THE POWER OF CAD/CAM LASER BIOPRINTING AT THE SINGLE-CELL LEVEL: EVOLUTION OF PRINTING - 3D Bioprinting and Nanotechnology in Tissue Engineering and Regenerative Medicine - page 94

extracellular environment has begun to develop, including how individual molecular guidance cues
affect guidance ( McCormick and Leipzig, 2012 ; Yu et al., 2008 ). Where single-cell printing can add
value is recapitulating the numerous external cellular “guideposts” each axon encounters along its
journey, to study the multitude of cellular interactions that coalesce during development.
4.5.1.2 Engineered Circuits
The ability to fabricate highly specific patterns of neuronal cells has the potential to lend insight into
many of the functional units of the brain and beyond. Xu et al . were the first to demonstrate that printed
neuronal cells retained healthy electrophysiological characteristics ( Xu et al., 2006 ). The subsequent
ability to engineer neuronal circuits at the single-cell level was demonstrated by Edwards et al. with
hippocampal neurons ( Edwards et al., 2013 ). In a similar vein, techniques have been demonstrated
to control individual synaptic connectivity of larger homogenous neuronal populations, enabling specific
control over network and circuit properties ( Staii et al., 2009 ; Vogt et al., 2005 ).
These methods do not allow for incorporation of multiple cell types, severely limiting their ability to
recapitulate critical heterogeneous cell synapses. The advantages of laser bioprinting to control the pre-
cise location and association of multiple cell types, in combination with hydrogel and biomolecular-based
models for controlled axonal outgrowth, would allow the creation of mono and polysynaptic circuits
between heterogeneous neuronal populations ( Curley and Moore, 2011 ; Horn-Ranney et al., 2013 ). La-
ser direct write represents the only technology currently available to accomplish this complicated feat,
and the ability to recreate neural tracts of virtually any system at the single- and multicell level would
allow for unprecedented experiments into the function of higher-order activities such as memory, learning,
cognition, locomotion, and pain.
Highly specific brain regions are known to integrate and communicate through transient synapses, fa-
cilitating the signaling that encodes and dictates all activity. Further complicating matters, these neuronal
connections are constantly being strengthened, weakened, or lost based on external outputs. For example,
within the hippocampus, multiple cell types are known to control memory and spatial navigation ( Dick-
erson and Eichenbaum, 2010 ; Turrigiano, 2012 ). Similarly, thalamocortical circuits govern cognition,
behavior, and consciousness, with clinical implications in autism, schizophrenia, and attention deficit
disorder ( Buonanno, 2010 ; Sudhof, 2008 ). Sensorimotor neuron integration is another wide ranging path-
way that influences motor control and proprioception as well as all of the five classic senses ( Goulding
et al., 2002 ). The ability to understand and engineer highly specific sensorimotor circuits also has implica-
tions in advancing prosthetic design to interface with native tissue and restore near-natural function ( Guo
et al. 2012 ; Raspopovic et al., 2014 ). Another system with implication in limb prostheses is the neuromus-
cular junction. Das et al. have defined and explored in vitro models for synapse formation, though to date
only in heterogeneous dissociated cultures ( Das et al., 2010, 2007 ). In both cases, precisely how synaptic
plasticity influences information processing is not yet understood. All of these systems are highly complex
and divergent across applications, but laser direct write could be used to manipulate long-term studies of
cellular, genetic, and molecular influences on individual synapse formation and maintenance. Due to the
stochastic nature of these systems, the high-throughput potential of laser direct write will be critical to
increasing our understanding of normal function and will inform treatment of pathological states.
4.5.1.3 Non-neuronal Interactions
The consequences of studying engineered interactions between neuronal and non-neuronal cells also
have application outside of synaptic function. Though the number is still contested, there are at least
as many non-neuronal as neuronal cells in the brain ( Azevedo et al., 2009 ). Clearly supportive glial