Our research draws on a wide range of methodologies and disciplines, including biological and chemical engineering, cell and developmental biology, mathematical modeling, molecular biology and quantitative biochemistry and imaging. These multidisciplinary activities are undertaken by a talented and creative group of students from chemical engineering, bioengineering, biochemistry and molecular biophysics. Several projects involve collaborations with colleagues in chemistry, biology, bioengineering and electrical engineering. Learn more below...
Project Areas:
1. Molecular and cellular crosstalk during developmental patterning
Students: Claudiu Giurumescu (ChE)
Collaborators: Prof. Paul Sternberg (Biology), Prof. Changhuei Yang (EE)
The most remarkable example of multicellular structure formation is the development of an organism from a fertilized egg. Many of the molecular networks guiding the development of simple organisms, such as the worm C. elegans, also operate in human cells. Thus, these model organisms offer a powerful system to parse molecular signals involved in multicellular patterning.
We have focused on an intriguing stage in C. elegans development where cell patterning depends not only on a spatial gradient in a soluble factor (a morphogen), but also on direct cell-cell interactions [Giurumescu et. al. (2006) PNAS]. In fact, these two extracellular signals are coupled by an intracellular signaling network of biochemical reactions. We have developed a mathematical model to analyze how this coupling benefits multicellular patterning. Our analysis reveals that coupling enhances cell preception of the extracellular gradient, so that a gradient in the soluble factor outside the cells produces an even steeper gradient in intracellular signals. Such gradient amplification may play a crucial role in patterning over moderate length scales, where a substantial morphogen gradient may not be established. These model predictions are being validated using a quantitative imaging platform with animals where coupling is preserved (wild-type) or ablated by molecular genetics and RNAi.
In addition to elucidating quantitative advantages in signal processing, we have developed a parameter-unbiased, computational framework that accurately predicts wild-type and mutant phenotypes [Giurumescu et. al., in preparation]. Since this framework predicts phenotype, it provides a unique opportunity to pursue genetics type questions in silico. For example, our model identifies perturbations (mutations) that convert a wild-type phenotype into an alternative multicellular pattern. Using this approach, we have identified distinct single-mutations that yield the same phenotypic change, thereby revealing functional equivalents in the molecular network. This computational approach also provides access to experimentally intractable questions, such as what are all the possible phenotypes that this network will permit, and among these, what mutations yield novel outcomes?
Collaborators: Prof. Paul Sternberg (Biology), Prof. Changhuei Yang (EE)
The most remarkable example of multicellular structure formation is the development of an organism from a fertilized egg. Many of the molecular networks guiding the development of simple organisms, such as the worm C. elegans, also operate in human cells. Thus, these model organisms offer a powerful system to parse molecular signals involved in multicellular patterning.
We have focused on an intriguing stage in C. elegans development where cell patterning depends not only on a spatial gradient in a soluble factor (a morphogen), but also on direct cell-cell interactions [Giurumescu et. al. (2006) PNAS]. In fact, these two extracellular signals are coupled by an intracellular signaling network of biochemical reactions. We have developed a mathematical model to analyze how this coupling benefits multicellular patterning. Our analysis reveals that coupling enhances cell preception of the extracellular gradient, so that a gradient in the soluble factor outside the cells produces an even steeper gradient in intracellular signals. Such gradient amplification may play a crucial role in patterning over moderate length scales, where a substantial morphogen gradient may not be established. These model predictions are being validated using a quantitative imaging platform with animals where coupling is preserved (wild-type) or ablated by molecular genetics and RNAi.
In addition to elucidating quantitative advantages in signal processing, we have developed a parameter-unbiased, computational framework that accurately predicts wild-type and mutant phenotypes [Giurumescu et. al., in preparation]. Since this framework predicts phenotype, it provides a unique opportunity to pursue genetics type questions in silico. For example, our model identifies perturbations (mutations) that convert a wild-type phenotype into an alternative multicellular pattern. Using this approach, we have identified distinct single-mutations that yield the same phenotypic change, thereby revealing functional equivalents in the molecular network. This computational approach also provides access to experimentally intractable questions, such as what are all the possible phenotypes that this network will permit, and among these, what mutations yield novel outcomes?
2. Molecular networks and cell-cell interactions in the formation of human epithelial cell structures
Students: Nicholas Graham (ChE), Melissa Pope (BE), Jin-Hong Kim (BE)
The interplay between soluble factors and cell-cell contact observed during C. elegans development (above) is also critical in mammalian cell systems. A prominent example involves epithelial tissues where cells directly adjoin their neighbors to form a multicellular sheet that often serves as a barrier. In these tissues, cell-cell contact not only physically tethers together neighboring cells, but also encodes biochemical signals that inhibit cell behaviors such as proliferation. This contact-inhibition of proliferation overrides growth-promoting signals from soluble factors. Mutations that disrupt contact-inhibition leads to chaotic cell proliferation, a hallmark of cancer cells.
Our lab is elucidating the molecular signals governing contact-inhibition. We discovered that a growth-promoting factor (EGF) stimulates proliferation by utilizing a signaling protein (b-catenin) that normally associates with cell-cell contacts [Graham et. al. (2004) J. Biol. Chem.]. We have further delineated the molecular network by which EGF titrates b-catenin from cell-cell contacts to promote cell proliferation [Graham et. al., in preparation]. Our lab is now investigating how disruptions to this network affects contact-inhibition and the formation of epithelial multicellular structures, both in two-dimensional and three-dimensional cultures.
The interplay between soluble factors and cell-cell contact observed during C. elegans development (above) is also critical in mammalian cell systems. A prominent example involves epithelial tissues where cells directly adjoin their neighbors to form a multicellular sheet that often serves as a barrier. In these tissues, cell-cell contact not only physically tethers together neighboring cells, but also encodes biochemical signals that inhibit cell behaviors such as proliferation. This contact-inhibition of proliferation overrides growth-promoting signals from soluble factors. Mutations that disrupt contact-inhibition leads to chaotic cell proliferation, a hallmark of cancer cells.
Our lab is elucidating the molecular signals governing contact-inhibition. We discovered that a growth-promoting factor (EGF) stimulates proliferation by utilizing a signaling protein (b-catenin) that normally associates with cell-cell contacts [Graham et. al. (2004) J. Biol. Chem.]. We have further delineated the molecular network by which EGF titrates b-catenin from cell-cell contacts to promote cell proliferation [Graham et. al., in preparation]. Our lab is now investigating how disruptions to this network affects contact-inhibition and the formation of epithelial multicellular structures, both in two-dimensional and three-dimensional cultures.
3. Physical platforms for programming mammalian cell behaviors and patterns
Students: Niki Galownia (ChE), Melissa Pope (BE), Keiichiro Kushiro (BMB)
Collaborators: Prof. Pat Collier (Chemistry), Prof. Ravi Kane (RPI, ChE), Prof. David Tirrell (Chemistry & ChE)
The physical interactions of a cell with its microenvironment provides structural scaffolding for multicellular structures. Cell-cell interactions provide part of this structural support; in addition, cells adhere to an extracellular solid-state matrix of proteins. Much like cell-cell interactions, cell-matrix adhesion is not only a physical event, but also stimulates intracellular biochemical signals that regulate cell behaviors. For example, cell proliferation and survival require adhesion to an extracellular protein matrix.
Engineering synthetic matrices that elicit similar control over cell behaviors is a major challenge in tissue engineering. Designing such "smart" materials is limited by our nascent undestanding of how cells perceive and respond to bioactive materials. Our lab takes a quantitative approach in analyzing cell responses to materials whose biochemical and physical properties are tunable and well-characterized. This approach has revealed quantitative metrics for gauging how effectively a biomaterial supports cell adhesion and spreading [Richman et. al. (2005) J. Controll. Rel.]. Quantifying cell reactions to biomaterials has also uncovered unexpected results. We have found that contrary to the general paradigm, cell adhesion to matrix proteins may not always improve cell response. Rather, it can have the opposite effect of desensitizing cells [Galownia et. al., in preparation]. How the cell chooses between these two extremes -- priming versus desensensitization -- depends on the biochemical signals involved and their dynamics. This quantitative insight into how cells perceive and respond to adhesive materials offers design principles for engineering smart biomaterials for tissue engineering applications.
4. Predictive synthetic biology: re-engineering molecular circuits using a modeling-guided approach
Collaborators: Prof. Pat Collier (Chemistry), Prof. Ravi Kane (RPI, ChE), Prof. David Tirrell (Chemistry & ChE)
The physical interactions of a cell with its microenvironment provides structural scaffolding for multicellular structures. Cell-cell interactions provide part of this structural support; in addition, cells adhere to an extracellular solid-state matrix of proteins. Much like cell-cell interactions, cell-matrix adhesion is not only a physical event, but also stimulates intracellular biochemical signals that regulate cell behaviors. For example, cell proliferation and survival require adhesion to an extracellular protein matrix.
Engineering synthetic matrices that elicit similar control over cell behaviors is a major challenge in tissue engineering. Designing such "smart" materials is limited by our nascent undestanding of how cells perceive and respond to bioactive materials. Our lab takes a quantitative approach in analyzing cell responses to materials whose biochemical and physical properties are tunable and well-characterized. This approach has revealed quantitative metrics for gauging how effectively a biomaterial supports cell adhesion and spreading [Richman et. al. (2005) J. Controll. Rel.]. Quantifying cell reactions to biomaterials has also uncovered unexpected results. We have found that contrary to the general paradigm, cell adhesion to matrix proteins may not always improve cell response. Rather, it can have the opposite effect of desensitizing cells [Galownia et. al., in preparation]. How the cell chooses between these two extremes -- priming versus desensensitization -- depends on the biochemical signals involved and their dynamics. This quantitative insight into how cells perceive and respond to adhesive materials offers design principles for engineering smart biomaterials for tissue engineering applications.
Students: Stephen Chapman (ChE)
Collaborators: Prof. Ray Deshaies (Biology)
Cell-cell contact, cell-material interactions and other environmental cues induce intracellular signaling pathways that culminate in specific cell responses. Interestingly, diverse stimuli often use a common intracellular signaling pathway to drive cell functions. For example, all the systems studied in our lab (worm, mammalian cells, yeast cells) employ a common intracellular signaling cascade, the MAP kinase pathway. Re-engineering such "common protocols" for signal transduction offers a powerful approach to tune stimuli-response relationships in a wide-range of biological contexts.
An important challenge is that signaling pathways like the MAP kinase cascade involve a sophisticated network of molecular interactions. Thus, it is not intuitive how perturbations in the signaling network will affect its overall performance. To address this challenge, our lab is studying the quantitative effects of manipulating the MAP kinase pathway using yeast cells as a test-bed system. Yeast cells are highly amenable to genetic manipulation and to quantitative biochemical techniques. In parallel, we are developing mathematical models to gain mechanistic insight from our quantitative experimental measurements and to guide future re-design of the MAP kinase pathway [Chapman et. al. (2004) Biotech. & Bioeng.].
Funding:Collaborators: Prof. Ray Deshaies (Biology)
Cell-cell contact, cell-material interactions and other environmental cues induce intracellular signaling pathways that culminate in specific cell responses. Interestingly, diverse stimuli often use a common intracellular signaling pathway to drive cell functions. For example, all the systems studied in our lab (worm, mammalian cells, yeast cells) employ a common intracellular signaling cascade, the MAP kinase pathway. Re-engineering such "common protocols" for signal transduction offers a powerful approach to tune stimuli-response relationships in a wide-range of biological contexts.
An important challenge is that signaling pathways like the MAP kinase cascade involve a sophisticated network of molecular interactions. Thus, it is not intuitive how perturbations in the signaling network will affect its overall performance. To address this challenge, our lab is studying the quantitative effects of manipulating the MAP kinase pathway using yeast cells as a test-bed system. Yeast cells are highly amenable to genetic manipulation and to quantitative biochemical techniques. In parallel, we are developing mathematical models to gain mechanistic insight from our quantitative experimental measurements and to guide future re-design of the MAP kinase pathway [Chapman et. al. (2004) Biotech. & Bioeng.].
Our research is supported by the Jacobs Institute for Molecular Engineering for Medicine, Concern Foundation, National Institutes of Health (NIH), National Science Foundation (NSF), Army Research Office (ARO) and Caltech's Center for Biological Circuit Design.