The development and function of the central nervous system rely on the microtubule (MT) and actin cytoskeletons and their respective effectors. Although the structural role of the cytoskeleton has long been acknowledged in neuronal morphology and activity, it was recently recognized to play the role of a signaling platform. Following this recognition, research into Microtubule Associated Proteins (MAPs) diversified. Indeed, historically, structural MAPs—including MAP1B, MAP2, Tau, and MAP6 (also known as STOP);—were identified and described as MT-binding and -stabilizing proteins. Extensive data obtained over the last 20 years indicated that these structural MAPs could also contribute to a variety of other molecular roles. Among multi-role MAPs, MAP6 provides a striking example illustrating the diverse molecular and cellular properties of MAPs and showing how their functional versatility contributes to the central nervous system. In this review, in addition to MAP6’s effect on microtubules, we describe its impact on the actin cytoskeleton, on neuroreceptor homeostasis, and its involvement in signaling pathways governing neuron development and maturation. We also discuss its roles in synaptic plasticity, brain connectivity, and cognitive abilities, as well as the potential relationships between the integrated brain functions of MAP6 and its molecular activities. In parallel, the Collapsin Response Mediator Proteins (CRMPs) are presented as examples of how other proteins, not initially identified as MAPs, fall into the broader MAP family. These proteins bind MTs as well as exhibiting molecular and cellular properties very similar to MAP6. Finally, we briefly summarize the multiple similarities between other classical structural MAPs and MAP6 or CRMPs.In summary, this review revisits the molecular properties and the cellular and neuronal roles of the classical MAPs, broadening our definition of what constitutes a MAP.

Morphometry characterization is an important procedure in describing neuronal cultures and identifying phenotypic differences. This task usually requires labor-intensive measurements and the classification of numerous neurites from large numbers of neurons in culture. To automate these measurements, we wrote AutoNeuriteJ, an imageJ/Fiji plugin that measures and classifies neurites from a very large number of neurons. We showed that Auto-NeuriteJ is able to detect variations of neuritic growth induced by several compounds known to affect the neuronal growth. In these experiments measurement of more than 5000 mouse neurons per conditions was obtained within a few hours. Moreover, by analyzing mouse neurons deficient for the microtubule associated protein 6 (MAP6) and wild type neurons we illustrate that AutoNeuriteJ is capable to detect subtle phenotypic difference in axonal length. Overall the use of AutoNeuriteJ will provide rapid, unbiased and accurate measurement of neuron morphologies.