Presentation Title

Collagen Gel as a Scaffold for Mesenchymal Stem Cells and Chitosan Nanoparticles for a Tissue-Engineered Brain Patch to Promote Neural Regeneration

Faculty Mentor

Prof. Orwin

Start Date

18-11-2017 10:00 AM

End Date

18-11-2017 11:00 AM

Location

BSC-Ursa Minor 94

Session

Poster 1

Type of Presentation

Poster

Subject Area

biological_agricultural_sciences

Abstract

Traumatic Brain Injury (TBI) has devastating effects through both the initial trauma and the secondary injury from inflammation. The “Brain Patch” is a tissue-engineered TBI treatment, aimed at reducing secondary injury. The collagen gel patch is infused with antibacterial and anti-inflammatory chitosan nanoparticles (CNPs) and mesenchymal stem cells (MSCs) that encourage regrowth of neural connections. Since the differentiation of MSCs into neural cells is directly affected by the stiffness of the extracellular matrix (ECM)1, characterizing the stiffness of the collagen gel is essential for controlling MSC differentiation. By varying collagen concentration (%w/v) from 0.25%-1.0%, we have been able to reproducibly create gels with compressive bulk stiffnesses from 2-30 kPa, which corresponds to the substrate stiffness that allows MSCs to differentiate into neural cells1 (Fig. 1a). To determine the ideal scaffold conditions, MSCs were cultured on collagen gels with and without retinoic acid (RA) to induce differentiation to neural cells. The best MSC growth conditions were on the 0.25% gels without RA (Fig. 1b). A Western Blot will quantify the neural markers, MAP2 and β-Tubulin, to assess the optimal differentiation conditions. We also determined the effect of MSCs and CNPs on gel stiffness. Initial results show that the addition of CNPs to collagen gels at expected antibacterial concentrations2 does not significantly alter the stiffness of the gels. The addition of MSCs inside the collagen gels significantly increases the gel stiffness (Fig. 1a). Creating collagen gels within appropriate stiffness ranges and characterizing the effects of CNPs and MSCs on the stiffness in order to induce neural differentiation while maintaining antibacterial properties is a groundbreaking step towards engineering a Brain Patch.

Figure 1. a) Stiffness of 0.5% collagen gels infused with varying concentrations of MSCs; b) Bradford Assay results of 0.25% and 1% collagen gels, with and without retinoic acid, indicating total protein of samples when cultured with retinoic acid. Higher protein concentration corresponds to higher cell number.

References:

  1. Engler, AJ et. al, Cell, 2006, 126, pp. 677-689.

  2. Qi, L et al, Carbohydr Res, 2004, 339, pp. 2693-2700.

Summary of research results to be presented

This research lays the groundwork to eventually incorporate CNPs and MSCs into collagen gels to form a Brain Patch. The mechanical testing shows that the gels are in the correct stiffness range for neural differentiation compared to previous measures by Engler et. al.

While the Bradford assay’s results demonstrate that MSCs might grow best in 0.25% collagen without RA, they do not confirm whether the stiffness of the collagen is inducing neural differentiation. A Western blot will be able to provide this evidence.

Future work includes determining the stiffness limits that allow for the differentiation of MSCs into neural glial cells by repeating the differentiation experiment with more gel concentrations. The effect of CNPs on MSC differentiation will also need to be investigated. As well, mechanical testing will need to be repeated with both MSCs and CNPs. Eventually, the mechanism of delivery of both CNPs and MSCs into surrounding tissues will need to be studied.

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Nov 18th, 10:00 AM Nov 18th, 11:00 AM

Collagen Gel as a Scaffold for Mesenchymal Stem Cells and Chitosan Nanoparticles for a Tissue-Engineered Brain Patch to Promote Neural Regeneration

BSC-Ursa Minor 94

Traumatic Brain Injury (TBI) has devastating effects through both the initial trauma and the secondary injury from inflammation. The “Brain Patch” is a tissue-engineered TBI treatment, aimed at reducing secondary injury. The collagen gel patch is infused with antibacterial and anti-inflammatory chitosan nanoparticles (CNPs) and mesenchymal stem cells (MSCs) that encourage regrowth of neural connections. Since the differentiation of MSCs into neural cells is directly affected by the stiffness of the extracellular matrix (ECM)1, characterizing the stiffness of the collagen gel is essential for controlling MSC differentiation. By varying collagen concentration (%w/v) from 0.25%-1.0%, we have been able to reproducibly create gels with compressive bulk stiffnesses from 2-30 kPa, which corresponds to the substrate stiffness that allows MSCs to differentiate into neural cells1 (Fig. 1a). To determine the ideal scaffold conditions, MSCs were cultured on collagen gels with and without retinoic acid (RA) to induce differentiation to neural cells. The best MSC growth conditions were on the 0.25% gels without RA (Fig. 1b). A Western Blot will quantify the neural markers, MAP2 and β-Tubulin, to assess the optimal differentiation conditions. We also determined the effect of MSCs and CNPs on gel stiffness. Initial results show that the addition of CNPs to collagen gels at expected antibacterial concentrations2 does not significantly alter the stiffness of the gels. The addition of MSCs inside the collagen gels significantly increases the gel stiffness (Fig. 1a). Creating collagen gels within appropriate stiffness ranges and characterizing the effects of CNPs and MSCs on the stiffness in order to induce neural differentiation while maintaining antibacterial properties is a groundbreaking step towards engineering a Brain Patch.

Figure 1. a) Stiffness of 0.5% collagen gels infused with varying concentrations of MSCs; b) Bradford Assay results of 0.25% and 1% collagen gels, with and without retinoic acid, indicating total protein of samples when cultured with retinoic acid. Higher protein concentration corresponds to higher cell number.

References:

  1. Engler, AJ et. al, Cell, 2006, 126, pp. 677-689.

  2. Qi, L et al, Carbohydr Res, 2004, 339, pp. 2693-2700.