The norepinephrine transporter (NET), dopamine transporter (DAT), and serotonin transporter (SERT) catalyze the reuptake of their respective monoamine neurotransmitters from the extracellular space surrounding synaptic membranes, terminating neurotransmission. These transporters are critical regulators of neuronal signaling. Non-synonymous sequence polymorphisms of NET, DAT and SERT are implicated in numerous psychiatric disorders, including major depression, anxiety disorders and obsessive compulsive disorder (OCD), and the transporters are molecular targets for widely prescribed mental health drugs. Deep mutational scanning is a new technology that combines directed evolution of large, diverse libraries of sequence variants with deep sequencing to track the phenotypes of potentially thousands of mutants in a single experiment. This makes it possible to experimentally determine a comprehensive fitness landscape of a protein, but this technique has yet to be applied to human transmembrane proteins evolving in human cell culture.
The specific aims of this project are Aim 1: to experimentally determine the fitness landscapes of monoamine neurotransmitter transporters. Single site-saturation mutagenesis libraries encoding all amino acid substitutions of NET, DAT and SERT will be transfected into human cells, which will subsequently be sorted for variants that are expressed on the cell surface and actively transport a fluorescent neurotransmitter analogue. Enrichment scores for each mutation during in vitro evolution will be calculated, and from these fitness landscapes insight will be gained into critical residues for transporter folding, surface trafficking, oligomerization, substrate binding, transport and regulation. In addition to learning how the transporter sequences relate to their basic molecular functions, the data will pre-emptively describe molecular phenotypes for all possible single amino acid substitutions that may exist in the human population. This is a radical change from existing approaches where non-synonymous SNPs are identified first, perhaps in clinical populations with psychiatric disease, and then molecular activity is investigated.
Aim 2 : Develop a deep mutational scanning- based assay for mapping drug interaction sites to protein sequences of neurotransmitter transporters. A diverse library of SERT mutants will be screened by deep mutational scanning for variants with decreased response to the drugs (S)-citalopram and paroxetine. Mutations that `rescue' transport will be mapped to crystal structures of human SERT bound to (S)-citalopram and paroxetine, which will validate whether this method can successfully identify known orthosteric and allosteric binding sites. In addition to providing a new technology platform for mapping drug interaction sites with residue-level resolution, the data will again pre- emptively describe how all possible non-synonmous sequence variants of the transporter impact drug potency. We envisage in the future deep mutational scanning data will inform interpretation of a patient's genotype, even for rare alleles not previously observed in the clinic, and influence practitioner drug choice.
Using new technologies in genomics that combine in vitro evolution of large numbers of protein variants with deep sequencing, the expression and activity of tens of thousands of sequence variants of the neurotransmitter transporters for serotonin, dopamine and norepinephrine will be characterized. From this unprecedented mutational analysis, it will be both possible to gain insight into molecular mechanisms of transport, and `pre- emptively' determine the transport phenotypes of all single amino acid-substituted alleles that may exist in the human population and may be associated with psychiatric disease. The methods will also be adapted in proof- of-concept studies to map transporter interaction sites with antidepressant drugs.