This application aims to provide a mechanistic understanding of the effect of gradients of physical and chemical guidance cues (GCs), individually and combinatory, on guidance and modulation of axonal growth. The proposed study will specifically answer to questions whether: (1) immediate turning of growth cone depends on the difference between the concentration gradients on the left- and right-hand sides of the growth cone; (2) immediate and biased turning and growth-rate modulation work together to guide axons towards their targets; (3) integration of gradients of multiple cues can provide a precise regulation mechanism for axonal guidance. Axons are guided along specific pathways by gradients of attractive and repulsive cues in their extracellular environment. To understand the effect of gradients of guidance cues individually or in combination on growth cone turning and growth rate modulation, the development of platforms that are capable of producing precisely controlled shape gradients of guidance cues is essential. I propose to develop an inexpensive and high- throughput technology that is capable of providing precise, reproducible, and arbitrarily shaped gradients of physical and biochemical cues to direct and modulate axonal growth. For these studies, we will first fabricate aligned nanotubes of conducting polymer loaded with nerve growth factor on micro-fabricated electrode arrays. To release the entrapped nerve growth factor, we will actuate these nanotubes by applying electrical voltages. By varying the actuating voltage across the electrode array, we will create precisely controlled gradients of released nerve growth factor on these microelectrodes. Next, we will generate gradients of substrate-bound molecules, in this case laminin, on conducting polymer nanotubes across the electrode array. Inclusion of laminin on the nanotubes will be achieved by using this protein as a dopant during electropolymerization of conducting polymer. We will employ different concentrations of laminin on individual electrode sites to achieve the desired gradient profile. To generate gradients of surface topography, we will create gradients in diameter and surface roughness of aligned conducting polymer nanotubes on the micro-fabricated electrode arrays. We will modulate (a) the diameter of conducting polymer nanotubes by varying the time of electrochemical polymerization of conducting polymer, and (b) the surface roughness of conducting polymer nanotubes by varying the current density applied during electrodeposition. Finally, we will develop a 3D conduit consisting of a PDMS guidance channel that contains nanostructured conducting polymers that provide (i) physical and biochemical growth cues, and (ii) low impedance electrodes to monitor axonal growth by electrophysiological recording along the regeneration pathway. This multifunctional conduit will be tested in vitro and vivo to determine the effect of gradient of multiple guidance cues on axonal growth direction and rate. The results of these studies may significantly impact society by paving the way for a solution to the major clinical problem of axon regeneration and guidance.

Public Health Relevance

Nerve injury in both central and peripheral nervous system (CNS and PNS) is a major health problem. According to the National Spinal Cord Injury Statistical Center, there are approximately 290,000 individuals in the US who suffer from spinal cord injuries with about 12,000 new injuries occurring each year. The findings of this research will, therefore, have a significant impact on public health.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS087224-04
Application #
9271054
Study Section
Biomaterials and Biointerfaces Study Section (BMBI)
Program Officer
Jakeman, Lyn B
Project Start
2014-04-01
Project End
2019-03-31
Budget Start
2017-04-01
Budget End
2018-03-31
Support Year
4
Fiscal Year
2017
Total Cost
$296,297
Indirect Cost
$99,422
Name
University of Houston
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
036837920
City
Houston
State
TX
Country
United States
Zip Code
77204
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