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Cortical cells were classified using an unsupervised cluster analysis based upon their quantitative and combinatorial immunoreactivity for glutamate, gamma-aminobutyric acid (GABA), aspartate, glutamine and taurine. Overall, cell class-specific amino acid signatures were found for 12 cellular types; seven GABA-immunoreactive (GABA-IR) populations (GABA1--7), three classes containing high glutamate levels (GLUT1--3) and two putative glial (GLIA1, 2) cell types. From their large somata, associated vertical processes and high glutamate content, the GLUT classes most probably correspond to pyramidal neurons. Two of the GLUT classes demonstrated complementary distributions in different cortical layers, suggesting spatial separation of cells differing in amino acid immunoreactivity. Of the seven GABA classes, two comprised cells with large somata and displayed medium to low glutamate levels. On the basis of size, these two populations may correspond to large basket cell interneurons. Glial populations could be divided into two classes: GLIA1 cells were more frequently associated with blood vessels and GLIA2 cells were more commonly seen in the lower cortical layers. This work demonstrates that signature recognition based upon amino acid content can be used to separate cortical cells into different categories and reveal further subclasses within these categories. This approach is complementary to other methods using physiological and molecular tools and ultimately will enhance our understanding of neuronal heterogeneity.

Cellular Diversity in Mouse Neocortex Revealed by Multispectral Analysis of Amino Acid Immunoreactivity