Metabolic profiling of the mouse retina using amino acid signatures: Insight into developmental cell dispersion patterns

Pattern recognition has been used for the complete and statistically rigid classification of retinal neurons in vertebrates such as the adult cat, primate, rat and goldfish. Here, we label the mouse retina with antibodies against seven amino acids and use pattern recognition to characterize distinct retinal neurochemical cell classes based on their unique amino acid signatures. We followed the development of the cell classes in the X-inactivation transgenic mouse expressing the lacZ reporter gene on one X-chromosome. This mouse allows clonally related cells to be identified through differential beta-galactosidase activity due to random X-chromosome inactivation. Pattern recognition analysis partitioned the retina into nine neuronal classes at birth, increasing to 19 classes at eye opening and 26 classes by adulthood. Emergence of new cell classes was partly attributed to new neuron types and partly to the splitting of classes from early ages from refinement of their amino acid profiles. All six GABAergic amacrine cell classes and most ganglion cell classes appeared by P7 whilst all the glycinergic amacrine cell classes did not appear till adulthood. Separable bipolar cell classes were not detected till eye opening. Photoreceptor cell classes were detected at P3 but inner and outer segments did not form separable classes until adulthood. More importantly, we show that cells which share common amino acid profiles also shared cell dispersion patterns. GABAergic amacrine cell classes with conventional and displaced counterparts transgressed clonal boundaries whereas GABAergic amacrine cell classes found exclusively in the inner nuclear layer and all glycinergic amacrine cell classes did not transgress. Ganglion cells displayed both dispersion patterns. This study provides a comprehensive neurochemical atlas of the developing mouse retina, tracking the amino acid levels within distinct neuronal populations and highlighting unique migratory patterns within subpopulations of inner retinal neurons. (C) 2013 Elsevier Inc. All rights reserved.