Factorial analysis of adaptable properties of self-assembling peptide matrix on cellular proliferation and neuronal differentiation of pluripotent embryonic carcinoma

An integrative and quantitative approach for systematically studying the effects of changing the matrix environment on pluripotent cell viability and neuronal differentiation was demonstrated. This approach, based on factorial analysis and a self-assembling peptide (SAP) matrix, was exemplified using P19 as a pluripotent cell model. In a two-level, three-factor factorial design of experiments, three niche factors, namely, culture dimensionality, fixed biochemical signal and mechanical stiffness, were simultaneously investigated. We found that cell growth was slowed in matrices containing IKVAV epitopes on the SAP constructs, and neuronal differentiation was promoted synergistically by culturing in a three-dimensional matrix and in the presence of IKVAV. Variation of the storage modulus from around 262 Pa to 672 Pa had no significant effect on either viability or differentiation. This approach should be applicable to studying how niche properties that are tunable using SAPs affect the behavior of pluripotent cells in general, thus generating guidelines for constructing artificial matrices.