Danielle Mor (Murphy Lab): The role of branched chain amino acid transferase 1 in Parkinson’s disease, aging, and longevity
Parkinson’s disease (PD) is primarily a movement disorder characterized by the loss of dopaminergic and cholinergic neurons, as well as the formation of abnormal protein aggregates containing alpha-synuclein. The mechanisms that induce neurodegeneration in PD are still poorly understood, and over 70% of cases have no known cause. Using a new method we created that combines human genome-wide association studies with tissue-specific functional networks in C. elegans, we discovered a novel link between branched-chain amino acid transferase 1 (bcat-1), which catalyzes the first step in branched-chain amino acid (BCAA) catabolism, and PD. We found that BCAT-1 expression is normally high in PD-susceptible brain regions, and is reduced in the substantia nigra of PD patients. Reduction of neuronal bcat-1 in C. elegans caused an age-dependent, abnormal curling motor defect, and associated degeneration of cholinergic neurons. Moreover, in the context of alpha-synuclein toxicity, bcat-1 reduction accelerated the loss of dopaminergic neurons. To identify new potential treatments for PD, we developed software that detects and quantifies the curling motor deficit, and conducted a screen of 50 FDA-approved compounds for those that improve motor function. We found that existing Parkinson’s medications restore motor function in bcat-1 RNAi-fed worms, and we identified new drug candidates for PD treatment. Paradoxically, while our findings link bcat-1 knockdown to neurodegeneration and functional decline, reducing bcat-1 or elevating BCAAs greatly lengthens lifespan in yeast, worms, and mice. Simply extending lifespan is therefore insufficient for maintaining quality of life with age. Investigating the effects of BCAA metabolism on both lifespan and neuronal health may uncover disease-modifying therapies and interventions that promote longevity without sacrificing brain function.
Amir Erez (CPBF, Wingreen Lab): Systematic discovery and analysis of overexpressed genes in the human microbiome
The human gut microbiome is composed of hundreds of species, and includes bacteria, archea, fungi, protozoa, and viruses. With this enormous diversity of microbes, it is often difficult to discern which genes, pathways, and metabolites are important for life in the human gut, and may therefore mediate relevant interactions in this complex ecosystem. Here, we develop a computational method for the systematic identification of microbiome-derived genes that are highly expressed in human samples, with no prior taxonomical or functional assumptions. By applying this method to three human fecal microbiome cohorts where both metagenomic and metatranscriptomic data exist, we discover 20K highly expressed genes that span all microbial life forms and encode diverse biological functions. We conclude by investigating the temporal correlations and the co-expression profiles of these genes.