Pattern recognition of amino acid signatures in retinal neurons

TLDR: Pattern recognition of amino acid signals partitions the cells of the goldfish retina into nine statistically unique biochemical theme classes and permits a first-order chemical mapping of virtually all cellular space.

Abstract: Pattern recognition of amino acid signals partitions the cells of the goldfish retina into nine statistically unique biochemical theme classes and permits a first-order chemical mapping of virtually all cellular space. Photoreceptors, bipolar cells, and ganglion cells display a set of unique, nominally glutamatergic type E1, E1+E2, and E4 signatures, respectively. All horizontal cells are assignable to a GABAergic gamma 2 class or a non-GABAergic class with a glutamate-rich E3 signature. The amacrine cell layer is largely a mixture of (1) a taurine-dominated T1 Muller's cell signature and (2) GABAergic gamma 1, glycinergic G1, and dual glycinergic/GABAergic G gamma 1 amacrine cell signatures. Several major conclusions emerge from this work. (1) Glutamatergic, GABAergic, and glycinergic neural signatures and glial signatures account for over 99% of the cellular space in the retina. (2) All known neurons in the goldfish retina are associated with a set of conventional nonpeptide neurotransmitters. (3) Multiple forms of metabolic profiles are associated with a single nominal neurotransmitter category. (4) Glutamate and aspartate contents exhibit overlapping distributions and are not adequate univariate probes for identifying cell classes. (5) Signatures can serve as quantitative measures of cell state.