Browsing by Author "Tsarfaty, Ilan"

Now showing 1 - 5 of 5
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    Live time-lapse dataset ofﾠin vitroﾠwound healing experiments
    (Oxford University Press, 2015) Zaritsky, Assaf; Natan, Sari; Kaplan, Doron; Ben-Jacob, Eshel; Tsarfaty, Ilan
    Background: The wound healing assay is the common method to study collective cell migration in vitro. Computational analyses of live imaging exploit the rich temporal information and significantly improve understanding of complex phenomena that emerge during this mode of collective motility. Publicly available experimental data can allow application of new analyses to promote new discoveries, and assess algorithms’ capabilities to distinguish between different experimental conditions. Findings: A freely-available dataset of 31 time-lapse in vitro wound healing experiments of two cell lines is presented. It consists of six different experimental conditions with 4–6 replicates each, gathered to study the effects of a growth factor on collective cell migration. The raw data is available at ‘The Cell: an Image Library’ repository. This Data Note provides detailed description of the data, intermediately processed data, scripts and experimental validations that have not been reported before and are currently available at GigaDB. This is the first publicly available repository of live collective cell migration data that includes independent replicates for each set of conditions. Conclusions: This dataset has the potential for extensive reuse. Some aspects in the data remain unexplored and can be exploited extensively to reveal new insight. The dataset could also be used to assess the performance of available and new quantification methods by demonstrating phenotypic discriminatory capabilities between the different experimental conditions. It may allow faster and more elaborated, reproducible and effective analyses, which will likely lead to new biological and biophysical discoveries.
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    Modeling the Transitions between Collective and Solitary Migration Phenotypes in Cancer Metastasis
    (Macmillan Publishers Limited, 2015) Huang, Bin; Jolly, Mohit Kumar; Lu, Mingyang; Tsarfaty, Ilan; Ben-Jacob, Eshel; Onuchic, José Nelson; Bioengineering; Biosciences; Chemistry; Physics and Astronomy; Center for Theoretical Biological Physics
    Cellular plasticity during cancer metastasis is a major clinical challenge. Two key cellular plasticity mechanisms —Epithelial-to-Mesenchymal Transition (EMT) and Mesenchymal-to-Amoeboid Transition (MAT) – have been carefully investigated individually, yet a comprehensive understanding of their interconnections remains elusive. Previously, we have modeled the dynamics of the core regulatory circuits for both EMT (miR-200/ZEB/miR-34/SNAIL) and MAT (Rac1/RhoA). We now extend our previous work to study the coupling between these two core circuits by considering the two microRNAs (miR-200 and miR-34) as external signals to the core MAT circuit. We show that this coupled circuit enables four different stable steady states (phenotypes) that correspond to hybrid epithelial/mesenchymal (E/M), mesenchymal (M), amoeboid (A) and hybrid amoeboid/mesenchymal (A/M) phenotypes. Our model recapitulates the metastasis-suppressing role of the microRNAs even in the presence of EMT-inducing signals like Hepatocyte Growth Factor (HGF). It also enables mapping the microRNA levels to the transitions among various cell migration phenotypes. Finally, it offers a mechanistic understanding for the observed phenotypic transitions among different cell migration phenotypes, specifically the Collective-to-Amoeboid Transition (CAT).
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    The motility-proliferation-metabolism interplay during metastatic invasion
    (Nature Publishing Group, 2015) Hecht, Inbal; Natan, Sari; Zaritsky, Assaf; Levine, Herbert; Tsarfaty, Ilan; Ben-Jacob, Eshel; Center for Theoretical Biological Physics
    Metastasis is the major cause for cancer patients’ death, and despite all the recent advances in cancer research it is still mostly incurable. Understanding the mechanisms that are involved in the migration of the cells in a complex environment is a key step towards successful anti-metastatic treatment. Using experimental data-based modeling, we focus on the fundamentals of metastatic invasion: motility, invasion, proliferation and metabolism, and study how they may be combined to maximize the cancer’s ability to metastasize. The modeled cells’ performance is measured by the number of cells that succeed in migration in a maze, which mimics the extracellular environment. We show that co-existence of different cell clones in the tumor, as often found in experiments, optimizes the invasive ability in a frequently-changing environment. We study the role of metabolism and stimulation by growth factors, and show that metabolism plays a crucial role in the metastatic process and should therefore be targeted for successful treatment.
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    The three-way switch operation of Rac1/RhoA GTPase-based circuit controlling amoeboid-hybrid-mesenchymal transition
    (Nature Publishing Group, 2014) Huang, Bin; Lu, Mingyang; Jolly, Mohit Kumar; Tsarfaty, Ilan; Onuchic, José Nelson; Ben-Jacob, Eshel; Bioengineering; Biosciences; Chemistry; Physics and Astronomy; Center for Theoretical Biological Physics
    Metastatic carcinoma cells exhibit at least two different phenotypes of motility and invasion - amoeboid and mesenchymal. This plasticity poses a major clinical challenge for treating metastasis, while its underlying mechanisms remain enigmatic. Transitions between these phenotypes are mediated by the Rac1/RhoA circuit that responds to external signals such as HGF/SF via c-MET pathway. Using detailed modeling of GTPase-based regulation to study the Rac1/RhoA circuit's dynamics, we found that it can operate as a three-way switch. We propose to associate the circuit's three possible states to the amoeboid, mesenchymal and amoeboid/mesenchymal hybrid phenotype. In particular, we investigated the range of existence of, and the transition between, the three states (phenotypes) in response to Grb2 and Gab1 - two downstream adaptors of c-MET. The results help to explain the regulation of metastatic cells by c-MET pathway and hence can contribute to the assessment of possible clinical interventions.
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    Tumor Invasion Optimization by Mesenchymal-Amoeboid Heterogeneity
    (Springer Nature, 2015) Hecht, Inbal; Bar-El, Yasmin; Balmer, Frederic; Natan, Sari; Tsarfaty, Ilan; Schweitzer, Frank; Ben-Jacob, Eshel; Center for Theoretical Biological Physics
    Metastasizing tumor cells migrate through the surrounding tissue and extracellular matrix toward the blood vessels, in order to colonize distant organs. They typically move in a dense environment, filled with other cells. In this work we study cooperative effects between neighboring cells of different types, migrating in a maze-like environment with directional cue. Using a computerized model, we measure the percentage of cells that arrive to the defined target, for different mesenchymal/amoeboid ratios. Wall degradation of mesenchymal cells, as well as motility of both types of cells, are coupled to metabolic energy-like resource level. We find that indirect cooperation emerges in mid-level energy, as mesenchymal cells create paths that are used by amoeboids. Therefore, we expect to see a small population of mesenchymals kept in a mostly-amoeboid population. We also study different forms of direct interaction between the cells, and show that energy-dependent interaction strength is optimal for the migration of both mesenchymals and amoeboids. The obtained characteristics of cellular cluster size are in agreement with experimental results. We therefore predict that hybrid states, e.g. epithelial-mesenchymal, should be utilized as a stress-response mechanism.