameters. An exception to this robustness is that changes in the degradation and secretion rates of EGF and CSF-1 can alter and even eliminate the invasion of tumor cells.

11:15 AM
11:30 AM

Discussion

11:30 AM
12:00 PM

Break/Poster Session Last View

12:00 PM

Shuttle pick-up from MBI (One to Hotel/One to Airport)

Name Affiliation
Alber, Mark malber@nd.edu Applied Mathematics, University of Notre Dame
Amacher, Sharon amacher.6@osu.edu Molecular Genetics, The Ohio State University
Anderson, Alexander alexander.Anderson@moffitt.org Division of Mathematics, University of Dundee
Barna, Maria mbarna@stanford.edu Developmental Biology and Genetics, Stanford University
Bergman, Aviv aviv@einstein.yu.edu Systems and Computational Biology,
Cheng, Yougan yicaiwill@gmail.com Mathematics, Case Western Reserve University
Condeelis, John john.condeelis@einstein.yu.edu Department of Anatomy & Structural Biology, Albert Einstein College of Medicine
Di Talia, Stefano sdi@princeton.edu Cell Biology, Duke University
Dickinson, Mary mdickins@bcm.edu Molecular Physiology & Biophysics, Baylor College of Medicine
Edelstein-Keshet, Leah keshet@math.ubc.ca Mathematics Department, University of British Columbia
Eliceiri, Kevin eliceiri@wisc.edu LOCI, University of WIsconsin at Madison
Gligorijevic, Bojana bojana.gligorijevic@einstein.yu.edu systems & computational biology, albert einstein college of medicine
Hadjantonakis, Anna-Katerina Hadjanta@MSKCC.ORG Developmental Biology Program, Memorial Sloan-Kettering Cancer Center
Henry, Clarissa Clarissa.Henry@umit.maine.edu Biology and Ecology, University of Maine
Hurdal, Monica mhurdal@math.fsu.edu Department of Mathematics, Florida State University
Isaacson, Samuel isaacson@math.bu.edu mathematics and statistics, Boston University
Keely, Patricia pjkeely@wisc.edu Cell and Regenerative Biology, University of Wisconsin
Knutsdottir, Hildur hildur@math.ubc.ca Mathematics, University of British Columbia
Kulesa, Paul pmk@stowers.org Developmental Biology, Stowers Institute for Medical Research
Levenson, Richard levenson@ucdavis.edu Pathology and Laboratory Medicine, University of California Davis
Liebling, Michael liebling@ece.ucsb.edu Electrical and Computer Engineering, University of California Santa Barbara
Lin, Congping congpinglin@gmail.com Mathematics , University of Exeter
Lipkow, Karen KL280@cam.ac.uk Nuclear Dynamics, The Babraham Institute
Maini, Philip maini@maths.ox.ac.uk Centre for Mathematical Biology, Mathematical Institute
McKinney, Mary mck@stowers.org Imaging, Stowers Institute for Medical Research
Mjolsness, Eric emj@uci.edu Department of Computer Science,
Mosaliganti, Kishore kishore_mosaliganti@hms.harvard.edu Department of Systems Biology, Harvard Medical School
Murphy, Robert murphy@cmu.edu Lane Center for Computational Biology, Carnegie-Mellon University
Muschel, Ruth ruth.muschel@rob.ox.ac.uk Oncology, Oxford University
Nowotschin, Sonja nowotscs@mskcc.org Developmental Biology, Sloan-Kettering
Osan, Remus rosan@gsu.edu Mathematics and Statistics, Georgia State University
Page, Karen kpage@math.ucl.ac.uk Mathematics, University College London
Rejniak, Katarzyna Kasia.Rejniak@moffitt.org H. Lee Moffitt Cancer Center & Research Institute, H. Lee Moffitt Cancer Center & Research Institute
Rodriguez-Brenes, Ignacio iarodrig@uci.edu Mathematics, University of California, Irvine
Roysam, Badri broysam@central.uh.edu Electrical & Computer Engineering, University of Houston
Saghian, Rojan rsag063@aucklanduni.ac.nz Engineering, Auckland Bioengineering Institute
Sahai, Erik erik.sahai@cancer.org.uk Tumor Cell Biology Lab, London Research Institute
Saiz Arenales, Nestor saizaren@mskcc.org Developmental Biology, Memorial Sloan-Kettering Cancer Center
Smart, Sean sean.smart@oncology.ox.ac.uk Oncology, Oxford University
Sun, Mingzhai mingzhai@gmail.com Heart and Lung Research Institute, Davis Heart and Lung Research Institute
Sutherland, Ann as9n@virginia.edu Department of Cell Biology, University of Virginia Health System
Tania, Nessy ntania@smith.edu Mathematics and Statistics, Smith College
van Rheenen, Jacco j.vanrheenen@hubrecht.eu Cancer biophyics, Hubrecht Institute and University Medical Center Utrecht
Weijer, Cornelis c.j.weijer@dundee.ac.uk College of Life Sciences, University of Dundee
Multiscale Modeling of Bacterial Swarming

The ability of animals to self-organize into remarkable patterns of movement is seen throughout nature from herds of large mammals, to flocks of birds, schools of fish, and swarms of insects. Remarkably, patterns of collective movement can be seen even in the simplest forms of life such as bacteria. M. xanthus are common soil bacteria that are among the most "social" bacteria in nature. In this talk clustering mechanism of M. xanthus will be described using combination of experimental movies obtained using a novel high-resolution, time-lapse microscopy approach and model simulations [1,2]. Population of bacteria P. aeruginosa, main infection in hospitals, will be also shown to propagate as high density waves that move symmetrically as rings within swarms towards the extending tendrils. Biologically-justified cell-based multiscale model simulations suggest a mechanism of wave propagation as well as branched tendril formation at the edge of the population that depend upon competition between the changing viscosity of the bacterial liquid suspension and the liquid film boundary expansion caused by Marangoni forces [2]. The model predictions of wave speed and swarm expansion rate as well as cell alignment in tendrils were confirmed experimentally

Tissue patterning with RNA oscillations: single cell resolution imaging of segmentation clock dynamics

Tissue patterning with RNA oscillations: single cell resolution imaging of segmentation clock dynamics

Modeling and Imaging of Bacterial Motility

Modeling and Imaging of Bacterial Motility

Revel in the Charm of (Genotypic) Variety, Relish in the Charm of (Phenotypic) Fidelity

Revel in the Charm of (Genotypic) Variety, Relish in the Charm of (Phenotypic) Fidelity.

Motility dynamics during tumor cell dissemination in breast tumors

Multi-photon intravital imaging of single tumor cells in breast tumors has revealed that macrophage-tumor cell pairing and streaming migration occur and this requires paracrine signaling and chemotaxis. Using signals involved in this macrophage-dependent tropism, tumor cells that co-migrate with macrophages have been isolated and expression profiled thereby revealing the pathways used by tumor cells during migration and invasion (the Invasion Signature).


The motility pathways identified in the Invasion Signature converge on the RhoC/Cofilin/Mena pathway which drives both invadopodium (invasive protrusion) formation and locomotory protrusions. Markers derived from this pathway can be used to predict risk of metastasis in breast cancer patients


To understand why the RhoC/Cofilin/Mena pathway predicts metastatic risk, FRET biosensors and multiphoton imaging have been used in vitro and in vivo leading to the following conclusions for breast tumors which will be discussed:



  1. Tumor cell movement during streaming and intravasation involves coordination of locomotory protrusions (pseudopods) and invasive protrusions (invadopodia).

  2. Both protrusions involve actin polymerization at the front of each protrusion in response to macrophage produced EGF.

  3. Cofilin activation is sufficient to determine the site of actin polymerization, protrusion and cell direction.

  4. Mena activity regulates the sensitivity of the EGFR to EGF thereby increasing invadopodium assembly and streaming migration with macrophages.

  5. RhoC/LIMK, Arg kinase, integrin beta1, cortactin, and NHE1 form a signaling complex that regulates the geometry and localization of cofilin activity in both invadopodia and locomotory protrusions determining the shape, size and oscillation of these protrusions during cell migration and invasion.

  6. PI3,4P2 and PI4,5P2 regulate the signaling complex in invadopodia and locomotory protrusions, respectively, demonstrating how the separation and coordination of these two types of protrusions is achieved.

  7. This signaling complex is involved in intravasation and dissemination of tumor cells thus determining the metastatic phenotype of the tumor.

  8. The rate constants for assembly of this complex supplies detailed information that can be used to model the behavior and dynamics of locomotory and invasive protrusions used during tumor cell dissemination.


Imaging dynamic events in vessel remodeling during mouse development

Imaging dynamic events in vessel remodeling during mouse development

Modeling the regulation of cell motility in normal and cancer cells

Cell motility is coordinated by an intricate network of interacting proteins and lipids, that transduce signals into cytoskeletal reorganization, cell shape changes, and locomotion. Here I will survey some mathematical modeling that addresses both normal and aberrant cell motility. I will describe efforts in my group to construct and analyse mathematical models for proteins (such as Rho family GTPases) and lipids (such as phosphoinositides), their feedbacks and their effects on protrusion and contraction of the cell front and rear, as well as cell shape. The role of the cytoskeleton and its actin-associated proteins (e.g. cofilin) will be mentioned. I will describe how several projects on cell polarity and GTPase spatial patterns have contributed to some insights into cell motility.

Tumor cell motility and invadopodia in microenvironment context

During the metastasis, tumor cells move through the primary tumor and enter blood vessels (1). Tumor cell motility has been previously investigated in details in vitro and the signaling pathways which control locomotion in 2D or invadopodia formation, which results in extracellular matrix degradation and penetration, have been dissected (2,3). However, the conditions for the onset of such movements in vivo are not yet fully understood. Using multiphoton-based intravital microscopy we previously reported that the vicinity of macrophages (4) or blood vessels (5) is essential for tumor cell locomotion to occur in primary breast tumors. Yet other studies have demonstrated that the changes in stiffness (6) and architecture (7) of extracellular matrix may lead to increased motility and subsequently, metastasis. However, each of these factors has been studied separately and no attention was given to their combinatorial effect. Here we show that multiparametric, systems-level analysis is vital to predict tumor cell motility-related behaviors in vivo. Our analysis reveals the context in which invadopodia or tumor cell locomotion appear in vivo. Direct link was found between invadopodia number and lung metastasis. To predict invadopodium formation, which leads to intravasation, we conclude, microenvironmental conditions must be studied in concert rather than in isolation. Furthermore, future development of diagnostic markers for early metastasis will most likely necessitate such multiparametric analyses

NAD+ biosynthesis ameliorates muscular dystrophy in zebrafish

NAD+ biosynthesis ameliorates muscular dystrophy in zebrafish

The Influence of Spatial Variation in Chromatin Density on the Time to Find DNA Binding Sites

We will describe our recent work investigating how volume exclusion due to the spatially varying density of DNA in the nucleus influences the time required for proteins to find DNA binding sites. A lattice master equation model will be derived to approximate the drift-diffusion process a protein undergoes as it searches for a binding site. Detailed three-dimensional simulations of the protein's search process will then be constructed using several different types of high-resolution imaging of the interior of mammalian cell nuclei. Using asymptotic expansions, we will develop a mathematical theory to explain our observed simulation results.

Imaging Approaches in Collagen Alignment

Imaging Approaches in Collagen Alignment

Is 3 the magic number? Exploring the EGF/CSF-1 paracrine signaling between macrophages and tumor cells

Experiments have demonstrated that macrophages are directly involved in the invasion of breast tumor cells into surrounding tissues and blood vessels. The macrophages interact with tumor cells via an EGF/CSF-1 paracrine signaling loop. We developed a 3D individual cell based computational model to study the interaction between macrophages and breast tumor cells and to understand the observed streaming motility pattern. This model incorporates the paracrine signaling loop between tumor cells and macrophages and the cells are simulated as freely moving discrete deformable ellipsoids. This simplified model is sufficient to reproduce results from both in vitro and in vivo experiments (Goswami et al., Cancer Res, 2005; Wyckoff et al. Cancer Res, 2004). The model suggests that the removal of the signaling molecules, by for instance matrix metalloproteases (MMPs) and/or endocytosis, is essential to produce the noted ratio of 3 invasive tumor cells per 1 invasive macrophage. A parametric sensitivity analysis revealed that the invasive ratio between tumor cells and macrophages is robust to changes in most model parameters. An exception to this robustness is that changes in the degradation and secretion rates of EGF and CSF-1 can alter and even eliminate the invasion of tumor cells.

Image analysis and pathology: the raw and the cooked - and some stuff on multiplexing

Image analysis and pathology: the raw and the cooked - and some stuff on multiplexing

Decoupling morphogenetic tissue deformations from functional motion in cardiac development

Live microscopy allows observing rapidly moving samples, such as whole embryos during their development. Motion can be local (e.g. individual cells migrating, dividing, or contracting) or more global (e.g. induced by tissue growth or organ function). When the observed motion is induced by more than a single process or occurs at multiple temporal and spatial scales, subtler motions and events are often hidden among more prominent, but unrelated, motions patterns. For example, within the beating and developing heart, cells undergo both rapid, periodic motions as the heart contracts to pump blood and also slower motions as the cells rearrange during maturation of the heart. In this talk, I will discuss in vivo image acquisition, processing, and analysis tools that we developed to digitally document both the morphogenesis and the function of the developing heart. Specifically, I will present our strategy to capture and integrate heterogeneous data acquired with multiple microscopy modalities (including fluorescence microscopy and optical coherence tomography), at multiple temporal and spatial scales (from milliseconds to hours and from single cells to entire organs, respectively), and in multiple dimensions. This allowed us to observe cellular division on the surface of the beating heart without the need to ever slow or stop it, demonstrating the possibility of disentangling complex motion patterns through customized imaging and digital post-processing strategies.

Functional and Spatial Characterisation of Chromatin States in S. cerevisiae

The DNA of all eukaryotes is present in the nucleus as chromatin, in which DNA is closely associated with hundreds of different proteins. The precise combination at a given location determines how a gene is regulated. Experimentally measuring this protein distribution results in extensive datasets that are impossible to interpret by eye. We have applied a newly developed method to analyse chromatin from the model organism S. cerevisiae (bakers yeast). By carefully reducing the complexity of the original data, we identified five distinct chromatin states. These states differ in relevant biological properties, such as enrichment of gene ontologies. They form no detectable pattern in 1D along the chromosomes, but co-localise in 3D. To our surprise, much of the chromatin is poised, ready for change, under both standard and heat stressed conditions. This highlights the great dynamic capability of gene regulation, and how much is learned when taking a Systems view.

Modelling Collective Cell Motion in Biology

Modelling Collective Cell Motion in Biology

Learning Generative Models of the Dynamics of Cell Shape and Organization Changes

Given the complexity of biological systems, machine-learning methods are critically needed for building systems models of cell and tissue behavior and for studying their perturbations. Such models require accurate information about the subcellular distributions of proteins, RNAs and other macromolecules in order to be able to capture and simulate their spatiotemporal dynamics. Microscope images provide the best source of this information, and we have developed tools to build generative models of cell organization directly from such images. Generative models are capable of producing new instances of a pattern that are expected to be drawn from the same underlying distribution as those it was trained with. Our open source system, CellOrganizer (http://CellOrganizer.org), currently contains components that can build probabilistic generative models of cell, nuclear and organelle shape, organelle position, and microtubule distribution. These models capture heterogeneity within cell populations, and can be dependent upon each other and be combined to create new higher level models. The parameters of these models can be used as a highly interpretable basis for analyzing perturbations (e.g., induced by drug addition), and generative models of cell organization can be used as a framework for cell simulations to identify mechanisms underlying cell behavior. Results for analysis of systems ranging from neuronal differentiation to perturbation of plant protoplast organization will be presented.

Hypoxia and Radiation Therapy

Tissue oxygen concentrations are created by a balance between oxygen delivery and oxygen consumption. Tumors consistently have regions of extreme hypoxia. These areas of hypoxia are generated by inadequate oxygen delivery due to the inadequate structure of tumor vasculature leading to inadequate perfusion. Hypoxia has profound effects on cancer progression and metastasis. Radiation therapy is particularly adversely affected because hypoxia greatly reduces its effectiveness, both due to the requirement for oxygen to fix DNA damage and to the biological consequences of hypoxia. As a consequence considerable effort has been made to reduce the extent of hypoxia during radiation therapy. The most extensive efforts however have focused upon altering oxygen delivery, either by carbogen breathing or improving perfusion with limited success. Here we will discuss reduction of oxygen consumption as a means to achieve the same goal. As expected reduction in oxygen consumption leads to reduced hypoxia. We further demonstrate the possibility of improving the outcome of radiation therapy by this means.

Mathematical modelling of vertebrate neural tube patterning

A major challenge in developmental biology is to understand the mechanisms of pattern formation. Morphogens provide the positional information that organises gene expression and cell differentiation in many developing tissues. Conventional views say they induce distinct responses in a concentration-dependent manner. But signal duration has also been implicated in determining cellular responses. Here we establish how both the level and duration of signaling by the morphogen Sonic Hedgehog (Shh) control patterning in the vertebrate neural tube. Morphogen signaling is interpreted by a transcriptional regulatory circuit that links Shh signaling to three transcription factors. We present the circuit and equations to describe the levels of the transcription factors within a cell. We show that the design of this circuit unifies the temporal and graded response to Shh signaling. It also renders cells insensitive to transient increases in Shh signalling and confers hysteresis - memory of the signal. These results are experimentally verified. We discuss alternative behaviours of the gene regulatory network.

Mathematical modeling and biomedical imaging of anti-cancer drug penetration

The interactions between tumor cells and their microenvironment are complex, and this complexity is leveraged when both tumor and stromal cells are exposed to anticancer therapeutic agents. We use mathematical modeling and computational simulations to systematically explore the role of tumor tissue architecture and stromal composition on the extent of drug and biomarker molecule penetration into the tissue. An integral part of our approach is the use of various biomedical imaging techniques to both parameterize the models and to validate their results. This is accomplished by close collaboration with cancer biologists and pathologists. In this talk, we present a current state of the computational model integrated with experimental data and calibrated to pancreatic tumor xenografts that aim on providing an analytical tool in designing drug properties and drug administration schedules that will optimize drug penetration into the tumor tissue and enhance their therapeutic efficacy.

Computational Discovery of Events & Phenomena from Microscopy Image Data

Computationally delineating complex biological structures in fluorescence microscopy images, also known as segmentation, is increasingly maturing to the point of becoming an operational tool for rapid and accurate morphometry. Multiplexed fluorescence imaging allows associative measurements relating multiple structures. Increasingly also, the ability to track moving structures in live time-lapse microscopy data is also advancing rapidly, and emerging as a tool for quantifying dynamic processes in cells and tissue. Combining multiplex fluorescence with time-lapse allows multiple phenomena to be imaged in a manner that preserves their relative context. In addition, gene and protein arrays have matured into routine tools for measuring the molecular profile of tissue specimens. Overall, the resulting measurements of structures, molecular signatures, and activities take the form of high-dimensional multi-variate datasets that are rich in terms of trends, events, and relationships. In this talk, I will describe progress in the development and integration of multivariate analytics tools into image analysis systems, specifically, the open source FARSIGHT toolkit (www.farsight-toolkit.org), to sense and extract these patterns. These capabilities are broadly useful in advancing quantitative biology, and I will draw upon examples from neuroscience and immunology to illustrate these methods.

Modelling cell migration in different matrix geometries

Modelling cell migration in different matrix geometries

In vivo Study of the Intact Mouse by Non-Invasive Tomographic Imaging

In vivo Study of the Intact Mouse by Non-Invasive Tomographic Imaging

Distinct apical and basolateral mechanisms drive PCP-dependent convergent extension of the mouse neural plate

The early embryo, which generally begins as a sphere or a disc, forms an elongated body axis through the mass tissue movements of convergence and extension (CE). While the mechanisms driving CE are well described in the frog and fish, our understanding of CE and the resulting axial elongation forces in mammalian embryos is still rudimentary. We have shown by direct observation that the paraxial mesoderm of murine embryos undergoes CE by mediolaterally polarized cell intercalation driven by bipolar protrusive activity. CE has also been implicated as a mechanism driving elongation and closure of the neural tube, but the underlying cellular behaviors leading to epithelial cell rearrangement in this tissue have not been identified.


To determine what cell behaviors lead to neural CE in the mouse, we examined the neural plate of live, fluorescently labeled embryos using time-lapse confocal microscopy. We have found that mouse neural epithelial cells undergo mediolaterally biased cell intercalation and exhibit both apical boundary rearrangement and polarized basolateral protrusive activity, both of which contribute to cell intercalation. Planar polarization and coordination of these two cell behaviors is essential for neural CE, as shown by failure of mediolateral intercalation in embryos mutant for two proteins associated with planar cell polarity signaling: Vangl2 and Ptk7. Embryos with mutations in Ptk7 fail to polarize cell behaviors within the plane of the tissue, while Vangl2 Lp mutant embryos maintain tissue polarity and basal protrusive activity, but are deficient in apical neighbor exchange. These results reveal a novel cooperative cellular mechanism for cell rearrangement during epithelial morphogenesis.

Modeling the regulation of cofilin and actin based protrusion in invasive tumor cells

Modeling the regulation of cofilin and actin based protrusion in invasive tumor cells

Intravital Microscopy of Cancer Cell Plasticity Through Imaging Windows

Complications due to metastasis, the process where cells detach from a primary tumor to form new tumors at distant sites, are the primary reason why people die from cancer. Although histological techniques have provided important information on metastasis, they only give a static image of tumor cells and their microenvironment and thus compromise interpretation of this dynamic process. To study this dynamic process, we visualize the behavior of single metastasizing cells at subcellular resolution with two-photon intravital imaging (IVM). We have recently developed a Mammary Imaging Window (MIW) to image primary mammary tumors over multiple days. By combing the MIW with fluorescent lineage tracing tools, we intravitally lineage traced mammary tumors growth. Our intravital lineage tracing experiments showed the existence of a small population of cells, referred to as cancer stem cells (CSCs), that maintains and provides growth. Moreover, our experiments illustrated existing CSCs disappear and new CSCs form during mammary tumor growth, illustrating the dynamic nature of these cells.

In order to study how tumor cells arrive, survive and grow at secondary sites, we developed a new imaging window to image abdominal organs such as the liver, which is one of the primary organs for metastasis formation. Using this abdominal imaging window, we are able to visualize how individual tumor cells that arrive at the liver grow into metastases. We observe that single extravasated tumor cells proliferate and form 'pre-micrometastases' in which cells are migratory and lack contact to neighboring tumor cells. Subsequently, the clones condense into micrometastases in which cell migration is strongly diminished, but proliferation continues. By suppressing tumor cell migration in pre-micrometastases genetically or by drugs we reduce the number of metastases, and therefore we conclude that the migration of cells within pre-micrometastases is a novel contributing step in the formation of liver metastasis.

Cellular mechanisms underlying the formation of the primitive streak formation in the chick embryo

The mechanisms controlling the formation of the primitive streak in amniote embryos are still not understood. In the chick embryo it has been shown that streak formation involves extensive large scale counter rotating cell flows in the epiblast that merge at the position of the forming streak and which transport the forming mesoderm in the midline of the embryo. Simultaneous with the formation of the streak, the hypoblast develops and extends in anterior direction. Based on experimental observations and modelling studies it has been suggested that streak formation could result from chemotaxis, local cell-cell intercalation and or oriented division. However detailed quantitative data on cell behaviours to back up any of these hypothesis are still lacking. The cells in the epiblast form a highly polarised epithelial sheet and the cells are connected through well developed apical adherens and tight junctions. It remains to be determined by which mechanisms the cells in the epiblast and forming streak move and how much relative cell movement exists. To answer some of the questions and study most cells in the embryo (3-4 mm across) we have developed a dedicated light sheet microscope that in combination with the availability of a new transgenic chick line that expresses a membrane targeted GFP now allows us to investigate cellular dynamics during streak formation in great detail. We will describe our recent findings made using these new tools. The results obtained support a novel mechanism for streak formation based on localised shape changes resulting in ingression as well as intercalation of mesendoderm cells. We will discuss our current ideas of the mechanisms underlying and coordinating these processes and discuss some of the open questions

Posters

A Spatially Distributed Model of Brain energy Metabolism

In the modeling literature, brain energy metabolism has been approached in the framework of spatially lumped models, where the region of interest is represented as in terms of well mixed compartments representing different cell types, extracellular space and capillary blood [1], [2]. While these models shed some light on the brain metabolism, they overlook some potentially important factors including the locus of the synaptic activity in reference to capillaries, the effect of diffusion, pre- and postsynaptic neurons, and possible variations in mitochondrial density within the cells. Intuitively, the different availability of oxygen and glucose away from the blood vessel could determine the cells' aerobic or anaerobic metabolism and trigger the uptake of lactate, highlighting the important role of diffusion.

We propose a spatially distributed metabolism model that better takes into account the aforementioned factors. The model is based on the idea of a multi-domain reaction-diffusion system, akin to the bi-domain models of myocardium [3]. The spatially lumped model is derived as a mean of the distributed one, and we use it to investigate the effect of different activation scenarios on the parameter distribution of the lumped model, deriving a lower dimensional distributed model based on the general three-dimensional model. We also reduce the lower dimensional distributed model further from a continuous model to a discretized model analog to the methods of lines, solving the corresponding system of partial differential equations (PDE) by solving a system of ordinary differential equations (ODE).

The numerical simulations suggest that: (1) At steady state, the oxygen glucose index (OGI) of the discretized subunit decreases when it moves away from the capillaries; (2) When the locus of the synaptic activity in reference to capillaries changes, the dynamical behavior of the system (the substrate concentration dynamics, the reaction flux flow and the transport flux flow) changes substantially; (3) Some of the parameters values for the corresponding lumped model change considerably when the locus of the synaptic activity changes in reference to the capillary location. The results suggest that the lumped models incorporating the same metabolic pathways could behave differently as the locus of the synaptic activity in reference to capillaries changes, compensating with the parameter values for the lack of spatial resolution. This may explain why the parameter values of the same reaction/transport are sensitive to the settings of the lumped model. To look into these questions in more details, we need to simulate the system in high dimension using finite element methods. The work is under development.

Quantifying Dynamic Cell Shape and Neighbor Relationships During Neural Crest Migration

Quantifying Dynamic Cell Shape and Neighbor Relationships During Neural Crest Migration

video image

NAD+ biosynthesis ameliorates muscular dystrophy in zebrafish
Clarissa Henry

NAD+ biosynthesis ameliorates muscular dystrophy in zebrafish

video image

Decoupling morphogenetic tissue deformations from functional motion in cardiac development
Michael Liebling

Live microscopy allows observing rapidly moving samples, such as whole embryos during their development. Motion can be local (e.g. individual cells migrating, dividing, or contracting) or more global (e.g. induced by tissue growth or organ f

video image

Tumor cell motility and invadopodia in microenvironment context
Bojana Gligorijevic

During the metastasis, tumor cells move through the primary tumor and enter blood vessels (1). Tumor cell motility has been previously investigated in details in vitro and the signaling pathways which control locomotion in 2D or invadopodia

video image

Modeling the regulation of cofilin and actin based protrusion in invasive tumor cells
Nessy Tania

Modeling the regulation of cofilin and actin based protrusion in invasive tumor cells

video image

Modeling the regulation of cell motility in normal and cancer cells
Leah Edelstein-Keshet

Cell motility is coordinated by an intricate network of interacting proteins and lipids, that transduce signals into cytoskeletal reorganization, cell shape changes, and locomotion. Here I will survey some mathematical modeling that addresse