Sulfation modification of dopamine in brain regulates aggregative behavior of animals

Behavioral plasticity and the underlying neuronal plasticity represent a fundamental capacity of animals to cope with environmental stimuli. Behavioral plasticity is controlled by complex molecular networks that act under different layers of regulation. While various molecules have been found to be involved in the regulation of plastic behaviors across species, less is known about how organisms orchestrate the activity of these molecules as part of a coherent behavioral response to varying environments. Here we discover a mechanism for the regulation of animal behavioral plasticity involving molecular sulfation in the brain, a modification of substrate molecules by sulfotransferase (ST)-catalyzed addition of a sulfonate group (SO₃) from an obligate donor, 3^′-phosphoadenosine 5^′-phosphosulfate (PAPS) to the substrates. We investigated aggregation behaviors of migratory locusts, which are well-known for extreme phase change plasticity triggered by population density. The processes of PAPS biosynthesis acted efficiently on induction of locust behavioral transition: Inhibition of PAPS synthesis solicited a behavioral shift from gregarious to solitarious states; external PAPS dosage, by contrast, promoted aggregation in solitarious locusts. Genetic or pharmacological intervention in the sulfation catalyzation resulted into pronounced solitarizing effects. Analysis of substrate-specific STs suggests a widespread involvement of sulfated neurotransmitters in the behavioral response. Dopamine in the brain was finally identified to be actively sulfate conjugated, and the sulfate conjugation enhanced the free DA-mediated behavioral aggregation. Similar results in Caenorhabditis elegans and mice indicate that sulfation may be involved more broadly in the modulation of animal aggregation. These findings reveal a general mechanism that effectively regulates animal social-like behavioral plasticity, possibly through sulfation-mediated modification of neural networks.