(M-481) Grayscale Image Z-Stack-Guided Biochemical Customization of Hydrogel Biomaterials

Introduction:: User-programmable engineered tissues and materials that can facilitate them are vital to the ongoing development of next-generation therapeutics. As difficult problems such as symmetry breaking in organoid culture and the near-infinite variability of personalized medicine approach the forefront of biomedical research, it will be vital to reproduce living tissue morphology and biochemical complexity across four dimensions (i.e., 3D space and time) and at scales that are relevant to translational application. At present, multiphoton optical lithography offers the requisite 3D control of biomaterial fabrication for such applications but suffers from significant, often prohibitive, time and resource costs. Simultaneous advances in patterning hardware, software, and photochemistry are needed to harness this powerful technology for biomaterials and tissue engineering applications of the future. We developed “grayscale image z-stack-guided multiphoton optical lithography” (GIZMO) as a fundamentally new type of biomaterial fabrication technique that enables intuitive and user-defined engineering of complex tissues at unprecedented scales. GIZMO represents a disruptive advance in patterned biomaterial fabrication that should unlock new capabilities in 4D tissue culture and opportunities to probe fundamental biology.

Materials and Methods:: Following a user-inputted grayscale image stack, GIZMO methods were designed to control the extent of biomaterial modulation on a voxel-by-voxel basis by applying position-dependent laser power variation during raster scanning. Briefly, image stacks were processed into tiled layers with user-specified size and resolution. Individual pixel values in these layers inform the dynamic laser power at each location (Fig. 1). In conjunction with novel highly two-photon sensitive chemistries developed in our lab, validation patterns for mechanical and biochemical modulation of hydrogel biomaterials were generated. Synthetic degradable and non-degradable gels were cast using standard click-modified polymers and chemistries already vetted by the tissue engineering field. Patterning fidelity and extent were validated using a combination of multiphoton and fluorescence confocal imaging techniques.

Results, Conclusions, and Discussions:: Chemical and physical patterns generated by GIZMO are faithful to their digital representations near or below 1 µm resolution over 10s of cubic millimeter gel volumes with full grayscale control. Additionally, dynamic laser power variation abstracts fabrication time from pattern complexity, resulting in orders of magnitude gains in the volumetric rate of patterning.

GIZMO affords unprecedented customization of hydrogel biomaterials, both in chemical and physical spaces, in full 3D space. Using input image stacks derived from native tissue fluorescent micrographs, GIZMO affords direct replication of key biological features at subcellular resolutions. These techniques open the door to mimicking the dynamic heterogeneity of native tissue within engineered constructs.

GIZMO uniquely permits large-scale hydrogel biochemical customization with non-discrete biomolecular patterns at sub- or single-micron resolution and on timeframes compatible with modern tissue culture. We expect this work will translate smoothly to 3D cell culture applications due to the use of standard multiphoton patterning equipment and emerging bioorthogonal photochemistries.


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