Heterogeneous Expression of Nuclear Encoded Mitochondrial Genes Distinguishes Inhibitory and Excitatory Neurons.

Mitochondrial composition varies by organ and their constituent cell types. This mitochondrial diversity likely determines variations in mitochondrial function. However, the heterogeneity of mitochondria in the brain remains underexplored despite the large diversity of cell types in neuronal tissue. Here, we used molecular systems biology tools to address whether mitochondrial composition varies by brain region and neuronal cell type in mice. We reasoned that proteomics and transcriptomics of microdissected brain regions combined with analysis of single-cell mRNA sequencing (scRNAseq) could reveal the extent of mitochondrial compositional diversity. We selected nuclear encoded gene products forming complexes of fixed stoichiometry, such as the respiratory chain complexes and the mitochondrial ribosome, as well as molecules likely to perform their function as monomers, such as the family of SLC25 transporters. We found that the proteome encompassing these nuclear-encoded mitochondrial genes and obtained from microdissected brain tissue segregated the hippocampus, striatum, and cortex from each other. Nuclear-encoded mitochondrial transcripts could only segregate cell types and brain regions when the analysis was performed at the single-cell level. In fact, single-cell mitochondrial transcriptomes were able to distinguish glutamatergic and distinct types of GABAergic neurons from one another. Within these cell categories, unique SLC25A transporters were able to identify distinct cell subpopulations. Our results demonstrate heterogeneous mitochondrial composition across brain regions and cell types. We postulate that mitochondrial heterogeneity influences regional and cell type-specific mechanisms in health and disease.

Studying alcohol use disorder using Drosophila melanogaster in the era of 'Big Data'.

Our understanding of the networks of genes and protein functions involved in Alcohol Use Disorder (AUD) remains incomplete, as do the mechanisms by which these networks lead to AUD phenotypes. The fruit fly (Drosophila melanogaster) is an efficient model for functional and mechanistic characterization of the genes involved in alcohol behavior. The fly offers many advantages as a model organism for investigating the molecular and cellular mechanisms of alcohol-related behaviors, and for understanding the underlying neural circuitry driving behaviors, such as locomotor stimulation, sedation, tolerance, and appetitive (reward) learning and memory. Fly researchers are able to use an extensive variety of tools for functional characterization of gene products. To understand how the fly can guide our understanding of AUD in the era of Big Data we will explore these tools, and review some of the gene networks identified in the fly through their use, including chromatin-remodeling, glial, cellular stress, and innate immunity genes. These networks hold great potential as translational drug targets, making it prudent to conduct further research into how these gene mechanisms are involved in alcohol behavior.