Amphetamine (AMPH) is a widely abused drug, but before it was restricted in use it was an effective
weight loss agent. We have shown that a distinct group of neurons controls a large part of the
body’s weight loss response to amphetamine. In 2017 a single cell RNA sequencing project was
published (Campbell, Macosko et al. 2017) that described transcriptional profiles of 21,000 neurons,
amongst which are the neurons we have shown mediate the weight loss caused by amphetamine.
Amphetamine does not act directly on these neurons, rather AMPH increases the concentration of
the monoamines dopamine, noradrenaline and serotonin in the brain. We wish to analyse the
Campbell data set 1 to determine which sub populations of our neurons of interest express
monoamine neurotransmitter receptors.
Initially we anticipate using Seurat and principle component analysis clustering to tease apart the
various population of relevant neurons, and then test for the expression of genes that encode
monoamine receptors, because it is these monoamine receptors that mediate the metabolic (weight
loss) effects of AMPH. We anticipate that the identification of appropriate populations of neurons
will enable direct targeting of those neurons by chemogenetic techniques to test their effects on
metabolism. This will allow us to determine if those neurons are targets for further drug
development. We seek a Masters level bioinformatics student to help with the analysis of this data
and the design of future single cell RNA sequencing studies to help us identify new drug targets,
Campbell, J. N., E. Z. Macosko, H. Fenselau, T. H. Pers, A. Lyubetskaya, D. Tenen, M. Goldman, A. M. Verstegen, J. M. Resch, S. A. McCarroll, E. D. Rosen, B. B. Lowell and L. T. Tsai (2017). "A molecular census of arcuate hypothalamus and median eminence cell types." Nat Neurosci 20(3): 484-496.
Raw Drop-seq data and processed DGE files are available at GEO accession code GSE93374.
Determine which monoamine neurotransmitter receptors cluster with various hypothalamic
neuropeptides based on analysis of a published database
R Seurat, principle component analysis.