"To measure is to know": how advances in image analysis are supporting neural repair strategies

Abstract

Neuronal regeneration in the peripheral nervous system arises via a synergistic interplay of neurotrophic factors, integrins, cytoskeletal proteins, mechanical cues, cytokines, stem cells, glial cells and astrocytes. A plethora of additional potential factors are yet to be discovered (Yiu and He, 2006). In spite of encouraging progress, axonal repair in the central nervous system (CNS) remains elusive. There is a growing consensus that in order to capture such a moving target, a systematic approach has to eclipse the “trial and error” methodology that has proven so effective in many other instances. The role of large scale automation is critical in such an undertaking. This philosophy has in fact been championed for many years already by Big-Pharma together with larger academic laboratories under the heading: “High Content Analysis” (HCA). Neuronal cells in 2D microplate cultures are generally used (see Figure 1A). They are exposed to libraries of test compounds and variable environmental conditions as their response is being measured (e.g., axonal length, nucleus size, number of branching points…). More complex model systems are gaining traction, including cell co-cultures, neural explants, 3D cell cultures, organotypic slices, or whole organisms such as zebrafish. But traditional neuronal cell cultures remain a workhorse of research against neurodegenerative diseases.