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    Rational and combinatorial design of biomaterials for tissue engineering applications

    Author
    Ramamoorthy, Sriram
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    177079_Ramamoorthy_rpi_0185E_10805.pdf (5.641Mb)
    Other Contributors
    Karande, Pankaj; Cramer, Steven M.; Kane, Ravi S.; Lee, Sangwoo.; Thompson, Deanna M.;
    Date Issued
    2015-12
    Subject
    Chemical engineering
    Degree
    PhD;
    Terms of Use
    This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.;
    Metadata
    Show full item record
    URI
    https://hdl.handle.net/20.500.13015/1623
    Abstract
    The ability of neurons to regenerate after a peripheral nerve injury is limited by lack of growth permissive microenvironment and presence of glial scar acting as physical and chemical barrier for migration of non-neural cells and axons. An ideal biomaterial for neural regeneration will need to present growth supportive microenvironment for neurite outgrowth, Schwann cell (SC) migration, proliferation and myelination and revascularization. We propose a rational and combinatorial design strategy for screening of base scaffold, extracellular matrix proteins and soluble factors will lead to discovery of optimal biomaterials supporting both neural and non-neural cells. Current macro-scale combinatorial screening approach is cost-prohibitive, labor intensive and limited by prohibitively large experimental space of matrix proteins and growth factors. Moreover, we are limited by tools for high throughput evaluation of cell responses to 3D biomaterials. In this project, we have developed a high throughput platform for generating combinatorial libraries of biomaterials. Our high throughput system comprises of fluid handling elements that create combinatorial libraries by mixing individual components at desired composition and concentration. We describe our approach for evaluating cell responses using a high throughput fluorescent flatbed scanner and an image processing method for analyzing images obtained from scanner. We investigated mouse brain endothelial cell responses (mbEC) to composite collagen and matrigel biomaterials and determined endothelial cell number and spreading is modulated by both collagen and matrigel concentrations. Cell responses obtained from biomaterials fabricated by combinatorial printer correlated well with control biomaterials printed manually.; To summarize, our high throughput combinatorial screening platform enables us to generate a library of combinatorial materials from scaffold, ECM proteins and growth factors and identify lead candidates by assessment of various cell responses.; Taking cues from peripheral nervous tissue microenvironment, we rationally selected candidates for base scaffold, matrix proteins and soluble factors for high throughput combinatorial screening experiments. High throughput screening (HTS) results indicated mbEC response was dependent on the type and concentration of the matrix protein. Laminin was found have a major effect on mbEC followed by fibronectin. Screening results showed growth factors synergistically enhanced mbEC response. HTS platform identified lead biomaterials from combinatorial library fabricated from fibronectin, laminin and collagen I. We also evaluated the responses of human umbilical vein endothelial cells (HUVEC) to collagen matrigel composite biomaterials. The screening results revealed addition of matrigel did not improve HUVEC response and collagen I is the key protein regulating HUVEC responses. In addition to these results, we determined HUVEC capillary formation in collagen – matrigel composite biomaterials is inhibited at higher matrigel concentration. Coculture studies with SC, showed collagen I -20% matrigel composite biomaterial promoted both SC spreading and capillary network formation. Confocal reflectance microscopy analysis showed length of collagen fibers decreased with increasing matrigel content and collagen started accumulating in distinct pockets within the gel. This indicates mechanical properties of the material is also affected by ECM proteins.;
    Description
    December 2015; School of Engineering
    Department
    Dept. of Chemical and Biological Engineering;
    Publisher
    Rensselaer Polytechnic Institute, Troy, NY
    Relationships
    Rensselaer Theses and Dissertations Online Collection;
    Access
    Restricted to current Rensselaer faculty, staff and students. Access inquiries may be directed to the Rensselaer Libraries.;
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