Cellular diversity in mouse neocortex revealed by multispectral analysis of amino acid immunoreactivity

Citation
E. Hill et al., Cellular diversity in mouse neocortex revealed by multispectral analysis of amino acid immunoreactivity, CEREB CORT, 11(8), 2001, pp. 679-690
Citations number
37
Categorie Soggetti
Neurosciences & Behavoir
Journal title
CEREBRAL CORTEX
ISSN journal
10473211 → ACNP
Volume
11
Issue
8
Year of publication
2001
Pages
679 - 690
Database
ISI
SICI code
1047-3211(200108)11:8<679:CDIMNR>2.0.ZU;2-4
Abstract
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 hi gh glutamate content, the GLUT classes most probably correspond to pyramida l neurons. Two of the GLUT classes demonstrated complementary distributions in different cortical layers, suggesting spatial separation of cells diffe ring in amino acid immunoreactivity. Of the seven GABA classes, two compris ed cells with large somata and displayed medium to low glutamate levels. On the basis of size. these two populations may correspond to large basket ce ll interneurons. Glial populations could be divided into two classes: GLIA1 cells were more frequently associated with blood vessels and GLIA2 cells w ere more commonly seen in the lower cortical layers. This work demonstrates that signature recognition based upon amino acid content can be used to se parate cortical cells into different categories and reveal further subclass es within these categories. This approach is complementary to other methods using physiological and molecular tools and ultimately will enhance our un derstanding of neuronal heterogeneity.