Microenvironments Engineered by Inkjet Bioprinting Spatially Direct Adult Stem Cells Towards Muscle- and Bone-Like Subpopulations

¹ Molecular Biosensor and Imaging Center, Carnegie Mellon University, Pittsburgh, PA; Children's Hospital of Pittsburgh of UPMC, Pittsburgh, PA
² Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA
³ Robotics Institute, Carnegie Mellon University, Pittsburgh, PA
⁴ Children's Hospital of Pittsburgh of UPMC, Pittsburgh, PA
⁵ Molecular Biosensor and Imaging Center, Carnegie Mellon University, Pittsburgh, PA
⁶ Institute for Complex Engineered Systems, Carnegie Mellon University, Pittsburgh, PA

^* To whom correspondence should be addressed. E-mail: pcampbel{at}cs.cmu.edu.

	Abstract

In vivo, growth factors exist as both soluble and as solid-phase molecules, immobilized to cell surfaces and within the extracellular matrix. We employed this rationale to develop more biologically-relevant approaches to study stem cell behaviors. We engineered stem cell microenvironments using inkjet bioprinting technology to create spatially-defined patterns of immobilized growth factors. Using this approach, we engineered cell fate towards the osteogenic lineage in register to printed patterns of bone morphogenetic protein (BMP) 2 contained within a population of primary muscle-derived stem cells (MDSCs) isolated from adult mice. This patterning approach was conducive to patterning the MDSCs into sub-populations of osteogenic or myogenic cells simultaneously on the same chip. When cells were cultured under myogenic conditions on BMP-2 patterns, cells on pattern differentiated towards the osteogenic lineage; whereas cells off pattern differentiated towards the myogenic lineage. Time-lapse microscopy was used to visualize the formation of multinucleated myotubes and immunocytochemistry was used to demonstrate expression of myosin heavy chain (fast) (MHC-f) in cells off BMP-2 pattern. This work provides proof-of-concept for engineering spatially-controlled multi-lineage differentiation of stem cells using patterns of immobilized growth factors. This approach may be useful for understanding cell behaviors to immobilized biological patterns and could have potential applications for regenerative medicine.